6 Ecogeographical variables

Creation procedures of every EGV.

6.1 Climate_CHELSAv2.1-bio1_cell

filename: Climate_CHELSAv2.1-bio1_cell.tif

layername: egv_1

English name: Mean annual daily mean air temperature (°C) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējā ikdienas gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Procedure: Directly follows CHELSA v2.1. EGV is prepared with the workflow egvtools::downscale2egv() with inverse distance weighted (power = 2) gap filling and soft smoothing (power = 0.5) over 5 km radius of every cell.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio1_cell.tif"
layername="egv_1"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio1_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.2 Climate_CHELSAv2.1-bio10_cell

filename: Climate_CHELSAv2.1-bio10_cell.tif

layername: egv_2

English name: Mean daily mean air temperatures (°C) of the warmest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada siltākā ceturkšņa vidējā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio10_cell.tif"
layername="egv_2"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio10_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.3 Climate_CHELSAv2.1-bio11_cell

filename: Climate_CHELSAv2.1-bio11_cell.tif

layername: egv_3

English name: Mean daily mean air temperatures (°C) of the coldest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada aukstākā ceturkšņa vidējā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio11_cell.tif"
layername="egv_3"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio11_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.4 Climate_CHELSAv2.1-bio12_cell

filename: Climate_CHELSAv2.1-bio12_cell.tif

layername: egv_4

English name: Annual precipitation amount (kg m⁻² year⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada nokrišņu daudzums (kg m⁻² gadā) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio12_cell.tif"
layername="egv_4"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio12_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.5 Climate_CHELSAv2.1-bio13_cell

filename: Climate_CHELSAv2.1-bio13_cell.tif

layername: egv_5

English name: Precipitation amount (kg m⁻² month⁻¹) of the wettest month (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Slapjākā mēneša nokrišņu daudzums (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio13_cell.tif"
layername="egv_5"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio13_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.6 Climate_CHELSAv2.1-bio14_cell

filename: Climate_CHELSAv2.1-bio14_cell.tif

layername: egv_6

English name: Precipitation amount (kg m⁻² month⁻¹) of the driest month (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Sausākā mēneša nokrišņu daudzums (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio14_cell.tif"
layername="egv_6"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio14_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.7 Climate_CHELSAv2.1-bio15_cell

filename: Climate_CHELSAv2.1-bio15_cell.tif

layername: egv_7

English name: Precipitation seasonality (kg m⁻²) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Nokrišņu sezonalitāte (kg m⁻²) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio15_cell.tif"
layername="egv_7"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio15_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.8 Climate_CHELSAv2.1-bio16_cell

filename: Climate_CHELSAv2.1-bio16_cell.tif

layername: egv_8

English name: Mean monthly precipitation amount (kg m⁻² month⁻¹) of the wettest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Slapjākā ceturkšņa vidējais nokrišņu daudzums mēnesī (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio16_cell.tif"
layername="egv_8"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio16_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.9 Climate_CHELSAv2.1-bio17_cell

filename: Climate_CHELSAv2.1-bio17_cell.tif

layername: egv_9

English name: Mean monthly precipitation amount (kg m⁻² month⁻¹) of the driest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Sausākā ceturkšņa vidējais nokrišņu daudzums mēnesī (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio17_cell.tif"
layername="egv_9"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio17_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.10 Climate_CHELSAv2.1-bio18_cell

filename: Climate_CHELSAv2.1-bio18_cell.tif

layername: egv_10

English name: Mean monthly precipitation amount (kg m⁻² month⁻¹) of the warmest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Siltākā ceturkšņa vidējais nokrišņu daudzuma mēnesī (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio18_cell.tif"
layername="egv_10"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio18_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.11 Climate_CHELSAv2.1-bio19_cell

filename: Climate_CHELSAv2.1-bio19_cell.tif

layername: egv_11

English name: Mean monthly precipitation amount (kg m⁻² month⁻¹) of the coldest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Aukstākā ceturkšņa vidējais nokrišņu daudzums mēnesī (kg m⁻² mēnesī) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio19_cell.tif"
layername="egv_11"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio19_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.12 Climate_CHELSAv2.1-bio2_cell

filename: Climate_CHELSAv2.1-bio2_cell.tif

layername: egv_12

English name: Mean diurnal air temperature range (°C) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Diennakts temperatūru amplitūda (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio2_cell.tif"
layername="egv_12"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio2_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.13 Climate_CHELSAv2.1-bio3_cell

filename: Climate_CHELSAv2.1-bio3_cell.tif

layername: egv_13

English name: Isothermality (ratio of diurnal variation to annual variation in temperatures) (°C) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Izotermalitāte (attiecība starp diennakts un gada temperatūras svārstībām) (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio3_cell.tif"
layername="egv_13"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio3_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.14 Climate_CHELSAv2.1-bio4_cell

filename: Climate_CHELSAv2.1-bio4_cell.tif

layername: egv_14

English name: Temperature seasonality (standard deviation of the monthly mean temperatures) (°C/100) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Temperatūru sezonalitāte (mēneša vidējo temperatūru standartnovirze) (°C/100) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio4_cell.tif"
layername="egv_14"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio4_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.15 Climate_CHELSAv2.1-bio5_cell

filename: Climate_CHELSAv2.1-bio5_cell.tif

layername: egv_15

English name: Mean daily maximum air temperature (°C) of the warmest month (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Siltākā mēneša vidējā ikdienas augstākā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio5_cell.tif"
layername="egv_15"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio5_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.16 Climate_CHELSAv2.1-bio6_cell

filename: Climate_CHELSAv2.1-bio6_cell.tif

layername: egv_16

English name: Mean daily minimum air temperature (°C) of the coldest month (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Aukstākā mēneša vidējā ikdienas zemākā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio6_cell.tif"
layername="egv_16"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio6_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.17 Climate_CHELSAv2.1-bio7_cell

filename: Climate_CHELSAv2.1-bio7_cell.tif

layername: egv_17

English name: Annual range of air temperature (°C) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada temperatūru amplitūda (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio7_cell.tif"
layername="egv_17"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio7_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.18 Climate_CHELSAv2.1-bio8_cell

filename: Climate_CHELSAv2.1-bio8_cell.tif

layername: egv_18

English name: Mean daily mean air temperatures (°C) of the wettest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Slapjākā ceturkšņa vidējā ikdienas vidējā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio8_cell.tif"
layername="egv_18"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio8_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.19 Climate_CHELSAv2.1-bio9_cell

filename: Climate_CHELSAv2.1-bio9_cell.tif

layername: egv_19

English name: Mean daily mean air temperatures (°C) of the driest quarter (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Sausākā ceturkšņa vidējā ikdienas vidējā gaisa temperatūra (°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-bio9_cell.tif"
layername="egv_19"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-bio9_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.20 Climate_CHELSAv2.1-clt-max_cell

filename: Climate_CHELSAv2.1-clt-max_cell.tif

layername: egv_20

English name: Maximum monthly cloud area fraction (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālais mēneša vidējais mākoņu segums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-clt-max_cell.tif"
layername="egv_20"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-clt-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.21 Climate_CHELSAv2.1-clt-mean_cell

filename: Climate_CHELSAv2.1-clt-mean_cell.tif

layername: egv_21

English name: Mean monthly cloud area fraction (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējais mākoņu segums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-clt-mean_cell.tif"
layername="egv_21"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-clt-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.22 Climate_CHELSAv2.1-clt-min_cell

filename: Climate_CHELSAv2.1-clt-min_cell.tif

layername: egv_22

English name: Minimum monthly cloud area fraction (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālais mēneša vidējais mākoņu segums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-clt-min_cell.tif"
layername="egv_22"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-clt-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.23 Climate_CHELSAv2.1-clt-range_cell

filename: Climate_CHELSAv2.1-clt-range_cell.tif

layername: egv_23

English name: Annual range of monthly cloud area fraction (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada mākoņu seguma amplitūda (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-clt-range_cell.tif"
layername="egv_23"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-clt-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.24 Climate_CHELSAv2.1-cmi-max_cell

filename: Climate_CHELSAv2.1-cmi-max_cell.tif

layername: egv_24

English name: Maximum monthly climate moisture index (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālais mēneša vidējais klimata mitruma indekss (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-cmi-max_cell.tif"
layername="egv_24"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-cmi-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.25 Climate_CHELSAv2.1-cmi-mean_cell

filename: Climate_CHELSAv2.1-cmi-mean_cell.tif

layername: egv_25

English name: Mean monthly climate moisture index (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējais klimata mitruma indekss (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-cmi-mean_cell.tif"
layername="egv_25"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-cmi-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.26 Climate_CHELSAv2.1-cmi-min_cell

filename: Climate_CHELSAv2.1-cmi-min_cell.tif

layername: egv_26

English name: Minimum monthly climate moisture index (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālais mēneša vidējais klimata mitruma indekss (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-cmi-min_cell.tif"
layername="egv_26"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-cmi-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.27 Climate_CHELSAv2.1-cmi-range_cell

filename: Climate_CHELSAv2.1-cmi-range_cell.tif

layername: egv_27

English name: Annual range of monthly climate moisture index (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada klimata mitruma indeksa amplitūda (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-cmi-range_cell.tif"
layername="egv_27"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-cmi-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.28 Climate_CHELSAv2.1-fcf_cell

filename: Climate_CHELSAv2.1-fcf_cell.tif

layername: egv_28

English name: Frost change frequency (number of events in which tmin or tmax go above or below 0°C) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Sasalšanas gadījumu biežums (zemākā vai augstākā temperatūra šķērso 0°C) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-fcf_cell.tif"
layername="egv_28"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-fcf_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.29 Climate_CHELSAv2.1-fgd_cell

filename: Climate_CHELSAv2.1-fgd_cell.tif

layername: egv_29

English name: First day of the growing season (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pirmā diena (TREELIM) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-fgd_cell.tif"
layername="egv_29"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-fgd_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.30 Climate_CHELSAv2.1-gdd0_cell

filename: Climate_CHELSAv2.1-gdd0_cell.tif

layername: egv_30

English name: Growing degree days heat sum above 0°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Aktīvo temperatūru summa no 0°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdd0_cell.tif"
layername="egv_30"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdd0_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.31 Climate_CHELSAv2.1-gdd10_cell

filename: Climate_CHELSAv2.1-gdd10_cell.tif

layername: egv_31

English name: Growing degree days heat sum above 10°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Aktīvo temperatūru summa no 10°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdd10_cell.tif"
layername="egv_31"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdd10_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.32 Climate_CHELSAv2.1-gdd5_cell

filename: Climate_CHELSAv2.1-gdd5_cell.tif

layername: egv_32

English name: Growing degree days heat sum above 5°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Aktīvo temperatūru summa no 5°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdd5_cell.tif"
layername="egv_32"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdd5_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.33 Climate_CHELSAv2.1-gddlgd0_cell

filename: Climate_CHELSAv2.1-gddlgd0_cell.tif

layername: egv_33

English name: Last growing degree day above 0°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pēdējā diena no 0°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gddlgd0_cell.tif"
layername="egv_33"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gddlgd0_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.34 Climate_CHELSAv2.1-gddlgd10_cell

filename: Climate_CHELSAv2.1-gddlgd10_cell.tif

layername: egv_34

English name: Last growing degree day above 10°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pēdējā diena no 10°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gddlgd10_cell.tif"
layername="egv_34"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gddlgd10_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.35 Climate_CHELSAv2.1-gddlgd5_cell

filename: Climate_CHELSAv2.1-gddlgd5_cell.tif

layername: egv_35

English name: Last growing degree day above 5°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pēdējā diena no 5°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gddlgd5_cell.tif"
layername="egv_35"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gddlgd5_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.36 Climate_CHELSAv2.1-gdgfgd0_cell

filename: Climate_CHELSAv2.1-gdgfgd0_cell.tif

layername: egv_36

English name: First growing degree day above 0°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pirmā diena no 0°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdgfgd0_cell.tif"
layername="egv_36"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdgfgd0_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.37 Climate_CHELSAv2.1-gdgfgd10_cell

filename: Climate_CHELSAv2.1-gdgfgd10_cell.tif

layername: egv_37

English name: First growing degree day above 10°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pirmā diena no 10°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdgfgd10_cell.tif"
layername="egv_37"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdgfgd10_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.38 Climate_CHELSAv2.1-gdgfgd5_cell

filename: Climate_CHELSAv2.1-gdgfgd5_cell.tif

layername: egv_38

English name: First growing degree day above 5°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas pirmā diena no 5°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gdgfgd5_cell.tif"
layername="egv_38"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gdgfgd5_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.39 Climate_CHELSAv2.1-gsl_cell

filename: Climate_CHELSAv2.1-gsl_cell.tif

layername: egv_39

English name: Length of the growing season (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonas garums (TREELIM) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gsl_cell.tif"
layername="egv_39"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gsl_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.40 Climate_CHELSAv2.1-gsp_cell

filename: Climate_CHELSAv2.1-gsp_cell.tif

layername: egv_40

English name: Accumulated precipitation amount (kg m⁻² year⁻¹) on growing season days (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Veģetācijas sezonā (TREELIM) uzkrātais nokrišņu daudzums (kg m⁻² year⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gsp_cell.tif"
layername="egv_40"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gsp_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.41 Climate_CHELSAv2.1-gst_cell

filename: Climate_CHELSAv2.1-gst_cell.tif

layername: egv_41

English name: Mean temperature of the growing season (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējā ikdienas gaisa temperatūra (°C) veģetācijas sezonā (TREELIM) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-gst_cell.tif"
layername="egv_41"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-gst_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.42 Climate_CHELSAv2.1-hurs-max_cell

filename: Climate_CHELSAv2.1-hurs-max_cell.tif

layername: egv_42

English name: Maximum monthly near-surface relative humidity (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālais mēneša vidējais gaisa mitrums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-hurs-max_cell.tif"
layername="egv_42"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-hurs-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.43 Climate_CHELSAv2.1-hurs-mean_cell

filename: Climate_CHELSAv2.1-hurs-mean_cell.tif

layername: egv_43

English name: Mean monthly near-surface relative humidity (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējais ikmēneša gaisa mitrums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-hurs-mean_cell.tif"
layername="egv_43"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-hurs-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.44 Climate_CHELSAv2.1-hurs-min_cell

filename: Climate_CHELSAv2.1-hurs-min_cell.tif

layername: egv_44

English name: Minimum monthly near-surface relative humidity (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālais mēneša vidējais gaisa mitrums (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-hurs-min_cell.tif"
layername="egv_44"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-hurs-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.45 Climate_CHELSAv2.1-hurs-range_cell

filename: Climate_CHELSAv2.1-hurs-range_cell.tif

layername: egv_45

English name: Annual range of monthly near-surface relative humidity (%) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada gaisa mitruma amplitūda (%) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-hurs-range_cell.tif"
layername="egv_45"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-hurs-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.46 Climate_CHELSAv2.1-lgd_cell

filename: Climate_CHELSAv2.1-lgd_cell.tif

layername: egv_46

English name: Last day of the growing season (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Pēdējā veģetācijas sezonas diena (TREELIM) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-lgd_cell.tif"
layername="egv_46"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-lgd_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.47 Climate_CHELSAv2.1-ngd0_cell

filename: Climate_CHELSAv2.1-ngd0_cell.tif

layername: egv_47

English name: Number of days at which 2m air temperature > 0°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Dienu skaits, kurā gaisa temperatūra 2 m augstumā pārsniedz 0°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-ngd0_cell.tif"
layername="egv_47"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-ngd0_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.48 Climate_CHELSAv2.1-ngd10_cell

filename: Climate_CHELSAv2.1-ngd10_cell.tif

layername: egv_48

English name: Number of days at which 2m air temperature > 10°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Dienu skaits, kurā gaisa temperatūra 2 m augstumā pārsniedz 10°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-ngd10_cell.tif"
layername="egv_48"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-ngd10_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.49 Climate_CHELSAv2.1-ngd5_cell

filename: Climate_CHELSAv2.1-ngd5_cell.tif

layername: egv_49

English name: Number of days at which 2m air temperature > 5°C (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Dienu skaits, kurā gaisa temperatūra 2 m augstumā pārsniedz 5°C (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-ngd5_cell.tif"
layername="egv_49"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-ngd5_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.50 Climate_CHELSAv2.1-npp_cell

filename: Climate_CHELSAv2.1-npp_cell.tif

layername: egv_50

English name: Net primary productivity (g C m⁻² year⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Neto primārā produkcija (g C m⁻² year⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-npp_cell.tif"
layername="egv_50"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-npp_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.51 Climate_CHELSAv2.1-pet-penman-max_cell

filename: Climate_CHELSAv2.1-pet-penman-max_cell.tif

layername: egv_51

English name: Maximum monthly potential evapotranspiration (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālā mēneša potenciālā evapotranspirācija (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-pet-penman-max_cell.tif"
layername="egv_51"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-pet-penman-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.52 Climate_CHELSAv2.1-pet-penman-mean_cell

filename: Climate_CHELSAv2.1-pet-penman-mean_cell.tif

layername: egv_52

English name: Mean monthly potential evapotranspiration (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējā mēneša potenciālā evapotranspirācija (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-pet-penman-mean_cell.tif"
layername="egv_52"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-pet-penman-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.53 Climate_CHELSAv2.1-pet-penman-min_cell

filename: Climate_CHELSAv2.1-pet-penman-min_cell.tif

layername: egv_53

English name: Minimum monthly potential evapotranspiration (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālā mēneša vidējā potenciālā evapotranspirācija (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-pet-penman-min_cell.tif"
layername="egv_53"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-pet-penman-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.54 Climate_CHELSAv2.1-pet-penman-range_cell

filename: Climate_CHELSAv2.1-pet-penman-range_cell.tif

layername: egv_54

English name: Annual range of monthly potential evapotranspiration (kg m⁻² month⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada potenciālā evapotranspirācijas amplitūda (kg m⁻² month⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-pet-penman-range_cell.tif"
layername="egv_54"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-pet-penman-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.55 Climate_CHELSAv2.1-rsds-max_cell

filename: Climate_CHELSAv2.1-rsds-max_cell.tif

layername: egv_55

English name: Maximum monthly surface downwelling shortwave flux in air (MJ m⁻² d⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālā mēneša vidējā Zemes virsmu sasniedzošā saules radiācija (MJ m⁻² d⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-rsds-max_cell.tif"
layername="egv_55"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-rsds-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.56 Climate_CHELSAv2.1-rsds-mean_cell

filename: Climate_CHELSAv2.1-rsds-mean_cell.tif

layername: egv_56

English name: Mean monthly surface downwelling shortwave flux in air (MJ m⁻² d⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējā Zemes virsmu sasniedzošā saules radiācija (MJ m⁻² d⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-rsds-mean_cell.tif"
layername="egv_56"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-rsds-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.57 Climate_CHELSAv2.1-rsds-min_cell

filename: Climate_CHELSAv2.1-rsds-min_cell.tif

layername: egv_57

English name: Minimum monthly surface shortwave flux in air (MJ m⁻² d⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālā mēneša vidējā Zemes virsmu sasniedzošā saules radiācija (MJ m⁻² d⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-rsds-min_cell.tif"
layername="egv_57"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-rsds-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.58 Climate_CHELSAv2.1-rsds-range_cell

filename: Climate_CHELSAv2.1-rsds-range_cell.tif

layername: egv_58

English name: Annual range of monthly surface downwelling shortwave flux in air (MJ m⁻² d⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada amplitūda Zemes virsmu sasniedzošajai saules radiācijai (MJ m⁻² d⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-rsds-range_cell.tif"
layername="egv_58"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-rsds-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.59 Climate_CHELSAv2.1-scd_cell

filename: Climate_CHELSAv2.1-scd_cell.tif

layername: egv_59

English name: Number of days with snow cover (TREELIM) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Dienu ar sniega segu skaits (TREELIM) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-scd_cell.tif"
layername="egv_59"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-scd_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.60 Climate_CHELSAv2.1-sfcWind-max_cell

filename: Climate_CHELSAv2.1-sfcWind-max_cell.tif

layername: egv_60

English name: Maximum monthly near-surface wind speed (m s⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālais mēneša vidējais piezemes slāņa vēja ātrums (m s⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-sfcWind-max_cell.tif"
layername="egv_60"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-sfcWind-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.61 Climate_CHELSAv2.1-sfcWind-mean_cell

filename: Climate_CHELSAv2.1-sfcWind-mean_cell.tif

layername: egv_61

English name: Mean monthly near-surface wind speed (m s⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējais piezemes slāņa vēja ātrums (m s⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-sfcWind-mean_cell.tif"
layername="egv_61"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-sfcWind-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.62 Climate_CHELSAv2.1-sfcWind-min_cell

filename: Climate_CHELSAv2.1-sfcWind-min_cell.tif

layername: egv_62

English name: Minimum monthly near-surface wind speed (m s⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālais mēneša vidējais piezemes slāņa vēja ātrums (m s⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-sfcWind-min_cell.tif"
layername="egv_62"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-sfcWind-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.63 Climate_CHELSAv2.1-sfcWind-range_cell

filename: Climate_CHELSAv2.1-sfcWind-range_cell.tif

layername: egv_63

English name: Annual range of monthly near-surface wind speed (m s⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada amplitūda vidējam piezemes slāņa vēja ātrumam (m s⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-sfcWind-range_cell.tif"
layername="egv_63"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-sfcWind-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.64 Climate_CHELSAv2.1-swb_cell

filename: Climate_CHELSAv2.1-swb_cell.tif

layername: egv_64

English name: Site water balance (kg m⁻² year⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Ūdens bilance (kg m⁻² year⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-swb_cell.tif"
layername="egv_64"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-swb_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.65 Climate_CHELSAv2.1-swe_cell

filename: Climate_CHELSAv2.1-swe_cell.tif

layername: egv_65

English name: Snow water equivalent (kg m⁻² year⁻¹) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Ūdens ekvivalents sniegā (kg m⁻² year⁻¹) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-swe_cell.tif"
layername="egv_65"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-swe_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.66 Climate_CHELSAv2.1-vpd-max_cell

filename: Climate_CHELSAv2.1-vpd-max_cell.tif

layername: egv_66

English name: Maximum monthly vapor pressure deficit (Pa) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Maksimālais mēneša vidējais iztvaikošanas spiediena deficīts (Pa) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-vpd-max_cell.tif"
layername="egv_66"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-vpd-max_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.67 Climate_CHELSAv2.1-vpd-mean_cell

filename: Climate_CHELSAv2.1-vpd-mean_cell.tif

layername: egv_67

English name: Mean monthly vapor pressure deficit (Pa) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Vidējais iztvaikošanas spiediena deficīts (Pa) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-vpd-mean_cell.tif"
layername="egv_67"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-vpd-mean_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.68 Climate_CHELSAv2.1-vpd-min_cell

filename: Climate_CHELSAv2.1-vpd-min_cell.tif

layername: egv_68

English name: Minimum monthly vapor pressure deficit (Pa) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Minimālais mēneša vidējais iztvaikošanas spiediena deficīts (Pa) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-vpd-min_cell.tif"
layername="egv_68"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-vpd-min_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.69 Climate_CHELSAv2.1-vpd-range_cell

filename: Climate_CHELSAv2.1-vpd-range_cell.tif

layername: egv_69

English name: Annual range of monthly vapor pressure deficit (Pa) (CHELSA v2.1) within the analysis cell (1 ha)

Latvian name: Gada iztvaikošanas spiediena deficīta amplitūda (Pa) (CHELSA v2.1) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# job ----

localname="Climate_CHELSAv2.1-vpd-range_cell.tif"
layername="egv_69"
reading="./Geodata/2024/CHELSA/Climate_CHELSAv2.1-vpd-range_cell.tif"

df <- downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = reading,
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = localname,
  layer_name    = layername,
  fill_gaps     = TRUE,
  smooth        = TRUE,
  smooth_radius_km = 5,
  plot_result   = TRUE)
print(df)

6.70 HydroClim_01-max_cell

filename: HydroClim_01-max_cell.tif

layername: egv_70

English name: Maximum per subcatchment upstream mean annual air temperature (°C) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā vidējā gaisa temperatūra augštecē (°C) (HydroClim) analīzes šūnā (1 ha)

Procedure: Information - both basins and raster layers - from HydroClim data is used. First, basin CRS is transformed to epsg:3059. Then zonal statistics (per basin) with layer specific summary function - max - are calculated (exactextractr::exact_extract()) and then rasterized with egvtools::polygon2input(). Once rasterized to input data, EGV is created with egvtools::input2egv(). To prevent from gaps at the edges, inderse distance weighted (power = 2) gap filling is implemented. To save disk space, intermediate input layer is unlinked.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_01-max_cell.tif"
layername="egv_70"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.71 HydroClim_02-max_cell

filename: HydroClim_02-max_cell.tif

layername: egv_71

English name: Maximum per subcatchment upstream mean diurnal air temperature range (°C) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā diennakts gaisa temperatūras amplitūda augštecē (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_02-max_cell.tif"
layername="egv_71"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.72 HydroClim_03-max_cell

filename: HydroClim_03-max_cell.tif

layername: egv_72

English name: Maximum per subcatchment upstream isothermality (ratio of diurnal variation to annual variation in temperatures) (°C) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā izotermalitāte augštecē (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_03-max_cell.tif"
layername="egv_72"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.73 HydroClim_04-max_cell

filename: HydroClim_04-max_cell.tif

layername: egv_73

English name: Maximum per subcatchment upstream temperature seasonality (standard deviation of the monthly mean temperatures) (°C/100) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā temperatūras sezonalitāte augštecē (°C/100) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_04-max_cell.tif"
layername="egv_73"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.74 HydroClim_05-max_cell

filename: HydroClim_05-max_cell.tif

layername: egv_74

English name: Maximum per subcatchment upstream mean daily maximum air temperature (°C) of the warmest month (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces dienas vidējā gaisa temperatūra siltākajā mēnesī (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_05-max_cell.tif"
layername="egv_74"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.75 HydroClim_06-min_cell

filename: HydroClim_06-min_cell.tif

layername: egv_75

English name: Minimum per subcatchment upstream mean daily minimum air temperature (°C) of the coldest month (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina minimālā augšteces dienas vidējā gaisa temperatūra vēsākajā mēnesī (°C) (HydroClim) analīzes šūnā (1 ha)

Procedure: Information - both basins and raster layers - from HydroClim data is used. First, basin CRS is transformed to epsg:3059. Then zonal statistics (per basin) with layer specific summary function - min - are calculated (exactextractr::exact_extract()) and then rasterized with egvtools::polygon2input(). Once rasterized to input data, EGV is created with egvtools::input2egv(). To prevent from gaps at the edges, inderse distance weighted (power = 2) gap filling is implemented. To save disk space, intermediate input layer is unlinked.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_06-min_cell.tif"
layername="egv_75"
summary_function="min"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.76 HydroClim_07-max_cell

filename: HydroClim_07-max_cell.tif

layername: egv_76

English name: Maximum per subcatchment upstream annual range of air temperature (°C) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces gada gaisa temperatūru amplitūda (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_07-max_cell.tif"
layername="egv_76"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.77 HydroClim_08-max_cell

filename: HydroClim_08-max_cell.tif

layername: egv_77

English name: Maximum per subcatchment upstream mean daily mean air temperatures (°C) of the wettest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces dienas vidējā gaisa temperatūra mitrākajā ceturksnī (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_08-max_cell.tif"
layername="egv_77"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.78 HydroClim_09-min_cell

filename: HydroClim_09-min_cell.tif

layername: egv_78

English name: Minimum per subcatchment upstream mean daily mean air temperatures (°C) of the driest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces dienas vidējā gaisa temperatūra sausākajā ceturksnī (°C) (HydroClim) analīzes šūnā (1 ha)

Procedure: Information - both basins and raster layers - from HydroClim data is used. First, basin CRS is transformed to epsg:3059. Then zonal statistics (per basin) with layer specific summary function - min - are calculated (exactextractr::exact_extract()) and then rasterized with egvtools::polygon2input(). Once rasterized to input data, EGV is created with egvtools::input2egv(). To prevent from gaps at the edges, inderse distance weighted (power = 2) gap filling is implemented. To save disk space, intermediate input layer is unlinked.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_09-min_cell.tif"
layername="egv_78"
summary_function="min"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.79 HydroClim_10-max_cell

filename: HydroClim_10-max_cell.tif

layername: egv_79

English name: Maximum per subcatchment upstream mean daily mean air temperatures (°C) of the warmest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces dienas vidējā gaisa temperatūra siltākajā ceturksnī (°C) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_10-max_cell.tif"
layername="egv_79"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.80 HydroClim_11-min_cell

filename: HydroClim_11-min_cell.tif

layername: egv_80

English name: Minimum per subcatchment upstream mean daily mean air temperatures (°C) of the coldest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālā augšteces dienas vidējā gaisa temperatūra vēsākajā ceturksnī (°C) (HydroClim) analīzes šūnā (1 ha)

Procedure: Information - both basins and raster layers - from HydroClim data is used. First, basin CRS is transformed to epsg:3059. Then zonal statistics (per basin) with layer specific summary function - min - are calculated (exactextractr::exact_extract()) and then rasterized with egvtools::polygon2input(). Once rasterized to input data, EGV is created with egvtools::input2egv(). To prevent from gaps at the edges, inderse distance weighted (power = 2) gap filling is implemented. To save disk space, intermediate input layer is unlinked.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_11-min_cell.tif"
layername="egv_80"
summary_function="min"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.81 HydroClim_12-max_cell

filename: HydroClim_12-max_cell.tif

layername: egv_81

English name: Maximum per subcatchment upstream annual precipitation amount (kg m⁻² year⁻¹) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums gadā (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_12-max_cell.tif"
layername="egv_81"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.82 HydroClim_13-max_cell

filename: HydroClim_13-max_cell.tif

layername: egv_82

English name: Maximum per subcatchment upstream precipitation amount (kg m⁻² year⁻¹) of the wettest month (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums mitrākajā mēnesī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_13-max_cell.tif"
layername="egv_82"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.83 HydroClim_14-max_cell

filename: HydroClim_14-max_cell.tif

layername: egv_83

English name: Maximum per subcatchment upstream precipitation amount (kg m⁻² year⁻¹) of the driest month (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums sausākajā mēnesī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_14-max_cell.tif"
layername="egv_83"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.84 HydroClim_15-max_cell

filename: HydroClim_15-max_cell.tif

layername: egv_84

English name: Maximum per subcatchment upstream precipitation seasonality (kg m⁻²) (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzuma sezonalitāte (kg m⁻²) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_15-max_cell.tif"
layername="egv_84"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.85 HydroClim_16-max_cell

filename: HydroClim_16-max_cell.tif

layername: egv_85

English name: Maximum per subcatchment upstream mean monthly precipitation amount (kg m⁻² year⁻¹) of the wettest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums mitrākajā ceturksnī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_16-max_cell.tif"
layername="egv_85"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.86 HydroClim_17-max_cell

filename: HydroClim_17-max_cell.tif

layername: egv_86

English name: Maximum per subcatchment upstream mean monthly precipitation amount (kg m⁻² year⁻¹) of the driest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums sausākajā ceturksnī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_17-max_cell.tif"
layername="egv_86"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.87 HydroClim_18-max_cell

filename: HydroClim_18-max_cell.tif

layername: egv_87

English name: Maximum per subcatchment upstream mean monthly precipitation amount (kg m⁻² year⁻¹) of the warmest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums siltākajā ceturksnī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_18-max_cell.tif"
layername="egv_87"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.88 HydroClim_19-max_cell

filename: HydroClim_19-max_cell.tif

layername: egv_88

English name: Maximum per subcatchment upstream mean monthly precipitation amount (kg m⁻² year⁻¹) of the coldest quarter (HydroClim) within the analysis cell (1 ha)

Latvian name: Sateces apakšbaseina maksimālais augšteces nokrišņu daudzums vēsākajā ceturksnī (kg m⁻² year⁻¹) (HydroClim) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(exactextractr)) {install.packages("exactextractr"); require(exactextractr)}

# basins ----
level12=st_read("./Geodata/2024/HydroClim/hybas_lake_eu_lev01-12_v1c/hybas_lake_eu_lev12_v1c.shp")
grid_1km=sfarrow::st_read_parquet("./Templates/TemplateGrids/tikls1km_sauzeme.parquet")
grid_1km=st_transform(grid_1km,crs=3059)
level12=st_transform(level12,crs=3059)
level12=level12[grid_1km,,]

level12=st_make_valid(level12)

# job ----

localname="HydroClim_19-max_cell.tif"
layername="egv_88"
summary_function="max"
  
slanis=rast(paste0("./Geodata/2024/HydroClim/",localname))
level12$Hydro_values=exact_extract(slanis,level12,fun=summary_function)
  
polygon2input(vector_data = level12,
              template_path = "./Templates/TemplateRasters/LV10m_10km.tif",
              out_path = "./RasterGrids_10m/2024/",
              file_name = localname,
              value_field = "Hydro_values",
              fun="first",
              value_type = "continuous",
              prepare=FALSE,
              project_mode = "auto",
              check_na = FALSE,
              plot_result=FALSE,
              plot_gaps = FALSE,
              overwrite=TRUE)
  
egvrez=input2egv(input=paste0("./RasterGrids_10m/2024/",localname),
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 input_template = "./Templates/TemplateRasters/LV10m_10km.tif",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = localname,
                 layername = layername,
                 idw_weight = 2,
                 plot_gaps = FALSE,plot_final = FALSE)
egvrez
  
unlink(paste0("./RasterGrids_10m/2024/",localname))

6.89 Distance_Builtup_cell

filename: Distance_Builtup_cell.tif

layername: egv_89

English name: Distance to Built-Up features, average within the analysis cell (1 ha)

Latvian name: Attālums līdz apbūvei, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Landscape classification with class 500 reclassified as 1 and others as 0. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# Distance_Builtup_cell.tif egv_89 ----
simple_landscape=rast("./RasterGrids_10m/2024/Ainava_vienk_mask.tif")
builtup=ifel(simple_landscape==500,1,0)
plot(builtup)
distegv=distance2egv(input = builtup,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_Builtup_cell.tif",
                     layername = "egv_89")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_Builtup_cell.tif"))
rm(builtup)
rm(distegv)

6.90 Distance_ForestInside_cell

filename: Distance_ForestInside_cell.tif

layername: egv_90

English name: Distance to Forest Edge Inside Forests, average within the analysis cell (1 ha)

Latvian name: Attālums līdz meža malai tā iekšienē, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Landscape classification with values in a range from 630 to 700 reclassified as 0 and others as 1. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# Distance_ForestInside_cell.tif    egv_90 ----
simple_landscape=rast("./RasterGrids_10m/2024/Ainava_vienk_mask.tif")
trees_inside=ifel(simple_landscape>=630&simple_landscape<700,0,1)
plot(trees_inside)
distegv=distance2egv(input = trees_inside,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_ForestInside_cell.tif",
                     layername = "egv_90")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_ForestInside_cell.tif"))
rm(trees_inside)
rm(distegv)

6.91 Distance_GrasslandPermanent_cell

filename: Distance_GrasslandPermanent_cell.tif

layername: egv_91

English name: Distance to Permanent Grasslands, average within the analysis cell (1 ha)

Latvian name: Attālums līdz ilggadīgiem zālājiem, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Rural Support Service’s information on declared fields with PRODUCT_CODE=="710" classified as 1 and the rest of the country as 0. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(sfarrow)) {install.packages("sfarrow"); require(sfarrow)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(readxl)) {install.packages("readxl"); require(readxl)}
if(!require(raster)) {install.packages("raster"); require(raster)}
if(!require(fasterize)) {install.packages("fasterize"); require(fasterize)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
nulls10=rast("./Templates/TemplateRasters/nulls_LV10m_10km.tif")

rastra_pamatne=raster(template10)

# Distance_GrasslandPermanent_cell.tif  egv_91 ----
kodes=read_excel("./Geodata/2024/LAD/KulturuKodi_2024.xlsx")
lad=sfarrow::st_read_parquet("./Geodata/2024/LAD/Lauki_2024.parquet")
permgrass=lad %>% 
  filter(PRODUCT_CODE=="710") %>% 
  mutate(yes=1)
permgrass_r=fasterize(permgrass,rastra_pamatne,field="yes",fun="first")
permgrass_t=rast(permgrass_r)
permgrass_t2=cover(permgrass_t,nulls10)
plot(permgrass_t2)
distegv=distance2egv(input = permgrass_t2,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_GrasslandPermanent_cell.tif",
                     layername = "egv_91")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_GrasslandPermanent_cell.tif"))
rm(distegv)
rm(kodes)
rm(lad)
rm(permgrass)
rm(permgrass_r)
rm(permgrass_t)
rm(permgrass_t2)

6.92 Distance_Landfill_cell

filename: Distance_Landfill_cell.tif

layername: egv_92

English name: Distance to Landfills, average within the analysis cell (1 ha)

Latvian name: Attālums līdz atkritumu poligoniem, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows Waste and garbage disposal sites, landfills. 1. From the attachaed file read sheet “Poligoni”;

Create an sf object (epsg:3059);
Rasterize and cover so that cells of interest are 1 and others are 0;
create an egv with egvtools::distance2egv(). Expect warning regarding nothing to do with aggregation. It is because egvtools::distance2egv() already operate at egv-template not the input-template resolution. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(readxl)) {install.packages("readxl"); require(readxl)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")
nulls100=rast("./Templates/TemplateRasters/nulls_LV100m_10km.tif")

# Distance_Landfill_cell.tif egv_92 ----

# reading coordinates
landfills=read_excel("./Geodata/2024/GarbageWasteLandfills/Atkritumi.xlsx",sheet="Poligoni")
#sf object
landfills_sf=st_as_sf(landfills,coords=c("X","Y"),crs=3059)
# rasterize
landfills_rast=rasterize(landfills_sf,template100)
# raster to 1=Cell of interest, 0=background
landfills_bg=cover(landfills_rast,nulls100)

# create an egv
distegv=distance2egv(input = landfills_bg,
             template_egv = template100,
             values_as_one = 1,
             fill_gaps = TRUE, idw_weight = 2,
             outlocation = "RasterGrids_100m/2024/RAW/",
             outfilename = "Distance_Landfill_cell.tif",
             layername = "egv_92")
distegv

6.93 Distance_Sea_cell

filename: Distance_Sea_cell.tif

layername: egv_93

English name: Distance to Sea, average within the analysis cell (1 ha)

Latvian name: Attālums līdz jūrai, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows Latvian Exclusive Economic Zone polygon. 1. Read layer as sf object (it already is epsg:3059);

Rasterize and cover so that cells of interest are 1 and others are 0;
create an egv with egvtools::distance2egv(). {fasterize} does not write CRS with WKT from epsg-string. Therefore it is better to use project_to_template_input=TRUE and define input-template. However, the only difference is in how the CRS is stored, therefore this can ignored - distance will be calculated on the input CRS and only resulting layer will be projected to match egv-template (faster due to 10x aggregation of resolution). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(raster)) {install.packages("raster"); require(raster)}
if(!require(fasterize)) {install.packages("fasterize"); require(fasterize)}


# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
nulls10=rast("./Templates/TemplateRasters/nulls_LV10m_10km.tif")
rastrs10=raster::raster(template10)


# Distance_Sea_cell.tif egv_93 ----

# sea layer, sf
sea=st_read("./Geodata/2024/LV_EEZ/LV_EEZ.shp")

# quick rasterization
sea_r=fasterize(sea,rastrs10,field="LV_EEZ")
sea_rast=rast(sea_r)

# # raster to 1=Cell of interest, 0=background
sea_bg=cover(sea_rast,nulls10)

# create an egv
distegv=distance2egv(input = sea_bg,
                     template_egv = "./Templates/TemplateRasters/LV100m_10km.tif",
                     values_as_one = 1,
                     project_to_template_input=TRUE, # fasterize stores CRS differently
                     template_input=template10,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_Sea_cell.tif",
                     layername = "egv_93")
distegv

6.94 Distance_Trees_cell

filename: Distance_Trees_cell.tif

layername: egv_94

English name: Distance to Trees, average within the analysis cell (1 ha)

Latvian name: Attālums līdz kokiem, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Landscape classification with values in a range from 630 to 700 reclassified as 1 and others as 0. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# Distance_Trees_cell.tif   egv_94 ----
simple_landscape=rast("./RasterGrids_10m/2024/Ainava_vienk_mask.tif")
trees=ifel(simple_landscape>=630&simple_landscape<700,1,0)
plot(trees)
distegv=distance2egv(input = trees,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_Trees_cell.tif",
                     layername = "egv_94")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_Trees_cell.tif"))
rm(trees)
rm(distegv)

6.95 Distance_Waste_cell

filename: Distance_Waste_cell.tif

layername: egv_95

English name: Distance to Waste disposal sites, average within the analysis cell (1 ha)

Latvian name: Attālums līdz atkritumu šķirošanas un uzglabāšanas vietām, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows Waste and garbage disposal sites, landfills. 1. From the attachaed file read sheet “AtkritumuVietas” and clean names;

Create an sf object (epsg:3059);
Filter to non-deposit collection locations;
Rasterize and cover so that cells of interest are 1 and others are 0;
create an egv with egvtools::distance2egv(). Expect warning regarding nothing to do with aggregation. It is because egvtools::distance2egv() already operate at egv-template not the input-template resolution. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(sf)) {install.packages("sf"); require(sf)}
if(!require(tidyverse)) {install.packages("tidyverse"); require(tidyverse)}
if(!require(readxl)) {install.packages("readxl"); require(readxl)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")
nulls100=rast("./Templates/TemplateRasters/nulls_LV100m_10km.tif")


# Distance_Waste_cell.tif egv_95 ----

# reading coordinates
waste=read_excel("./Geodata/2024/GarbageWasteLandfills/Atkritumi.xlsx",sheet="AtkritumuVietas")
# cleaning names
waste2=janitor::clean_names(waste)
#sf object
waste_sf=st_as_sf(waste2,coords=c("y_koordinata_lks92_tm","x_koordinata_lks92_tm"),crs=3059)
# filtering to non-deposit
table(waste_sf$pienemsanas_vietas_tips)
waste_sf2=waste_sf %>% 
  filter(!str_detect(pienemsanas_vietas_tips,"Depozīta"))
# rasterize
waste_rast=rasterize(waste_sf2,template100)
# raster to 1=Cell of interest, 0=background
wastw_bg=cover(waste_rast,nulls100)

# create an egv
distegv=distance2egv(input = wastw_bg,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_Waste_cell.tif",
                     layername = "egv_95")
distegv

6.96 Distance_Water_cell

filename: Distance_Water_cell.tif

layername: egv_96

English name: Distance to Waterbodies, average within the analysis cell (1 ha)

Latvian name: Attālums līdz ūdenstilpēn, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Landscape classification with class 200 reclassified as 1 and others as 0. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# Distance_Water_cell.tif   egv_96 ----
simple_landscape=rast("./RasterGrids_10m/2024/Ainava_vienk_mask.tif")
water=ifel(simple_landscape==200,1,0)
plot(water)
distegv=distance2egv(input = water,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_Water_cell.tif",
                     layername = "egv_96")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_Water_cell.tif"))
rm(water)
rm(distegv)

6.97 Distance_WaterInside_cell

filename: Distance_WaterInside_cell.tif

layername: egv_97

English name: Distance to Waterbody Edge Inside Waterbody, average within the analysis cell (1 ha)

Latvian name: Attālums līdz ūdenstilpes malai tās iekšienē, vidējais analīzes šūnā (1 ha)

Procedure: Derived from Landscape classification with class 200 reclassified as 0 and others as 1. Processed with egvtools::distance2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# Distance_WaterInside_cell.tif egv_97 ----
simple_landscape=rast("./RasterGrids_10m/2024/Ainava_vienk_mask.tif")
water_outside=ifel(simple_landscape==200,0,1)
plot(water_outside)
distegv=distance2egv(input = water_outside,
                     template_egv = template100,
                     values_as_one = 1,
                     fill_gaps = TRUE, idw_weight = 2,
                     outlocation = "RasterGrids_100m/2024/RAW/",
                     outfilename = "Distance_WaterInside_cell.tif",
                     layername = "egv_97")
distegv
plot(rast("RasterGrids_100m/2024/RAW/Distance_WaterInside_cell.tif"))
rm(water_outside)
rm(distegv)

6.98 Diversity_Farmland_r500

filename: Diversity_Farmland_r500.tif

layername: egv_98

English name: Average farmland class α-diversity of 500 m grid cells within the 0.5 km landscape

Latvian name: Vidējā lauku ainavas klašu 500 m šūnu α-daudzveidība 0.5 km ainavā

Procedure: Derived from Landscape diversity, more precisely Farmland diversity. Average value of 25 ha cells diversity index values calculated with egvtools::radius_function(). To guard against missing values at the edges, inverse distance wieghted (power = 2) gap filling is allowed. File is written twice, to ensure layername.

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Farmland_500x.tif"),
  layer_prefixes = c("Diversity_Farmland"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Farmland_r500.tif   egv_98
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Farmland_r500.tif")
names(slanis)="egv_98"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Farmland_r500.tif",
            overwrite=TRUE)

6.99 Diversity_Farmland_r1250

filename: Diversity_Farmland_r1250.tif

layername: egv_99

English name: Average farmland class α-diversity of 500 m grid cells within the 1.25 km landscape

Latvian name: Vidējā lauku ainavas klašu 500 m šūnu α-daudzveidība 1.25 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Farmland_500x.tif"),
  layer_prefixes = c("Diversity_Farmland"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Farmland_r1250.tif  egv_99
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Farmland_r1250.tif")
names(slanis)="egv_99"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Farmland_r1250.tif",
            overwrite=TRUE)

6.100 Diversity_Farmland_r3000

filename: Diversity_Farmland_r3000.tif

layername: egv_100

English name: Average farmland class α-diversity of 500 m grid cells within the 3 km landscape

Latvian name: Vidējā lauku ainavas klašu 500 m šūnu α-daudzveidība 3 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Farmland_500x.tif"),
  layer_prefixes = c("Diversity_Farmland"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Farmland_r3000.tif  egv_100
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Farmland_r3000.tif")
names(slanis)="egv_100"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Farmland_r3000.tif",
            overwrite=TRUE)

6.101 Diversity_Farmland_r10000

filename: Diversity_Farmland_r10000.tif

layername: egv_101

English name: Average farmland class α-diversity of 500 m grid cells within the 10 km landscape

Latvian name: Vidējā lauku ainavas klašu 500 m šūnu α-daudzveidība 10 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Farmland_500x.tif"),
  layer_prefixes = c("Diversity_Farmland"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Farmland_r10000.tif egv_101
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Farmland_r10000.tif")
names(slanis)="egv_101"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Farmland_r10000.tif",
            overwrite=TRUE)

6.102 Diversity_Forest_r500

filename: Diversity_Forest_r500.tif

layername: egv_102

English name: Average forest class α-diversity of 500 m grid cells within the 0.5 km landscape

Latvian name: Vidējā mežu ainavas klašu 500 m šūnu α-daudzveidība 0.5 km ainavā

Procedure: Derived from Landscape diversity, more precisely Forest diversity. Average value of 25 ha cells diversity index values calculated with egvtools::radius_function(). To guard against missing values at the edges, inverse distance wieghted (power = 2) gap filling is allowed. File is written twice, to ensure layername.

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Forests_500x.tif"),
  layer_prefixes = c("Diversity_Forest"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Forest_r500.tif egv_102
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Forest_r500.tif")
names(slanis)="egv_102"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Forest_r500.tif",
            overwrite=TRUE)

6.103 Diversity_Forest_r1250

filename: Diversity_Forest_r1250.tif

layername: egv_103

English name: Average forest class α-diversity of 500 m grid cells within the 1.25 km landscape

Latvian name: Vidējā mežu ainavas klašu 500 m šūnu α-daudzveidība 1.25 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Forests_500x.tif"),
  layer_prefixes = c("Diversity_Forest"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Forest_r1250.tif    egv_103
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Forest_r1250.tif")
names(slanis)="egv_103"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Forest_r1250.tif",
            overwrite=TRUE)

6.104 Diversity_Forest_r3000

filename: Diversity_Forest_r3000.tif

layername: egv_104

English name: Average forest class α-diversity of 500 m grid cells within the 3 km landscape

Latvian name: Vidējā mežu ainavas klašu 500 m šūnu α-daudzveidība 3 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Forests_500x.tif"),
  layer_prefixes = c("Diversity_Forest"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Forest_r3000.tif    egv_104
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Forest_r3000.tif")
names(slanis)="egv_104"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Forest_r3000.tif",
            overwrite=TRUE)

6.105 Diversity_Forest_r10000

filename: Diversity_Forest_r10000.tif

layername: egv_105

English name: Average forest class α-diversity of 500 m grid cells within the 10 km landscape

Latvian name: Vidējā mežu ainavas klašu 500 m šūnu α-daudzveidība 10 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_Forests_500x.tif"),
  layer_prefixes = c("Diversity_Forest"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Forest_r10000.tif   egv_105
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Forest_r10000.tif")
names(slanis)="egv_105"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Forest_r10000.tif",
            overwrite=TRUE)

6.106 Diversity_Total_r500

filename: Diversity_Total_r500.tif

layername: egv_106

English name: Average combined landscape α-diversity of 500 m grid cells within the 0.5 km landscape

Latvian name: Vidējā visu ainavas klašu 500 m šūnu α-daudzveidība 0.5 km ainavā

Procedure: Derived from Landscape diversity, more precisely Landscape in general diversity. Average value of 25 ha cells diversity index values calculated with egvtools::radius_function(). To guard against missing values at the edges, inverse distance wieghted (power = 2) gap filling is allowed. File is written twice, to ensure layername.

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_GeneralLandscape_500x.tif"),
  layer_prefixes = c("Diversity_Total"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Total_r500.tif  egv_106
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Total_r500.tif")
names(slanis)="egv_106"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Total_r500.tif",
            overwrite=TRUE)

6.107 Diversity_Total_r1250

filename: Diversity_Total_r1250.tif

layername: egv_107

English name: Average combined landscape α-diversity of 500 m grid cells within the 1.25 km landscape

Latvian name: Vidējā visu ainavas klašu 500 m šūnu α-daudzveidība 1.25 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_GeneralLandscape_500x.tif"),
  layer_prefixes = c("Diversity_Total"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Total_r1250.tif egv_107
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Total_r1250.tif")
names(slanis)="egv_107"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Total_r1250.tif",
            overwrite=TRUE)

6.108 Diversity_Total_r3000

filename: Diversity_Total_r3000.tif

layername: egv_108

English name: Average combined landscape α-diversity of 500 m grid cells within the 3 km landscape

Latvian name: Vidējā visu ainavas klašu 500 m šūnu α-daudzveidība 3 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_GeneralLandscape_500x.tif"),
  layer_prefixes = c("Diversity_Total"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Total_r3000.tif egv_108
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Total_r3000.tif")
names(slanis)="egv_108"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Total_r3000.tif",
            overwrite=TRUE)

6.109 Diversity_Total_r10000

filename: Diversity_Total_r10000.tif

layername: egv_109

English name: Average combined landscape α-diversity of 500 m grid cells within the 10 km landscape

Latvian name: Vidējā visu ainavas klašu 500 m šūnu α-daudzveidība 10 km ainavā

Code

# Libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}
if(!require(terra)) {install.packages("terra"); require(terra)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_500m/2024/Diversity_GeneralLandscape_500x.tif"),
  layer_prefixes = c("Diversity_Total"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 12,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Diversity_Total_r10000.tif    egv_109
slanis=rast("./RasterGrids_100m/2024/RAW/Diversity_Total_r10000.tif")
names(slanis)="egv_109"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Diversity_Total_r10000.tif",
            overwrite=TRUE)

6.110 Edges_Bogs-Trees_cell

filename: Edges_Bogs-Trees_cell.tif

layername: egv_110

English name: Edge pixels of Bogs, Mires bordering with Trees within the analysis cell (1 ha)

Latvian name: Purvu malu ar kokiem garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.111 Edges_Bogs-Trees_r500

filename: Edges_Bogs-Trees_r500.tif

layername: egv_111

English name: Edge pixels of Bogs, Mires bordering with Trees within the 0.5 km landscape

Latvian name: Purvu malu ar kokiem garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.112 Edges_Bogs-Trees_r1250

filename: Edges_Bogs-Trees_r1250.tif

layername: egv_112

English name: Edge pixels of Bogs, Mires bordering with Trees within the 1.25 km landscape

Latvian name: Purvu malu ar kokiem garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.113 Edges_Bogs-Trees_r3000

filename: Edges_Bogs-Trees_r3000.tif

layername: egv_113

English name: Edge pixels of Bogs, Mires bordering with Trees within the 3 km landscape

Latvian name: Purvu malu ar kokiem garums 3 km ainavā

Procedure:

Code

# libs ----

6.114 Edges_Bogs-Trees_r10000

filename: Edges_Bogs-Trees_r10000.tif

layername: egv_114

English name: Edge pixels of Bogs, Mires bordering with Trees within the 10 km landscape

Latvian name: Purvu malu ar kokiem garums 10 km ainavā

Procedure:

Code

# libs ----

6.115 Edges_Bogs-Water_cell

filename: Edges_Bogs-Water_cell.tif

layername: egv_115

English name: Edge pixels of Bogs, Mires bordering with Water within the analysis cell (1 ha)

Latvian name: Purvu malu ar ūdeni garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.116 Edges_Bogs-Water_r500

filename: Edges_Bogs-Water_r500.tif

layername: egv_116

English name: Edge pixels of Bogs, Mires bordering with Water within the 0.5 km landscape

Latvian name: Purvu malu ar ūdeni garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.117 Edges_Bogs-Water_r1250

filename: Edges_Bogs-Water_r1250.tif

layername: egv_117

English name: Edge pixels of Bogs, Mires bordering with Water within the 1.25 km landscape

Latvian name: Purvu malu ar ūdeni garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.118 Edges_Bogs-Water_r3000

filename: Edges_Bogs-Water_r3000.tif

layername: egv_118

English name: Edge pixels of Bogs, Mires bordering with Water within the 3 km landscape

Latvian name: Purvu malu ar ūdeni garums 3 km ainavā

Procedure:

Code

# libs ----

6.119 Edges_Bogs-Water_r10000

filename: Edges_Bogs-Water_r10000.tif

layername: egv_119

English name: Edge pixels of Bogs, Mires bordering with Water within the 10 km landscape

Latvian name: Purvu malu ar ūdeni garums 10 km ainavā

Procedure:

Code

# libs ----

6.120 Edges_Farmland-Builtup_cell

filename: Edges_Farmland-Builtup_cell.tif

layername: egv_120

English name: Edge pixels of Farmland bordering with Built-Up areas within the analysis cell (1 ha)

Latvian name: Lauksaimniecības zemju malu ar apbūvi garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.121 Edges_Farmland-Builtup_r500

filename: Edges_Farmland-Builtup_r500.tif

layername: egv_121

English name: Edge pixels of Farmland bordering with Built-Up areas within the 0.5 km landscape

Latvian name: Lauksaimniecības zemju malu ar apbūvi garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.122 Edges_Farmland-Builtup_r1250

filename: Edges_Farmland-Builtup_r1250.tif

layername: egv_122

English name: Edge pixels of Farmland bordering with Built-Up areas within the 1.25 km landscape

Latvian name: Lauksaimniecības zemju malu ar apbūvi garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.123 Edges_Farmland-Builtup_r3000

filename: Edges_Farmland-Builtup_r3000.tif

layername: egv_123

English name: Edge pixels of Farmland bordering with Built-Up areas within the 3 km landscape

Latvian name: Lauksaimniecības zemju malu ar apbūvi garums 3 km ainavā

Procedure:

Code

# libs ----

6.124 Edges_Farmland-Builtup_r10000

filename: Edges_Farmland-Builtup_r10000.tif

layername: egv_124

English name: Edge pixels of Farmland bordering with Built-Up areas within the 10 km landscape

Latvian name: Lauksaimniecības zemju malu ar apbūvi garums 10 km ainavā

Procedure:

Code

# libs ----

6.125 Edges_Trees-Builtup_cell

filename: Edges_Trees-Builtup_cell.tif

layername: egv_125

English name: Edge pixels of Trees bordering with Built-Up areas within the analysis cell (1 ha)

Latvian name: Koku malu ar apbūvi garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.126 Edges_Trees-Builtup_r500

filename: Edges_Trees-Builtup_r500.tif

layername: egv_126

English name: Edge pixels of Trees bordering with Built-Up areas within the 0.5 km landscape

Latvian name: Koku malu ar apbūvi garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.127 Edges_Trees-Builtup_r1250

filename: Edges_Trees-Builtup_r1250.tif

layername: egv_127

English name: Edge pixels of Trees bordering with Built-Up areas within the 1.25 km landscape

Latvian name: Koku malu ar apbūvi garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.128 Edges_Trees-Builtup_r3000

filename: Edges_Trees-Builtup_r3000.tif

layername: egv_128

English name: Edge pixels of Trees bordering with Built-Up areas within the 3 km landscape

Latvian name: Koku malu ar apbūvi garums 3 km ainavā

Procedure:

Code

# libs ----

6.129 Edges_Trees-Builtup_r10000

filename: Edges_Trees-Builtup_r10000.tif

layername: egv_129

English name: Edge pixels of Trees bordering with Built-Up areas within the 10 km landscape

Latvian name: Koku malu ar apbūvi garums 10 km ainavā

Procedure:

Code

# libs ----

6.130 Edges_CropsFallow_cell

filename: Edges_CropsFallow_cell.tif

layername: egv_130

English name: Edge pixels of Cropland, Fallow land within the analysis cell (1 ha)

Latvian name: Aramzemju malu garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.131 Edges_CropsFallow_r500

filename: Edges_CropsFallow_r500.tif

layername: egv_131

English name: Edge pixels of Cropland, Fallow land within the 0.5 km landscape

Latvian name: Aramzemju malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.132 Edges_CropsFallow_r1250

filename: Edges_CropsFallow_r1250.tif

layername: egv_132

English name: Edge pixels of Cropland, Fallow land within the 1.25 km landscape

Latvian name: Aramzemju malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.133 Edges_CropsFallow_r3000

filename: Edges_CropsFallow_r3000.tif

layername: egv_133

English name: Edge pixels of Cropland, Fallow land within the 3 km landscape

Latvian name: Aramzemju malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.134 Edges_CropsFallow_r10000

filename: Edges_CropsFallow_r10000.tif

layername: egv_134

English name: Edge pixels of Cropland, Fallow land within the 10 km landscape

Latvian name: Aramzemju malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.135 Edges_FarmlandShrubs-Trees_cell

filename: Edges_FarmlandShrubs-Trees_cell.tif

layername: egv_135

English name: Edge pixels of Farmland, Clear-Cuts, Shrubs bordering with Trees within the analysis cell (1 ha)

Latvian name: Lauksaimniecības zemju, izcirtumu, krūmu malu ar kokiem garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.136 Edges_FarmlandShrubs-Trees_r500

filename: Edges_FarmlandShrubs-Trees_r500.tif

layername: egv_136

English name: Edge pixels of Farmland, Clear-Cuts, Shrubs bordering with Trees within the 0.5 km landscape

Latvian name: Lauksaimniecības zemju, izcirtumu, krūmu malu ar kokiem garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.137 Edges_FarmlandShrubs-Trees_r1250

filename: Edges_FarmlandShrubs-Trees_r1250.tif

layername: egv_137

English name: Edge pixels of Farmland, Clear-Cuts, Shrubs bordering with Trees within the 1.25 km landscape

Latvian name: Lauksaimniecības zemju, izcirtumu, krūmu malu ar kokiem garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.138 Edges_FarmlandShrubs-Trees_r3000

filename: Edges_FarmlandShrubs-Trees_r3000.tif

layername: egv_138

English name: Edge pixels of Farmland, Clear-Cuts, Shrubs bordering with Trees within the 3 km landscape

Latvian name: Lauksaimniecības zemju, izcirtumu, krūmu malu ar kokiem garums 3 km ainavā

Procedure:

Code

# libs ----

6.139 Edges_FarmlandShrubs-Trees_r10000

filename: Edges_FarmlandShrubs-Trees_r10000.tif

layername: egv_139

English name: Edge pixels of Farmland, Clear-Cuts, Shrubs bordering with Trees within the 10 km landscape

Latvian name: Lauksaimniecības zemju, izcirtumu, krūmu malu ar kokiem garums 10 km ainavā

Procedure:

Code

# libs ----

6.140 Edges_Grasslands_cell

filename: Edges_Grasslands_cell.tif

layername: egv_140

English name: Edge pixels of Grassland within the analysis cell (1 ha)

Latvian name: Zālāju malu garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.141 Edges_Grasslands_r500

filename: Edges_Grasslands_r500.tif

layername: egv_141

English name: Edge pixels of Grassland within the 0.5 km landscape

Latvian name: Zālāju malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.142 Edges_Grasslands_r1250

filename: Edges_Grasslands_r1250.tif

layername: egv_142

English name: Edge pixels of Grassland within the 1.25 km landscape

Latvian name: Zālāju malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.143 Edges_Grasslands_r3000

filename: Edges_Grasslands_r3000.tif

layername: egv_143

English name: Edge pixels of Grassland within the 3 km landscape

Latvian name: Zālāju malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.144 Edges_Grasslands_r10000

filename: Edges_Grasslands_r10000.tif

layername: egv_144

English name: Edge pixels of Grassland within the 10 km landscape

Latvian name: Zālāju malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.145 Edges_OldForests_cell

filename: Edges_OldForests_cell.tif

layername: egv_145

English name: Edge pixels of Forests Over Rotation Age within the analysis cell (1 ha)

Latvian name: Pieaugušo un pāraugušo mežaudžu malu garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.146 Edges_OldForests_r500

filename: Edges_OldForests_r500.tif

layername: egv_146

English name: Edge pixels of Forests Over Rotation Age within the 0.5 km landscape

Latvian name: Pieaugušo un pāraugušo mežaudžu malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.147 Edges_OldForests_r1250

filename: Edges_OldForests_r1250.tif

layername: egv_147

English name: Edge pixels of Forests Over Rotation Age within the 1.25 km landscape

Latvian name: Pieaugušo un pāraugušo mežaudžu malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.148 Edges_OldForests_r3000

filename: Edges_OldForests_r3000.tif

layername: egv_148

English name: Edge pixels of Forests Over Rotation Age within the 3 km landscape

Latvian name: Pieaugušo un pāraugušo mežaudžu malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.149 Edges_OldForests_r10000

filename: Edges_OldForests_r10000.tif

layername: egv_149

English name: Edge pixels of Forests Over Rotation Age within the 10 km landscape

Latvian name: Pieaugušo un pāraugušo mežaudžu malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.150 Edges_Roads_cell

filename: Edges_Roads_cell.tif

layername: egv_150

English name: Edge pixels of Roads within the analysis cell (1 ha)

Latvian name: Ceļu malu garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.151 Edges_Roads_r500

filename: Edges_Roads_r500.tif

layername: egv_151

English name: Edge pixels of Roads within the 0.5 km landscape

Latvian name: Ceļu malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.152 Edges_Roads_r1250

filename: Edges_Roads_r1250.tif

layername: egv_152

English name: Edge pixels of Roads within the 1.25 km landscape

Latvian name: Ceļu malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.153 Edges_Roads_r3000

filename: Edges_Roads_r3000.tif

layername: egv_153

English name: Edge pixels of Roads within the 3 km landscape

Latvian name: Ceļu malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.154 Edges_Roads_r10000

filename: Edges_Roads_r10000.tif

layername: egv_154

English name: Edge pixels of Roads within the 10 km landscape

Latvian name: Ceļu malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.155 Edges_Trees_cell

filename: Edges_Trees_cell.tif

layername: egv_155

English name: Edge pixels of Trees within the analysis cell (1 ha)

Latvian name: Koku malu garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.156 Edges_Trees_r500

filename: Edges_Trees_r500.tif

layername: egv_156

English name: Edge pixels of Trees within the 0.5 km landscape

Latvian name: Koku malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.157 Edges_Trees_r1250

filename: Edges_Trees_r1250.tif

layername: egv_157

English name: Edge pixels of Trees within the 1.25 km landscape

Latvian name: Koku malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.158 Edges_Trees_r3000

filename: Edges_Trees_r3000.tif

layername: egv_158

English name: Edge pixels of Trees within the 3 km landscape

Latvian name: Koku malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.159 Edges_Trees_r10000

filename: Edges_Trees_r10000.tif

layername: egv_159

English name: Edge pixels of Trees within the 10 km landscape

Latvian name: Koku malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.160 Edges_Water_cell

filename: Edges_Water_cell.tif

layername: egv_160

English name: Edge pixels of Water within the analysis cell (1 ha)

Latvian name: Ūdenstilpju malu garums nalīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.161 Edges_Water_r500

filename: Edges_Water_r500.tif

layername: egv_161

English name: Edge pixels of Water within the 0.5 km landscape

Latvian name: Ūdenstilpju malu garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.162 Edges_Water_r1250

filename: Edges_Water_r1250.tif

layername: egv_162

English name: Edge pixels of Water within the 1.25 km landscape

Latvian name: Ūdenstilpju malu garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.163 Edges_Water_r3000

filename: Edges_Water_r3000.tif

layername: egv_163

English name: Edge pixels of Water within the 3 km landscape

Latvian name: Ūdenstilpju malu garums 3 km ainavā

Procedure:

Code

# libs ----

6.164 Edges_Water_r10000

filename: Edges_Water_r10000.tif

layername: egv_164

English name: Edge pixels of Water within the 10 km landscape

Latvian name: Ūdenstilpju malu garums 10 km ainavā

Procedure:

Code

# libs ----

6.165 Edges_Water-Farmland_cell

filename: Edges_Water-Farmland_cell.tif

layername: egv_165

English name: Edge pixels of Water bordering with Farmland within the analysis cell (1 ha)

Latvian name: Ūdenstilpu malu ar lauksaimniecības zemēm garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.166 Edges_Water-Farmland_r500

filename: Edges_Water-Farmland_r500.tif

layername: egv_166

English name: Edge pixels of Water bordering with Farmland within the 0.5 km landscape

Latvian name: Ūdenstilpu malu ar lauksaimniecības zemēm garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.167 Edges_Water-Farmland_r1250

filename: Edges_Water-Farmland_r1250.tif

layername: egv_167

English name: Edge pixels of Water bordering with Farmland within the 1.25 km landscape

Latvian name: Ūdenstilpu malu ar lauksaimniecības zemēm garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.168 Edges_Water-Farmland_r3000

filename: Edges_Water-Farmland_r3000.tif

layername: egv_168

English name: Edge pixels of Water bordering with Farmland within the 3 km landscape

Latvian name: Ūdenstilpu malu ar lauksaimniecības zemēm garums 3 km ainavā

Procedure:

Code

# libs ----

6.169 Edges_Water-Farmland_r10000

filename: Edges_Water-Farmland_r10000.tif

layername: egv_169

English name: Edge pixels of Water bordering with Farmland within the 10 km landscape

Latvian name: Ūdenstilpu malu ar lauksaimniecības zemēm garums 10 km ainavā

Procedure:

Code

# libs ----

6.170 Edges_Water-Grassland_cell

filename: Edges_Water-Grassland_cell.tif

layername: egv_170

English name: Edge pixels of Water bordering with Grassland within the analysis cell (1 ha)

Latvian name: Ūdenstilpu malu ar zālājiem garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.171 Edges_Water-Grassland_r500

filename: Edges_Water-Grassland_r500.tif

layername: egv_171

English name: Edge pixels of Water bordering with Grassland within the 0.5 km landscape

Latvian name: Ūdenstilpu malu ar zālājiem garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.172 Edges_Water-Grassland_r1250

filename: Edges_Water-Grassland_r1250.tif

layername: egv_172

English name: Edge pixels of Water bordering with Grassland within the 1.25 km landscape

Latvian name: Ūdenstilpu malu ar zālājiem garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.173 Edges_Water-Grassland_r3000

filename: Edges_Water-Grassland_r3000.tif

layername: egv_173

English name: Edge pixels of Water bordering with Grassland within the 3 km landscape

Latvian name: Ūdenstilpu malu ar zālājiem garums 3 km ainavā

Procedure:

Code

# libs ----

6.174 Edges_Water-Grassland_r10000

filename: Edges_Water-Grassland_r10000.tif

layername: egv_174

English name: Edge pixels of Water bordering with Grassland within the 10 km landscape

Latvian name: Ūdenstilpu malu ar zālājiem garums 10 km ainavā

Procedure:

Code

# libs ----

6.175 Edges_ReedSedgeRushBeds-Water_cell

filename: Edges_ReedSedgeRushBeds-Water_cell.tif

layername: egv_175

English name: Edge pixels of Reed-, Sedge-, Rush- Beds bordering with Water within the analysis cell (1 ha)

Latvian name: Niedrāju, grīslāju, meldrāju malu ar ūdeni garums analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.176 Edges_ReedSedgeRushBeds-Water_r500

filename: Edges_ReedSedgeRushBeds-Water_r500.tif

layername: egv_176

English name: Edge pixels of Reed-, Sedge-, Rush- Beds bordering with Water within the 0.5 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju malu ar ūdeni garums 0,5 km ainavā

Procedure:

Code

# libs ----

6.177 Edges_ReedSedgeRushBeds-Water_r1250

filename: Edges_ReedSedgeRushBeds-Water_r1250.tif

layername: egv_177

English name: Edge pixels of Reed-, Sedge-, Rush- Beds bordering with Water within the 1.25 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju malu ar ūdeni garums 1,25 km ainavā

Procedure:

Code

# libs ----

6.178 Edges_ReedSedgeRushBeds-Water_r3000

filename: Edges_ReedSedgeRushBeds-Water_r3000.tif

layername: egv_178

English name: Edge pixels of Reed-, Sedge-, Rush- Beds bordering with Water within the 3 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju malu ar ūdeni garums 3 km ainavā

Procedure:

Code

# libs ----

6.179 Edges_ReedSedgeRushBeds-Water_r10000

filename: Edges_ReedSedgeRushBeds-Water_r10000.tif

layername: egv_179

English name: Edge pixels of Reed-, Sedge-, Rush- Beds bordering with Water within the 10 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju malu ar ūdeni garums 10 km ainavā

Procedure:

Code

# libs ----

6.180 FarmlandCrops_CropsAll_cell

filename: FarmlandCrops_CropsAll_cell.tif

layername: egv_180

English name: Fractional cover of Crops (all types) within the analysis cell (1 ha)

Latvian name: Aramzemju (dažādu lauksaimniecības kultūru) platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.181 FarmlandCrops_CropsAll_r500

filename: FarmlandCrops_CropsAll_r500.tif

layername: egv_181

English name: Fractional cover of Crops (all types) within the 0.5 km landscape

Latvian name: Aramzemju (dažādu lauksaimniecības kultūru) platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.182 FarmlandCrops_CropsAll_r1250

filename: FarmlandCrops_CropsAll_r1250.tif

layername: egv_182

English name: Fractional cover of Crops (all types) within the 1.25 km landscape

Latvian name: Aramzemju (dažādu lauksaimniecības kultūru) platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.183 FarmlandCrops_CropsAll_r3000

filename: FarmlandCrops_CropsAll_r3000.tif

layername: egv_183

English name: Fractional cover of Crops (all types) within the 3 km landscape

Latvian name: Aramzemju (dažādu lauksaimniecības kultūru) platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.184 FarmlandCrops_CropsAll_r10000

filename: FarmlandCrops_CropsAll_r10000.tif

layername: egv_184

English name: Fractional cover of Crops (all types) within the 10 km landscape

Latvian name: Aramzemju (dažādu lauksaimniecības kultūru) platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.185 FarmlandCrops_CropsHoed_cell

filename: FarmlandCrops_CropsHoed_cell.tif

layername: egv_185

English name: Fractional cover of Hoed Crops within the analysis cell (1 ha)

Latvian name: Vagu un rušināmkultūru platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.186 FarmlandCrops_CropsHoed_r500

filename: FarmlandCrops_CropsHoed_r500.tif

layername: egv_186

English name: Fractional cover of Hoed Crops within the 0.5 km landscape

Latvian name: Vagu un rušināmkultūru platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.187 FarmlandCrops_CropsHoed_r1250

filename: FarmlandCrops_CropsHoed_r1250.tif

layername: egv_187

English name: Fractional cover of Hoed Crops within the 1.25 km landscape

Latvian name: Vagu un rušināmkultūru platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.188 FarmlandCrops_CropsHoed_r3000

filename: FarmlandCrops_CropsHoed_r3000.tif

layername: egv_188

English name: Fractional cover of Hoed Crops within the 3 km landscape

Latvian name: Vagu un rušināmkultūru platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.189 FarmlandCrops_CropsHoed_r10000

filename: FarmlandCrops_CropsHoed_r10000.tif

layername: egv_189

English name: Fractional cover of Hoed Crops within the 10 km landscape

Latvian name: Vagu un rušināmkultūru platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.190 FarmlandCrops_CropsOther_cell

filename: FarmlandCrops_CropsOther_cell.tif

layername: egv_190

English name: Fractional cover of Other Crops within the analysis cell (1 ha)

Latvian name: Citu lauksaimniecības kultūraugu aramzemēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.191 FarmlandCrops_CropsOther_r500

filename: FarmlandCrops_CropsOther_r500.tif

layername: egv_191

English name: Fractional cover of Other Crops within the 0.5 km landscape

Latvian name: Citu lauksaimniecības kultūraugu aramzemēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.192 FarmlandCrops_CropsOther_r1250

filename: FarmlandCrops_CropsOther_r1250.tif

layername: egv_192

English name: Fractional cover of Other Crops within the 1.25 km landscape

Latvian name: Citu lauksaimniecības kultūraugu aramzemēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.193 FarmlandCrops_CropsOther_r3000

filename: FarmlandCrops_CropsOther_r3000.tif

layername: egv_193

English name: Fractional cover of Other Crops within the 3 km landscape

Latvian name: Citu lauksaimniecības kultūraugu aramzemēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.194 FarmlandCrops_CropsOther_r10000

filename: FarmlandCrops_CropsOther_r10000.tif

layername: egv_194

English name: Fractional cover of Other Crops within the 10 km landscape

Latvian name: Citu lauksaimniecības kultūraugu aramzemēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.195 FarmlandCrops_CropsSpring_cell

filename: FarmlandCrops_CropsSpring_cell.tif

layername: egv_195

English name: Fractional cover of Spring Sown Crops within the analysis cell (1 ha)

Latvian name: Vasarāju aramzemēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.196 FarmlandCrops_CropsSpring_r500

filename: FarmlandCrops_CropsSpring_r500.tif

layername: egv_196

English name: Fractional cover of Spring Sown Crops within the 0.5 km landscape

Latvian name: Vasarāju aramzemēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.197 FarmlandCrops_CropsSpring_r1250

filename: FarmlandCrops_CropsSpring_r1250.tif

layername: egv_197

English name: Fractional cover of Spring Sown Crops within the 1.25 km landscape

Latvian name: Vasarāju aramzemēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.198 FarmlandCrops_CropsSpring_r3000

filename: FarmlandCrops_CropsSpring_r3000.tif

layername: egv_198

English name: Fractional cover of Spring Sown Crops within the 3 km landscape

Latvian name: Vasarāju aramzemēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.199 FarmlandCrops_CropsSpring_r10000

filename: FarmlandCrops_CropsSpring_r10000.tif

layername: egv_199

English name: Fractional cover of Spring Sown Crops within the 10 km landscape

Latvian name: Vasarāju aramzemēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.200 FarmlandCrops_CropsWinter_cell

filename: FarmlandCrops_CropsWinter_cell.tif

layername: egv_200

English name: Fractional cover of Winter Crops within the analysis cell (1 ha)

Latvian name: Ziemāju aramzemēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.201 FarmlandCrops_CropsWinter_r500

filename: FarmlandCrops_CropsWinter_r500.tif

layername: egv_201

English name: Fractional cover of Winter Crops within the 0.5 km landscape

Latvian name: Ziemāju aramzemēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.202 FarmlandCrops_CropsWinter_r1250

filename: FarmlandCrops_CropsWinter_r1250.tif

layername: egv_202

English name: Fractional cover of Winter Crops within the 1.25 km landscape

Latvian name: Ziemāju aramzemēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.203 FarmlandCrops_CropsWinter_r3000

filename: FarmlandCrops_CropsWinter_r3000.tif

layername: egv_203

English name: Fractional cover of Winter Crops within the 3 km landscape

Latvian name: Ziemāju aramzemēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.204 FarmlandCrops_CropsWinter_r10000

filename: FarmlandCrops_CropsWinter_r10000.tif

layername: egv_204

English name: Fractional cover of Winter Crops within the 10 km landscape

Latvian name: Ziemāju aramzemēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.205 FarmlandCrops_RapeseedsSpring_cell

filename: FarmlandCrops_RapeseedsSpring_cell.tif

layername: egv_205

English name: Fractional cover of Spring Sown Rapeseed, Turnip, Corn within the analysis cell (1 ha)

Latvian name: Vasaras rapša, ripša, kukurūzas platība analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.206 FarmlandCrops_RapeseedsSpring_r500

filename: FarmlandCrops_RapeseedsSpring_r500.tif

layername: egv_206

English name: Fractional cover of Spring Sown Rapeseed, Turnip, Corn within the 0.5 km landscape

Latvian name: Vasaras rapša, ripša, kukurūzas platība 0,5 km ainavā

Procedure:

Code

# libs ----

6.207 FarmlandCrops_RapeseedsSpring_r1250

filename: FarmlandCrops_RapeseedsSpring_r1250.tif

layername: egv_207

English name: Fractional cover of Spring Sown Rapeseed, Turnip, Corn within the 1.25 km landscape

Latvian name: Vasaras rapša, ripša, kukurūzas platība 1,25 km ainavā

Procedure:

Code

# libs ----

6.208 FarmlandCrops_RapeseedsSpring_r3000

filename: FarmlandCrops_RapeseedsSpring_r3000.tif

layername: egv_208

English name: Fractional cover of Spring Sown Rapeseed, Turnip, Corn within the 3 km landscape

Latvian name: Vasaras rapša, ripša, kukurūzas platība 3 km ainavā

Procedure:

Code

# libs ----

6.209 FarmlandCrops_RapeseedsSpring_r10000

filename: FarmlandCrops_RapeseedsSpring_r10000.tif

layername: egv_209

English name: Fractional cover of Spring Sown Rapeseed, Turnip, Corn within the 10 km landscape

Latvian name: Vasaras rapša, ripša, kukurūzas platība 10 km ainavā

Procedure:

Code

# libs ----

6.210 FarmlandCrops_RapeseedsWinter_cell

filename: FarmlandCrops_RapeseedsWinter_cell.tif

layername: egv_210

English name: Fractional cover of Winter Rapeseed, Turnip within the analysis cell (1 ha)

Latvian name: Ziemas rapša, ripša platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.211 FarmlandCrops_RapeseedsWinter_r500

filename: FarmlandCrops_RapeseedsWinter_r500.tif

layername: egv_211

English name: Fractional cover of Winter Rapeseed, Turnip within the 0.5 km landscape

Latvian name: Ziemas rapša, ripša platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.212 FarmlandCrops_RapeseedsWinter_r1250

filename: FarmlandCrops_RapeseedsWinter_r1250.tif

layername: egv_212

English name: Fractional cover of Winter Rapeseed, Turnip within the 1.25 km landscape

Latvian name: Ziemas rapša, ripša platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.213 FarmlandCrops_RapeseedsWinter_r3000

filename: FarmlandCrops_RapeseedsWinter_r3000.tif

layername: egv_213

English name: Fractional cover of Winter Rapeseed, Turnip within the 3 km landscape

Latvian name: Ziemas rapša, ripša platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.214 FarmlandCrops_RapeseedsWinter_r10000

filename: FarmlandCrops_RapeseedsWinter_r10000.tif

layername: egv_214

English name: Fractional cover of Winter Rapeseed, Turnip within the 10 km landscape

Latvian name: Ziemas rapša, ripša platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.215 FarmlandGrassland_GrasslandsAbandoned_cell

filename: FarmlandGrassland_GrasslandsAbandoned_cell.tif

layername: egv_215

English name: Fractional cover of Abandoned Grassland within the analysis cell (1 ha)

Latvian name: Neapsaimniekotu zālāju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.216 FarmlandGrassland_GrasslandsAbandoned_r500

filename: FarmlandGrassland_GrasslandsAbandoned_r500.tif

layername: egv_216

English name: Fractional cover of Abandoned Grassland within the 0.5 km landscape

Latvian name: Neapsaimniekotu zālāju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.217 FarmlandGrassland_GrasslandsAbandoned_r1250

filename: FarmlandGrassland_GrasslandsAbandoned_r1250.tif

layername: egv_217

English name: Fractional cover of Abandoned Grassland within the 1.25 km landscape

Latvian name: Neapsaimniekotu zālāju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.218 FarmlandGrassland_GrasslandsAbandoned_r3000

filename: FarmlandGrassland_GrasslandsAbandoned_r3000.tif

layername: egv_218

English name: Fractional cover of Abandoned Grassland within the 3 km landscape

Latvian name: Neapsaimniekotu zālāju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.219 FarmlandGrassland_GrasslandsAbandoned_r10000

filename: FarmlandGrassland_GrasslandsAbandoned_r10000.tif

layername: egv_219

English name: Fractional cover of Abandoned Grassland within the 10 km landscape

Latvian name: Neapsaimniekotu zālāju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.220 FarmlandGrassland_GrasslandsAll_cell

filename: FarmlandGrassland_GrasslandsAll_cell.tif

layername: egv_220

English name: Fractional cover of any Grassland within the analysis cell (1 ha)

Latvian name: Zālāju (visu veidu) platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.221 FarmlandGrassland_GrasslandsAll_r500

filename: FarmlandGrassland_GrasslandsAll_r500.tif

layername: egv_221

English name: Fractional cover of any Grassland within the 0.5 km landscape

Latvian name: Zālāju (visu veidu) platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.222 FarmlandGrassland_GrasslandsAll_r1250

filename: FarmlandGrassland_GrasslandsAll_r1250.tif

layername: egv_222

English name: Fractional cover of any Grassland within the 1.25 km landscape

Latvian name: Zālāju (visu veidu) platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.223 FarmlandGrassland_GrasslandsAll_r3000

filename: FarmlandGrassland_GrasslandsAll_r3000.tif

layername: egv_223

English name: Fractional cover of any Grassland within the 3 km landscape

Latvian name: Zālāju (visu veidu) platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.224 FarmlandGrassland_GrasslandsAll_r10000

filename: FarmlandGrassland_GrasslandsAll_r10000.tif

layername: egv_224

English name: Fractional cover of any Grassland within the 10 km landscape

Latvian name: Zālāju (visu veidu) platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.225 FarmlandGrassland_GrasslandsPermanent_cell

filename: FarmlandGrassland_GrasslandsPermanent_cell.tif

layername: egv_225

English name: Fractional cover of Permanent Grassland within the analysis cell (1 ha)

Latvian name: Ilggadīgu zālāju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.226 FarmlandGrassland_GrasslandsPermanent_r500

filename: FarmlandGrassland_GrasslandsPermanent_r500.tif

layername: egv_226

English name: Fractional cover of Permanent Grassland within the 0.5 km landscape

Latvian name: Ilggadīgu zālāju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.227 FarmlandGrassland_GrasslandsPermanent_r1250

filename: FarmlandGrassland_GrasslandsPermanent_r1250.tif

layername: egv_227

English name: Fractional cover of Permanent Grassland within the 1.25 km landscape

Latvian name: Ilggadīgu zālāju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.228 FarmlandGrassland_GrasslandsPermanent_r3000

filename: FarmlandGrassland_GrasslandsPermanent_r3000.tif

layername: egv_228

English name: Fractional cover of Permanent Grassland within the 3 km landscape

Latvian name: Ilggadīgu zālāju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.229 FarmlandGrassland_GrasslandsPermanent_r10000

filename: FarmlandGrassland_GrasslandsPermanent_r10000.tif

layername: egv_229

English name: Fractional cover of Permanent Grassland within the 10 km landscape

Latvian name: Ilggadīgu zālāju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.230 FarmlandGrassland_GrasslandsTemporary_cell

filename: FarmlandGrassland_GrasslandsTemporary_cell.tif

layername: egv_230

English name: Fractional cover of Temporary Grassland within the analysis cell (1 ha)

Latvian name: Zālāju-aramzemē platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.231 FarmlandGrassland_GrasslandsTemporary_r500

filename: FarmlandGrassland_GrasslandsTemporary_r500.tif

layername: egv_231

English name: Fractional cover of Temporary Grassland within the 0.5 km landscape

Latvian name: Zālāju-aramzemē platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.232 FarmlandGrassland_GrasslandsTemporary_r1250

filename: FarmlandGrassland_GrasslandsTemporary_r1250.tif

layername: egv_232

English name: Fractional cover of Temporary Grassland within the 1.25 km landscape

Latvian name: Zālāju-aramzemē platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.233 FarmlandGrassland_GrasslandsTemporary_r3000

filename: FarmlandGrassland_GrasslandsTemporary_r3000.tif

layername: egv_233

English name: Fractional cover of Temporary Grassland within the 3 km landscape

Latvian name: Zālāju-aramzemē platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.234 FarmlandGrassland_GrasslandsTemporary_r10000

filename: FarmlandGrassland_GrasslandsTemporary_r10000.tif

layername: egv_234

English name: Fractional cover of Temporary Grassland within the 10 km landscape

Latvian name: Zālāju-aramzemē platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.235 FarmlandParcels_FieldsActive_cell

filename: FarmlandParcels_FieldsActive_cell.tif

layername: egv_235

English name: Fractional cover of Agricultural Land Parcels within the analysis cell (1 ha)

Latvian name: Lauku bloku platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.236 FarmlandParcels_FieldsActive_r500

filename: FarmlandParcels_FieldsActive_r500.tif

layername: egv_236

English name: Fractional cover of Agricultural Land Parcels within the 0.5 km landscape

Latvian name: Lauku bloku platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.237 FarmlandParcels_FieldsActive_r1250

filename: FarmlandParcels_FieldsActive_r1250.tif

layername: egv_237

English name: Fractional cover of Agricultural Land Parcels within the 1.25 km landscape

Latvian name: Lauku bloku platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.238 FarmlandParcels_FieldsActive_r3000

filename: FarmlandParcels_FieldsActive_r3000.tif

layername: egv_238

English name: Fractional cover of Agricultural Land Parcels within the 3 km landscape

Latvian name: Lauku bloku platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.239 FarmlandParcels_FieldsActive_r10000

filename: FarmlandParcels_FieldsActive_r10000.tif

layername: egv_239

English name: Fractional cover of Agricultural Land Parcels within the 10 km landscape

Latvian name: Lauku bloku platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.240 FarmlandPloughed_CropsFallow_cell

filename: FarmlandPloughed_CropsFallow_cell.tif

layername: egv_240

English name: Fractional cover of Crop-, Fallow- Land within the analysis cell (1 ha)

Latvian name: Aramzemju, papuvju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.241 FarmlandPloughed_CropsFallow_r500

filename: FarmlandPloughed_CropsFallow_r500.tif

layername: egv_241

English name: Fractional cover of Crop-, Fallow- Land within the 0.5 km landscape

Latvian name: Aramzemju, papuvju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.242 FarmlandPloughed_CropsFallow_r1250

filename: FarmlandPloughed_CropsFallow_r1250.tif

layername: egv_242

English name: Fractional cover of Crop-, Fallow- Land within the 1.25 km landscape

Latvian name: Aramzemju, papuvju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.243 FarmlandPloughed_CropsFallow_r3000

filename: FarmlandPloughed_CropsFallow_r3000.tif

layername: egv_243

English name: Fractional cover of Crop-, Fallow- Land within the 3 km landscape

Latvian name: Aramzemju, papuvju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.244 FarmlandPloughed_CropsFallow_r10000

filename: FarmlandPloughed_CropsFallow_r10000.tif

layername: egv_244

English name: Fractional cover of Crop-, Fallow- Land within the 10 km landscape

Latvian name: Aramzemju, papuvju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.245 FarmlandPloughed_CropsFallowTempGrass_cell

filename: FarmlandPloughed_CropsFallowTempGrass_cell.tif

layername: egv_245

English name: Fractional cover of Crop-, Fallow-, Temporary Grass- Lands within the analysis cell (1 ha)

Latvian name: Aramzemju, papuvju, zālāju-aramzemē platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.246 FarmlandPloughed_CropsFallowTempGrass_r500

filename: FarmlandPloughed_CropsFallowTempGrass_r500.tif

layername: egv_246

English name: Fractional cover of Crop-, Fallow-, Temporary Grass- Lands within the 0.5 km landscape

Latvian name: Aramzemju, papuvju, zālāju-aramzemē platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.247 FarmlandPloughed_CropsFallowTempGrass_r1250

filename: FarmlandPloughed_CropsFallowTempGrass_r1250.tif

layername: egv_247

English name: Fractional cover of Crop-, Fallow-, Temporary Grass- Lands within the 1.25 km landscape

Latvian name: Aramzemju, papuvju, zālāju-aramzemē platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.248 FarmlandPloughed_CropsFallowTempGrass_r3000

filename: FarmlandPloughed_CropsFallowTempGrass_r3000.tif

layername: egv_248

English name: Fractional cover of Crop-, Fallow-, Temporary Grass- Lands within the 3 km landscape

Latvian name: Aramzemju, papuvju, zālāju-aramzemē platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.249 FarmlandPloughed_CropsFallowTempGrass_r10000

filename: FarmlandPloughed_CropsFallowTempGrass_r10000.tif

layername: egv_249

English name: Fractional cover of Crop-, Fallow-, Temporary Grass- Lands within the 10 km landscape

Latvian name: Aramzemju, papuvju, zālāju-aramzemē platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.250 FarmlandPloughed_Fallow_cell

filename: FarmlandPloughed_Fallow_cell.tif

layername: egv_250

English name: Fractional cover of Fallow Land within the analysis cell (1 ha)

Latvian name: Papuvju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.251 FarmlandPloughed_Fallow_r500

filename: FarmlandPloughed_Fallow_r500.tif

layername: egv_251

English name: Fractional cover of Fallow Land within the 0.5 km landscape

Latvian name: Papuvju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.252 FarmlandPloughed_Fallow_r1250

filename: FarmlandPloughed_Fallow_r1250.tif

layername: egv_252

English name: Fractional cover of Fallow Land within the 1.25 km landscape

Latvian name: Papuvju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.253 FarmlandPloughed_Fallow_r3000

filename: FarmlandPloughed_Fallow_r3000.tif

layername: egv_253

English name: Fractional cover of Fallow Land within the 3 km landscape

Latvian name: Papuvju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.254 FarmlandPloughed_Fallow_r10000

filename: FarmlandPloughed_Fallow_r10000.tif

layername: egv_254

English name: Fractional cover of Fallow Land within the 10 km landscape

Latvian name: Papuvju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.255 FarmlandSubsidies_BiologicalSubsidies_cell

filename: FarmlandSubsidies_BiologicalSubsidies_cell.tif

layername: egv_255

English name: Fractional cover of Farmland receiving Subsidies for Biological Agriculture within the analysis cell (1 ha)

Latvian name: Bioloģiskās lauksaimniecības atbalstam pieteikto lauksaimniecības platību īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.256 FarmlandSubsidies_BiologicalSubsidies_r500

filename: FarmlandSubsidies_BiologicalSubsidies_r500.tif

layername: egv_256

English name: Fractional cover of Farmland receiving Subsidies for Biological Agriculture within the 0.5 km landscape

Latvian name: Bioloģiskās lauksaimniecības atbalstam pieteikto lauksaimniecības platību īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.257 FarmlandSubsidies_BiologicalSubsidies_r1250

filename: FarmlandSubsidies_BiologicalSubsidies_r1250.tif

layername: egv_257

English name: Fractional cover of Farmland receiving Subsidies for Biological Agriculture within the 1.25 km landscape

Latvian name: Bioloģiskās lauksaimniecības atbalstam pieteikto lauksaimniecības platību īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.258 FarmlandSubsidies_BiologicalSubsidies_r3000

filename: FarmlandSubsidies_BiologicalSubsidies_r3000.tif

layername: egv_258

English name: Fractional cover of Farmland receiving Subsidies for Biological Agriculture within the 3 km landscape

Latvian name: Bioloģiskās lauksaimniecības atbalstam pieteikto lauksaimniecības platību īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.259 FarmlandSubsidies_BiologicalSubsidies_r10000

filename: FarmlandSubsidies_BiologicalSubsidies_r10000.tif

layername: egv_259

English name: Fractional cover of Farmland receiving Subsidies for Biological Agriculture within the 10 km landscape

Latvian name: Bioloģiskās lauksaimniecības atbalstam pieteikto lauksaimniecības platību īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.260 FarmlandTrees_PermanentCrops_cell

filename: FarmlandTrees_PermanentCrops_cell.tif

layername: egv_260

English name: Fractional cover of Permanent Crops within the analysis cell (1 ha)

Latvian name: Augļudārzu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.261 FarmlandTrees_PermanentCrops_r500

filename: FarmlandTrees_PermanentCrops_r500.tif

layername: egv_261

English name: Fractional cover of Permanent Crops within the 0.5 km landscape

Latvian name: Augļudārzu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.262 FarmlandTrees_PermanentCrops_r1250

filename: FarmlandTrees_PermanentCrops_r1250.tif

layername: egv_262

English name: Fractional cover of Permanent Crops within the 1.25 km landscape

Latvian name: Augļudārzu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.263 FarmlandTrees_PermanentCrops_r3000

filename: FarmlandTrees_PermanentCrops_r3000.tif

layername: egv_263

English name: Fractional cover of Permanent Crops within the 3 km landscape

Latvian name: Augļudārzu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.264 FarmlandTrees_PermanentCrops_r10000

filename: FarmlandTrees_PermanentCrops_r10000.tif

layername: egv_264

English name: Fractional cover of Permanent Crops within the 10 km landscape

Latvian name: Augļudārzu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.265 FarmlandTrees_ShortRotationCoppice_cell

filename: FarmlandTrees_ShortRotationCoppice_cell.tif

layername: egv_265

English name: Fractional cover of Short-rotation Coppice and Other Woody Energy Crops within the analysis cell (1 ha)

Latvian name: Īscirtmeta atvasāju un enerģijai audzētu kokaugu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.266 FarmlandTrees_ShortRotationCoppice_r500

filename: FarmlandTrees_ShortRotationCoppice_r500.tif

layername: egv_266

English name: Fractional cover of Short-rotation Coppice and Other Woody Energy Crops within the 0.5 km landscape

Latvian name: Īscirtmeta atvasāju un enerģijai audzētu kokaugu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.267 FarmlandTrees_ShortRotationCoppice_r1250

filename: FarmlandTrees_ShortRotationCoppice_r1250.tif

layername: egv_267

English name: Fractional cover of Short-rotation Coppice and Other Woody Energy Crops within the 1.25 km landscape

Latvian name: Īscirtmeta atvasāju un enerģijai audzētu kokaugu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.268 FarmlandTrees_ShortRotationCoppice_r3000

filename: FarmlandTrees_ShortRotationCoppice_r3000.tif

layername: egv_268

English name: Fractional cover of Short-rotation Coppice and Other Woody Energy Crops within the 3 km landscape

Latvian name: Īscirtmeta atvasāju un enerģijai audzētu kokaugu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.269 FarmlandTrees_ShortRotationCoppice_r10000

filename: FarmlandTrees_ShortRotationCoppice_r10000.tif

layername: egv_269

English name: Fractional cover of Short-rotation Coppice and Other Woody Energy Crops within the 10 km landscape

Latvian name: Īscirtmeta atvasāju un enerģijai audzētu kokaugu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.270 ForestsAge_ClearcutsLowStands_cell

filename: ForestsAge_ClearcutsLowStands_cell.tif

layername: egv_270

English name: Fractional cover of Clearcuts and Stands lower than 5 m within the analysis cell (1 ha)

Latvian name: Izcirtumu un mežaudžu līdz 5 m augstumam platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.271 ForestsAge_ClearcutsLowStands_r500

filename: ForestsAge_ClearcutsLowStands_r500.tif

layername: egv_271

English name: Fractional cover of Clearcuts and Stands lower than 5 m within the 0.5 km landscape

Latvian name: Izcirtumu un mežaudžu līdz 5 m augstumam platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.272 ForestsAge_ClearcutsLowStands_r1250

filename: ForestsAge_ClearcutsLowStands_r1250.tif

layername: egv_272

English name: Fractional cover of Clearcuts and Stands lower than 5 m within the 1.25 km landscape

Latvian name: Izcirtumu un mežaudžu līdz 5 m augstumam platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.273 ForestsAge_ClearcutsLowStands_r3000

filename: ForestsAge_ClearcutsLowStands_r3000.tif

layername: egv_273

English name: Fractional cover of Clearcuts and Stands lower than 5 m within the 3 km landscape

Latvian name: Izcirtumu un mežaudžu līdz 5 m augstumam platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.274 ForestsAge_ClearcutsLowStands_r10000

filename: ForestsAge_ClearcutsLowStands_r10000.tif

layername: egv_274

English name: Fractional cover of Clearcuts and Stands lower than 5 m within the 10 km landscape

Latvian name: Izcirtumu un mežaudžu līdz 5 m augstumam platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.275 ForestsAge_Middle_cell

filename: ForestsAge_Middle_cell.tif

layername: egv_275

English name: Fractional cover of Middle-Aged Forests within the analysis cell (1 ha)

Latvian name: Vidēja vecuma un briestaudžu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.276 ForestsAge_Middle_r500

filename: ForestsAge_Middle_r500.tif

layername: egv_276

English name: Fractional cover of Middle-Aged Forests within the 0.5 km landscape

Latvian name: Vidēja vecuma un briestaudžu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.277 ForestsAge_Middle_r1250

filename: ForestsAge_Middle_r1250.tif

layername: egv_277

English name: Fractional cover of Middle-Aged Forests within the 1.25 km landscape

Latvian name: Vidēja vecuma un briestaudžu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.278 ForestsAge_Middle_r3000

filename: ForestsAge_Middle_r3000.tif

layername: egv_278

English name: Fractional cover of Middle-Aged Forests within the 3 km landscape

Latvian name: Vidēja vecuma un briestaudžu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.279 ForestsAge_Middle_r10000

filename: ForestsAge_Middle_r10000.tif

layername: egv_279

English name: Fractional cover of Middle-Aged Forests within the 10 km landscape

Latvian name: Vidēja vecuma un briestaudžu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.280 ForestsAge_Old_cell

filename: ForestsAge_Old_cell.tif

layername: egv_280

English name: Fractional cover of Old (over rotation age) Forests within the analysis cell (1 ha)

Latvian name: Vecu (kopš cirtmeta) mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.281 ForestsAge_Old_r500

filename: ForestsAge_Old_r500.tif

layername: egv_281

English name: Fractional cover of Old (over rotation age) Forests within the 0.5 km landscape

Latvian name: Vecu (kopš cirtmeta)mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.282 ForestsAge_Old_r1250

filename: ForestsAge_Old_r1250.tif

layername: egv_282

English name: Fractional cover of Old (over rotation age) Forests within the 1.25 km landscape

Latvian name: Vecu (kopš cirtmeta) mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.283 ForestsAge_Old_r3000

filename: ForestsAge_Old_r3000.tif

layername: egv_283

English name: Fractional cover of Old (over rotation age) Forests within the 3 km landscape

Latvian name: Vecu (kopš cirtmeta) mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.284 ForestsAge_Old_r10000

filename: ForestsAge_Old_r10000.tif

layername: egv_284

English name: Fractional cover of Old (over rotation age) Forests within the 10 km landscape

Latvian name: Vecu (kopš cirtmeta) mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.285 ForestsAge_YoungTallStandsShrubs_cell

filename: ForestsAge_YoungTallStandsShrubs_cell.tif

layername: egv_285

English name: Fractional cover of Shrubs, Young Stands (at least 5 m tall) within the analysis cell (1 ha)

Latvian name: Krūmāju un jaunaudžu (no 5 m augstuma) platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.286 ForestsAge_YoungTallStandsShrubs_r500

filename: ForestsAge_YoungTallStandsShrubs_r500.tif

layername: egv_286

English name: Fractional cover of Shrubs, Young Stands (at least 5 m tall) within the 0.5 km landscape

Latvian name: Krūmāju un jaunaudžu (no 5 m augstuma) platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.287 ForestsAge_YoungTallStandsShrubs_r1250

filename: ForestsAge_YoungTallStandsShrubs_r1250.tif

layername: egv_287

English name: Fractional cover of Shrubs, Young Stands (at least 5 m tall) within the 1.25 km landscape

Latvian name: Krūmāju un jaunaudžu (no 5 m augstuma) platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.288 ForestsAge_YoungTallStandsShrubs_r3000

filename: ForestsAge_YoungTallStandsShrubs_r3000.tif

layername: egv_288

English name: Fractional cover of Shrubs, Young Stands (at least 5 m tall) within the 3 km landscape

Latvian name: Krūmāju un jaunaudžu (no 5 m augstuma) platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.289 ForestsAge_YoungTallStandsShrubs_r10000

filename: ForestsAge_YoungTallStandsShrubs_r10000.tif

layername: egv_289

English name: Fractional cover of Shrubs, Young Stands (at least 5 m tall) within the 10 km landscape

Latvian name: Krūmāju un jaunaudžu (no 5 m augstuma) platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.290 ForestsQuant_AgeProp-average_cell

filename: ForestsQuant_AgeProp-average_cell.tif

layername: egv_290

English name: Average stand age relative to rotation age within the analysis cell (1 ha)

Latvian name: Mežaudzes vecuma attiecība pret cirtmetu, vidējais analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.291 ForestsQuant_DominantDiameter-max_cell

filename: ForestsQuant_DominantDiameter-max_cell.tif

layername: egv_291

English name: Dominant tree trunk diameter, maximum within the analysis cell (1 ha)

Latvian name: Koku stumbra diametrs, valdaudzes maksimālais analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.292 ForestsQuant_LargestDiameter-max_cell

filename: ForestsQuant_LargestDiameter-max_cell.tif

layername: egv_292

English name: Largest tree trunk diameter within the analysis cell (1 ha)

Latvian name: Lielākais koka stumbra diametrs analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.293 ForestsQuant_TimeSinceDisturbance-average_cell

filename: ForestsQuant_TimeSinceDisturbance-average_cell.tif

layername: egv_293

English name: Time since last disturbance affecting tree growing within the analysis cell (1 ha)

Latvian name: Laiks kopš pēdējā ar koku augšanu saistītā traucējuma analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.294 ForestsQuant_VolumeAspen-sum_cell

filename: ForestsQuant_VolumeAspen-sum_cell.tif

layername: egv_294

English name: Timber volume of Aspens, Poplars within the analysis cell (1 ha)

Latvian name: Apšu, papeļu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.295 ForestsQuant_VolumeBirch-sum_cell

filename: ForestsQuant_VolumeBirch-sum_cell.tif

layername: egv_295

English name: Timber volume of Birches within the analysis cell (1 ha)

Latvian name: Bērzu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.296 ForestsQuant_VolumeBlackAlder-sum_cell

filename: ForestsQuant_VolumeBlackAlder-sum_cell.tif

layername: egv_296

English name: Timber volume of Black Alder within the analysis cell (1 ha)

Latvian name: Melnalkšņu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.297 ForestsQuant_VolumeBorealDeciduousOther-sum_cell

filename: ForestsQuant_VolumeBorealDeciduousOther-sum_cell.tif

layername: egv_297

English name: Timber volume of Other Boreal Deciduous trees within the analysis cell (1 ha)

Latvian name: Citu šaurlapju krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.298 ForestsQuant_VolumeBorealDeciduousTotal-sum_cell

filename: ForestsQuant_VolumeBorealDeciduousTotal-sum_cell.tif

layername: egv_298

English name: Timber volume of Boreal Deciduous trees within the analysis cell (1 ha)

Latvian name: Šaurlapju krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.299 ForestsQuant_VolumeConiferous-sum_cell

filename: ForestsQuant_VolumeConiferous-sum_cell.tif

layername: egv_299

English name: Timber volume of Coniferous trees within the analysis cell (1 ha)

Latvian name: Skujkoku krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.300 ForestsQuant_VolumeOak-sum_cell

filename: ForestsQuant_VolumeOak-sum_cell.tif

layername: egv_300

English name: Timber volume of Oaks within the analysis cell (1 ha)

Latvian name: Ozolu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.301 ForestsQuant_VolumeOakMaple-sum_cell

filename: ForestsQuant_VolumeOakMaple-sum_cell.tif

layername: egv_301

English name: Timber volume of Oaks, Maples within the analysis cell (1 ha)

Latvian name: Ozolu, kļavu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.302 ForestsQuant_VolumePine-sum_cell

filename: ForestsQuant_VolumePine-sum_cell.tif

layername: egv_302

English name: Timber volume of Pines within the analysis cell (1 ha)

Latvian name: Priežu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.303 ForestsQuant_VolumeSpruce-sum_cell

filename: ForestsQuant_VolumeSpruce-sum_cell.tif

layername: egv_303

English name: Timber volume of Spruces within the analysis cell (1 ha)

Latvian name: Egļu krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.304 ForestsQuant_VolumeTemperateDeciduousTotal-sum_cell

filename: ForestsQuant_VolumeTemperateDeciduousTotal-sum_cell.tif

layername: egv_304

English name: Timber volume of Temperate Deciduous trees within the analysis cell (1 ha)

Latvian name: Platlapju krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.305 ForestsQuant_VolumeTemperateWithoutOak-sum_cell

filename: ForestsQuant_VolumeTemperateWithoutOak-sum_cell.tif

layername: egv_305

English name: Timber volume of Temperate Deciduous trees (without oaks) within the analysis cell (1 ha)

Latvian name: Paltlapju (bez ozoliem) krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.306 ForestsQuant_VolumeTemperateWithoutOakMaple-sum_cell

filename: ForestsQuant_VolumeTemperateWithoutOakMaple-sum_cell.tif

layername: egv_306

English name: Timber volume of Temperate Deciduous trees (without oaks, maples) within the analysis cell (1 ha)

Latvian name: Platlapju (bez ozoliem, kļavām) krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.307 ForestsQuant_VolumeTotal-sum_cell

filename: ForestsQuant_VolumeTotal-sum_cell.tif

layername: egv_307

English name: Timber volume within the analysis cell (1 ha)

Latvian name: Kopējā krāja analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.308 ForestsSoil_EutrophicDrained_cell

filename: ForestsSoil_EutrophicDrained_cell.tif

layername: egv_308

English name: Fractional cover of Drained Eutrophic Forests within the analysis cell (1 ha)

Latvian name: Susinātu eitrofu mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.309 ForestsSoil_EutrophicDrained_r500

filename: ForestsSoil_EutrophicDrained_r500.tif

layername: egv_309

English name: Fractional cover of Drained Eutrophic Forests within the 0.5 km landscape

Latvian name: Susinātu eitrofu mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.310 ForestsSoil_EutrophicDrained_r1250

filename: ForestsSoil_EutrophicDrained_r1250.tif

layername: egv_310

English name: Fractional cover of Drained Eutrophic Forests within the 1.25 km landscape

Latvian name: Susinātu eitrofu mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.311 ForestsSoil_EutrophicDrained_r3000

filename: ForestsSoil_EutrophicDrained_r3000.tif

layername: egv_311

English name: Fractional cover of Drained Eutrophic Forests within the 3 km landscape

Latvian name: Susinātu eitrofu mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.312 ForestsSoil_EutrophicDrained_r10000

filename: ForestsSoil_EutrophicDrained_r10000.tif

layername: egv_312

English name: Fractional cover of Drained Eutrophic Forests within the 10 km landscape

Latvian name: Susinātu eitrofu mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.313 ForestsSoil_EutrophicMineral_cell

filename: ForestsSoil_EutrophicMineral_cell.tif

layername: egv_313

English name: Fractional cover of Eutrophic Forests on undrained Mineral Soils within the analysis cell (1 ha)

Latvian name: Eitrofu mežu nesusinātās minerālaugsnēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.314 ForestsSoil_EutrophicMineral_r500

filename: ForestsSoil_EutrophicMineral_r500.tif

layername: egv_314

English name: Fractional cover of Eutrophic Forests on undrained Mineral Soils within the 0.5 km landscape

Latvian name: Eitrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.315 ForestsSoil_EutrophicMineral_r1250

filename: ForestsSoil_EutrophicMineral_r1250.tif

layername: egv_315

English name: Fractional cover of Eutrophic Forests on undrained Mineral Soils within the 1.25 km landscape

Latvian name: Eitrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.316 ForestsSoil_EutrophicMineral_r3000

filename: ForestsSoil_EutrophicMineral_r3000.tif

layername: egv_316

English name: Fractional cover of Eutrophic Forests on undrained Mineral Soils within the 3 km landscape

Latvian name: Eitrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.317 ForestsSoil_EutrophicMineral_r10000

filename: ForestsSoil_EutrophicMineral_r10000.tif

layername: egv_317

English name: Fractional cover of Eutrophic Forests on undrained Mineral Soils within the 10 km landscape

Latvian name: Eitrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.318 ForestsSoil_EutrophicOrganic_cell

filename: ForestsSoil_EutrophicOrganic_cell.tif

layername: egv_318

English name: Fractional cover of Eutrophic Forests on undrained Organic Soils within the analysis cell (1 ha)

Latvian name: Eitrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.319 ForestsSoil_EutrophicOrganic_r500

filename: ForestsSoil_EutrophicOrganic_r500.tif

layername: egv_319

English name: Fractional cover of Eutrophic Forests on undrained Organic Soils within the 0.5 km landscape

Latvian name: Eitrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.320 ForestsSoil_EutrophicOrganic_r1250

filename: ForestsSoil_EutrophicOrganic_r1250.tif

layername: egv_320

English name: Fractional cover of Eutrophic Forests on undrained Organic Soils within the 1.25 km landscape

Latvian name: Eitrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.321 ForestsSoil_EutrophicOrganic_r3000

filename: ForestsSoil_EutrophicOrganic_r3000.tif

layername: egv_321

English name: Fractional cover of Eutrophic Forests on undrained Organic Soils within the 3 km landscape

Latvian name: Eitrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.322 ForestsSoil_EutrophicOrganic_r10000

filename: ForestsSoil_EutrophicOrganic_r10000.tif

layername: egv_322

English name: Fractional cover of Eutrophic Forests on undrained Organic Soils within the 10 km landscape

Latvian name: Eitrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.323 ForestsSoil_MesotrophicMineral_cell

filename: ForestsSoil_MesotrophicMineral_cell.tif

layername: egv_323

English name: Fractional cover of Mesotrophic Forests on undrained Mineral Soils within the analysis cell (1 ha)

Latvian name: Mezotrofu mežu minerālaugsnēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.324 ForestsSoil_MesotrophicMineral_r500

filename: ForestsSoil_MesotrophicMineral_r500.tif

layername: egv_324

English name: Fractional cover of Mesotrophic Forests on undrained Mineral Soils within the 0.5 km landscape

Latvian name: Mezotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.325 ForestsSoil_MesotrophicMineral_r1250

filename: ForestsSoil_MesotrophicMineral_r1250.tif

layername: egv_325

English name: Fractional cover of Mesotrophic Forests on undrained Mineral Soils within the 1.25 km landscape

Latvian name: Mezotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.326 ForestsSoil_MesotrophicMineral_r3000

filename: ForestsSoil_MesotrophicMineral_r3000.tif

layername: egv_326

English name: Fractional cover of Mesotrophic Forests on undrained Mineral Soils within the 3 km landscape

Latvian name: Mezotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.327 ForestsSoil_MesotrophicMineral_r10000

filename: ForestsSoil_MesotrophicMineral_r10000.tif

layername: egv_327

English name: Fractional cover of Mesotrophic Forests on undrained Mineral Soils within the 10 km landscape

Latvian name: Mezotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.328 ForestsSoil_OligotrophicDrained_cell

filename: ForestsSoil_OligotrophicDrained_cell.tif

layername: egv_328

English name: Fractional cover of Drained Oligotrophic Forests within the analysis cell (1 ha)

Latvian name: Susinātu oligotrofu mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.329 ForestsSoil_OligotrophicDrained_r500

filename: ForestsSoil_OligotrophicDrained_r500.tif

layername: egv_329

English name: Fractional cover of Drained Oligotrophic Forests within the 0.5 km landscape

Latvian name: Susinātu oligotrofu mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.330 ForestsSoil_OligotrophicDrained_r1250

filename: ForestsSoil_OligotrophicDrained_r1250.tif

layername: egv_330

English name: Fractional cover of Drained Oligotrophic Forests within the 1.25 km landscape

Latvian name: Susinātu oligotrofu mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.331 ForestsSoil_OligotrophicDrained_r3000

filename: ForestsSoil_OligotrophicDrained_r3000.tif

layername: egv_331

English name: Fractional cover of Drained Oligotrophic Forests within the 3 km landscape

Latvian name: Susinātu oligotrofu mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.332 ForestsSoil_OligotrophicDrained_r10000

filename: ForestsSoil_OligotrophicDrained_r10000.tif

layername: egv_332

English name: Fractional cover of Drained Oligotrophic Forests within the 10 km landscape

Latvian name: Susinātu oligotrofu mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.333 ForestsSoil_OligotrophicMineral_cell

filename: ForestsSoil_OligotrophicMineral_cell.tif

layername: egv_333

English name: Fractional cover of Oligotrophic Forests on undrained Mineral Soils within the analysis cell (1 ha)

Latvian name: Oligotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.334 ForestsSoil_OligotrophicMineral_r500

filename: ForestsSoil_OligotrophicMineral_r500.tif

layername: egv_334

English name: Fractional cover of Oligotrophic Forests on undrained Mineral Soils within the 0.5 km landscape

Latvian name: Oligotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.335 ForestsSoil_OligotrophicMineral_r1250

filename: ForestsSoil_OligotrophicMineral_r1250.tif

layername: egv_335

English name: Fractional cover of Oligotrophic Forests on undrained Mineral Soils within the 1.25 km landscape

Latvian name: Oligotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.336 ForestsSoil_OligotrophicMineral_r3000

filename: ForestsSoil_OligotrophicMineral_r3000.tif

layername: egv_336

English name: Fractional cover of Oligotrophic Forests on undrained Mineral Soils within the 3 km landscape

Latvian name: Oligotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.337 ForestsSoil_OligotrophicMineral_r10000

filename: ForestsSoil_OligotrophicMineral_r10000.tif

layername: egv_337

English name: Fractional cover of Oligotrophic Forests on undrained Mineral Soils within the 10 km landscape

Latvian name: Oligotrofu mežu nesusinātās minerālaugsnēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.338 ForestsSoil_OligotrophicOrganic_cell

filename: ForestsSoil_OligotrophicOrganic_cell.tif

layername: egv_338

English name: Fractional cover of Oligotrophic Forests on undrained Organic Soils within the analysis cell (1 ha)

Latvian name: Oligotrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.339 ForestsSoil_OligotrophicOrganic_r500

filename: ForestsSoil_OligotrophicOrganic_r500.tif

layername: egv_339

English name: Fractional cover of Oligotrophic Forests on undrained Organic Soils within the 0.5 km landscape

Latvian name: Oligotrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.340 ForestsSoil_OligotrophicOrganic_r1250

filename: ForestsSoil_OligotrophicOrganic_r1250.tif

layername: egv_340

English name: Fractional cover of Oligotrophic Forests on undrained Organic Soils within the 1.25 km landscape

Latvian name: Oligotrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.341 ForestsSoil_OligotrophicOrganic_r3000

filename: ForestsSoil_OligotrophicOrganic_r3000.tif

layername: egv_341

English name: Fractional cover of Oligotrophic Forests on undrained Organic Soils within the 3 km landscape

Latvian name: Oligotrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.342 ForestsSoil_OligotrophicOrganic_r10000

filename: ForestsSoil_OligotrophicOrganic_r10000.tif

layername: egv_342

English name: Fractional cover of Oligotrophic Forests on undrained Organic Soils within the 10 km landscape

Latvian name: Oligotrofu mežu nesusinātās organiskajās augsnēs platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.343 ForestsTreesAge_BorealDeciduousOld_cell

filename: ForestsTreesAge_BorealDeciduousOld_cell.tif

layername: egv_343

English name: Fractional cover of Old (over rotation age) Boreal Deciduous Forests within the analysis cell (1 ha)

Latvian name: Vecu (kopš cirtmeta) šaurlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.344 ForestsTreesAge_BorealDeciduousOld_r500

filename: ForestsTreesAge_BorealDeciduousOld_r500.tif

layername: egv_344

English name: Fractional cover of Old (over rotation age) Boreal Deciduous Forests within the 0.5 km landscape

Latvian name: Vecu (kopš cirtmeta) šaurlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.345 ForestsTreesAge_BorealDeciduousOld_r1250

filename: ForestsTreesAge_BorealDeciduousOld_r1250.tif

layername: egv_345

English name: Fractional cover of Old (over rotation age) Boreal Deciduous Forests within the 1.25 km landscape

Latvian name: Vecu (kopš cirtmeta) šaurlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.346 ForestsTreesAge_BorealDeciduousOld_r3000

filename: ForestsTreesAge_BorealDeciduousOld_r3000.tif

layername: egv_346

English name: Fractional cover of Old (over rotation age) Boreal Deciduous Forests within the 3 km landscape

Latvian name: Vecu (kopš cirtmeta) šaurlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.347 ForestsTreesAge_BorealDeciduousOld_r10000

filename: ForestsTreesAge_BorealDeciduousOld_r10000.tif

layername: egv_347

English name: Fractional cover of Old (over rotation age) Boreal Deciduous Forests within the 10 km landscape

Latvian name: Vecu (kopš cirtmeta) šaurlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.348 ForestsTreesAge_BorealDeciduousYoung_cell

filename: ForestsTreesAge_BorealDeciduousYoung_cell.tif

layername: egv_348

English name: Fractional cover of Young (pre-rotation age) Boreal Deciduous Forests within the analysis cell (1 ha)

Latvian name: Jaunu (pirms cirtmeta) šaurlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.349 ForestsTreesAge_BorealDeciduousYoung_r500

filename: ForestsTreesAge_BorealDeciduousYoung_r500.tif

layername: egv_349

English name: Fractional cover of Young (pre-rotation age) Boreal Deciduous Forests within the 0.5 km landscape

Latvian name: Jaunu (pirms cirtmeta) šaurlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.350 ForestsTreesAge_BorealDeciduousYoung_r1250

filename: ForestsTreesAge_BorealDeciduousYoung_r1250.tif

layername: egv_350

English name: Fractional cover of Young (pre-rotation age) Boreal Deciduous Forests within the 1.25 km landscape

Latvian name: Jaunu (pirms cirtmeta) šaurlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.351 ForestsTreesAge_BorealDeciduousYoung_r3000

filename: ForestsTreesAge_BorealDeciduousYoung_r3000.tif

layername: egv_351

English name: Fractional cover of Young (pre-rotation age) Boreal Deciduous Forests within the 3 km landscape

Latvian name: Jaunu (pirms cirtmeta) šaurlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.352 ForestsTreesAge_BorealDeciduousYoung_r10000

filename: ForestsTreesAge_BorealDeciduousYoung_r10000.tif

layername: egv_352

English name: Fractional cover of Young (pre-rotation age) Boreal Deciduous Forests within the 10 km landscape

Latvian name: Jaunu (pirms cirtmeta) šaurlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.353 ForestsTreesAge_ConiferousOld_cell

filename: ForestsTreesAge_ConiferousOld_cell.tif

layername: egv_353

English name: Fractional cover of Old (over rotation age) Coniferous Forests within the analysis cell (1 ha)

Latvian name: Vecu (kopš cirtmeta) skujkoku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.354 ForestsTreesAge_ConiferousOld_r500

filename: ForestsTreesAge_ConiferousOld_r500.tif

layername: egv_354

English name: Fractional cover of Old (over rotation age) Coniferous Forests within the 0.5 km landscape

Latvian name: Vecu (kopš cirtmeta) skujkoku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.355 ForestsTreesAge_ConiferousOld_r1250

filename: ForestsTreesAge_ConiferousOld_r1250.tif

layername: egv_355

English name: Fractional cover of Old (over rotation age) Coniferous Forests within the 1.25 km landscape

Latvian name: Vecu (kopš cirtmeta) skujkoku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.356 ForestsTreesAge_ConiferousOld_r3000

filename: ForestsTreesAge_ConiferousOld_r3000.tif

layername: egv_356

English name: Fractional cover of Old (over rotation age) Coniferous Forests within the 3 km landscape

Latvian name: Vecu (kopš cirtmeta) skujkoku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.357 ForestsTreesAge_ConiferousOld_r10000

filename: ForestsTreesAge_ConiferousOld_r10000.tif

layername: egv_357

English name: Fractional cover of Old (over rotation age) Coniferous Forests within the 10 km landscape

Latvian name: Vecu (kopš cirtmeta) skujkoku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.358 ForestsTreesAge_ConiferousYoung_cell

filename: ForestsTreesAge_ConiferousYoung_cell.tif

layername: egv_358

English name: Fractional cover of Young (pre-rotation age) Coniferous Forests within the analysis cell (1 ha)

Latvian name: Jaunu (pirms cirtmeta) skujkoku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.359 ForestsTreesAge_ConiferousYoung_r500

filename: ForestsTreesAge_ConiferousYoung_r500.tif

layername: egv_359

English name: Fractional cover of Young (pre-rotation age) Coniferous Forests within the 0.5 km landscape

Latvian name: Jaunu (pirms cirtmeta) skujkoku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.360 ForestsTreesAge_ConiferousYoung_r1250

filename: ForestsTreesAge_ConiferousYoung_r1250.tif

layername: egv_360

English name: Fractional cover of Young (pre-rotation age) Coniferous Forests within the 1.25 km landscape

Latvian name: Jaunu (pirms cirtmeta) skujkoku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.361 ForestsTreesAge_ConiferousYoung_r3000

filename: ForestsTreesAge_ConiferousYoung_r3000.tif

layername: egv_361

English name: Fractional cover of Young (pre-rotation age) Coniferous Forests within the 3 km landscape

Latvian name: Jaunu (pirms cirtmeta) skujkoku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.362 ForestsTreesAge_ConiferousYoung_r10000

filename: ForestsTreesAge_ConiferousYoung_r10000.tif

layername: egv_362

English name: Fractional cover of Young (pre-rotation age) Coniferous Forests within the 10 km landscape

Latvian name: Jaunu (pirms cirtmeta) skujkoku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.363 ForestsTreesAge_MixedOld_cell

filename: ForestsTreesAge_MixedOld_cell.tif

layername: egv_363

English name: Fractional cover of Old (over rotation age) Mixed Forests within the analysis cell (1 ha)

Latvian name: Vecu (kopš cirtmeta) jauktu koku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.364 ForestsTreesAge_MixedOld_r500

filename: ForestsTreesAge_MixedOld_r500.tif

layername: egv_364

English name: Fractional cover of Old (over rotation age) Mixed Forests within the 0.5 km landscape

Latvian name: Vecu (kopš cirtmeta) jauktu koku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.365 ForestsTreesAge_MixedOld_r1250

filename: ForestsTreesAge_MixedOld_r1250.tif

layername: egv_365

English name: Fractional cover of Old (over rotation age) Mixed Forests within the 1.25 km landscape

Latvian name: Vecu (kopš cirtmeta) jauktu koku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.366 ForestsTreesAge_MixedOld_r3000

filename: ForestsTreesAge_MixedOld_r3000.tif

layername: egv_366

English name: Fractional cover of Old (over rotation age) Mixed Forests within the 3 km landscape

Latvian name: Vecu (kopš cirtmeta) jauktu koku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.367 ForestsTreesAge_MixedOld_r10000

filename: ForestsTreesAge_MixedOld_r10000.tif

layername: egv_367

English name: Fractional cover of Old (over rotation age) Mixed Forests within the 10 km landscape

Latvian name: Vecu (kopš cirtmeta) jauktu koku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.368 ForestsTreesAge_MixedYoung_cell

filename: ForestsTreesAge_MixedYoung_cell.tif

layername: egv_368

English name: Fractional cover of Young (pre-rotation age) Mixed Forests within the analysis cell (1 ha)

Latvian name: Jaunu (pirms cirtmeta) jauktu koku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.369 ForestsTreesAge_MixedYoung_r500

filename: ForestsTreesAge_MixedYoung_r500.tif

layername: egv_369

English name: Fractional cover of Young (pre-rotation age) Mixed Forests within the 0.5 km landscape

Latvian name: Jaunu (pirms cirtmeta) jauktu koku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.370 ForestsTreesAge_MixedYoung_r1250

filename: ForestsTreesAge_MixedYoung_r1250.tif

layername: egv_370

English name: Fractional cover of Young (pre-rotation age) Mixed Forests within the 1.25 km landscape

Latvian name: Jaunu (pirms cirtmeta) jauktu koku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.371 ForestsTreesAge_MixedYoung_r3000

filename: ForestsTreesAge_MixedYoung_r3000.tif

layername: egv_371

English name: Fractional cover of Young (pre-rotation age) Mixed Forests within the 3 km landscape

Latvian name: Jaunu (pirms cirtmeta) jauktu koku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.372 ForestsTreesAge_MixedYoung_r10000

filename: ForestsTreesAge_MixedYoung_r10000.tif

layername: egv_372

English name: Fractional cover of Young (pre-rotation age) Mixed Forests within the 10 km landscape

Latvian name: Jaunu (pirms cirtmeta) jauktu koku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.373 ForestsTreesAge_TemperateDeciduousOld_cell

filename: ForestsTreesAge_TemperateDeciduousOld_cell.tif

layername: egv_373

English name: Fractional cover of Old (over rotation age) Temperate Deciduous Forests within the analysis cell (1 ha)

Latvian name: Vecu (kopš cirtmeta) platlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.374 ForestsTreesAge_TemperateDeciduousOld_r500

filename: ForestsTreesAge_TemperateDeciduousOld_r500.tif

layername: egv_374

English name: Fractional cover of Old (over rotation age) Temperate Deciduous Forests within the 0.5 km landscape

Latvian name: Vecu (kopš cirtmeta) platlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.375 ForestsTreesAge_TemperateDeciduousOld_r1250

filename: ForestsTreesAge_TemperateDeciduousOld_r1250.tif

layername: egv_375

English name: Fractional cover of Old (over rotation age) Temperate Deciduous Forests within the 1.25 km landscape

Latvian name: Vecu (kopš cirtmeta) platlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.376 ForestsTreesAge_TemperateDeciduousOld_r3000

filename: ForestsTreesAge_TemperateDeciduousOld_r3000.tif

layername: egv_376

English name: Fractional cover of Old (over rotation age) Temperate Deciduous Forests within the 3 km landscape

Latvian name: Vecu (kopš cirtmeta) platlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.377 ForestsTreesAge_TemperateDeciduousOld_r10000

filename: ForestsTreesAge_TemperateDeciduousOld_r10000.tif

layername: egv_377

English name: Fractional cover of Old (over rotation age) Temperate Deciduous Forests within the 10 km landscape

Latvian name: Vecu (kopš cirtmeta) platlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.378 ForestsTreesAge_TemperateDeciduousYoung_cell

filename: ForestsTreesAge_TemperateDeciduousYoung_cell.tif

layername: egv_378

English name: Fractional cover of Young (pre-rotation age) Temperate Deciduous Forests within the analysis cell (1 ha)

Latvian name: Jaunu (pirms cirtmeta) platlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.379 ForestsTreesAge_TemperateDeciduousYoung_r500

filename: ForestsTreesAge_TemperateDeciduousYoung_r500.tif

layername: egv_379

English name: Fractional cover of Young (pre-rotation age) Temperate Deciduous Forests within the 0.5 km landscape

Latvian name: Jaunu (pirms cirtmeta) platlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.380 ForestsTreesAge_TemperateDeciduousYoung_r1250

filename: ForestsTreesAge_TemperateDeciduousYoung_r1250.tif

layername: egv_380

English name: Fractional cover of Young (pre-rotation age) Temperate Deciduous Forests within the 1.25 km landscape

Latvian name: Jaunu (pirms cirtmeta) platlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.381 ForestsTreesAge_TemperateDeciduousYoung_r3000

filename: ForestsTreesAge_TemperateDeciduousYoung_r3000.tif

layername: egv_381

English name: Fractional cover of Young (pre-rotation age) Temperate Deciduous Forests within the 3 km landscape

Latvian name: Jaunu (pirms cirtmeta) platlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.382 ForestsTreesAge_TemperateDeciduousYoung_r10000

filename: ForestsTreesAge_TemperateDeciduousYoung_r10000.tif

layername: egv_382

English name: Fractional cover of Young (pre-rotation age) Temperate Deciduous Forests within the 10 km landscape

Latvian name: Jaunu (pirms cirtmeta) platlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.383 ForestsTrees_BorealDeciduous_cell

filename: ForestsTrees_BorealDeciduous_cell.tif

layername: egv_383

English name: Fractional cover of Boeral Deciduous Forests within the analysis cell (1 ha)

Latvian name: Šaurlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.384 ForestsTrees_BorealDeciduous_r500

filename: ForestsTrees_BorealDeciduous_r500.tif

layername: egv_384

English name: Fractional cover of Boreal Deciduous Forests within the 0.5 km landscape

Latvian name: Šaurlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.385 ForestsTrees_BorealDeciduous_r1250

filename: ForestsTrees_BorealDeciduous_r1250.tif

layername: egv_385

English name: Fractional cover of Boreal Deciduous Forests within the 1.25 km landscape

Latvian name: Šaurlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.386 ForestsTrees_BorealDeciduous_r3000

filename: ForestsTrees_BorealDeciduous_r3000.tif

layername: egv_386

English name: Fractional cover of Boreal Deciduous Forests within the 3 km landscape

Latvian name: Šaurlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.387 ForestsTrees_BorealDeciduous_r10000

filename: ForestsTrees_BorealDeciduous_r10000.tif

layername: egv_387

English name: Fractional cover of Boreal Deciduous Forests within the 10 km landscape

Latvian name: Šaurlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.388 ForestsTrees_Coniferous_cell

filename: ForestsTrees_Coniferous_cell.tif

layername: egv_388

English name: Fractional cover of Coniferous Forests within the analysis cell (1 ha)

Latvian name: Skujkoku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.389 ForestsTrees_Coniferous_r500

filename: ForestsTrees_Coniferous_r500.tif

layername: egv_389

English name: Fractional cover of Coniferous Forests within the 0.5 km landscape

Latvian name: Skujkoku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.390 ForestsTrees_Coniferous_r1250

filename: ForestsTrees_Coniferous_r1250.tif

layername: egv_390

English name: Fractional cover of Coniferous Forests within the 1.25 km landscape

Latvian name: Skujkoku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.391 ForestsTrees_Coniferous_r3000

filename: ForestsTrees_Coniferous_r3000.tif

layername: egv_391

English name: Fractional cover of Coniferous Forests within the 3 km landscape

Latvian name: Skujkoku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.392 ForestsTrees_Coniferous_r10000

filename: ForestsTrees_Coniferous_r10000.tif

layername: egv_392

English name: Fractional cover of Coniferous Forests within the 10 km landscape

Latvian name: Skujkoku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.393 ForestsTrees_Mixed_cell

filename: ForestsTrees_Mixed_cell.tif

layername: egv_393

English name: Fractional cover of Mixed Forests within the analysis cell (1 ha)

Latvian name: Jauktu koku mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.394 ForestsTrees_Mixed_r500

filename: ForestsTrees_Mixed_r500.tif

layername: egv_394

English name: Fractional cover of Mixed Forests within the 0.5 km landscape

Latvian name: Jauktu koku mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.395 ForestsTrees_Mixed_r1250

filename: ForestsTrees_Mixed_r1250.tif

layername: egv_395

English name: Fractional cover of Mixed Forests within the 1.25 km landscape

Latvian name: Jauktu koku mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.396 ForestsTrees_Mixed_r3000

filename: ForestsTrees_Mixed_r3000.tif

layername: egv_396

English name: Fractional cover of Mixed Forests within the 3 km landscape

Latvian name: Jauktu koku mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.397 ForestsTrees_Mixed_r10000

filename: ForestsTrees_Mixed_r10000.tif

layername: egv_397

English name: Fractional cover of Mixed Forests within the 10 km landscape

Latvian name: Jauktu koku mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.398 ForestsTrees_TemperateDeciduous_cell

filename: ForestsTrees_TemperateDeciduous_cell.tif

layername: egv_398

English name: Fractional cover of Temperate Deciduous Forests within the analysis cell (1 ha)

Latvian name: Platlapju mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.399 ForestsTrees_TemperateDeciduous_r500

filename: ForestsTrees_TemperateDeciduous_r500.tif

layername: egv_399

English name: Fractional cover of Temperate Deciduous Forests within the 0.5 km landscape

Latvian name: Platlapju mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.400 ForestsTrees_TemperateDeciduous_r1250

filename: ForestsTrees_TemperateDeciduous_r1250.tif

layername: egv_400

English name: Fractional cover of Temperate Deciduous Forests within the 1.25 km landscape

Latvian name: Platlapju mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.401 ForestsTrees_TemperateDeciduous_r3000

filename: ForestsTrees_TemperateDeciduous_r3000.tif

layername: egv_401

English name: Fractional cover of Temperate Deciduous Forests within the 3 km landscape

Latvian name: Platlapju mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.402 ForestsTrees_TemperateDeciduous_r10000

filename: ForestsTrees_TemperateDeciduous_r10000.tif

layername: egv_402

English name: Fractional cover of Temperate Deciduous Forests within the 10 km landscape

Latvian name: Platlapju mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.403 General_AllotmentGardens_cell

filename: General_AllotmentGardens_cell.tif

layername: egv_403

English name: Fractional cover of Allotment gardens within the analysis cell (1 ha)

Latvian name: Vasarnīcu kompleksu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.404 General_AllotmentGardens_r500

filename: General_AllotmentGardens_r500.tif

layername: egv_404

English name: Fractional cover of Allotment gardens within the 0.5 km landscape

Latvian name: Vasarnīcu kompleksu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.405 General_AllotmentGardens_r1250

filename: General_AllotmentGardens_r1250.tif

layername: egv_405

English name: Fractional cover of Allotment gardens within the 1.25 km landscape

Latvian name: Vasarnīcu kompleksu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.406 General_AllotmentGardens_r3000

filename: General_AllotmentGardens_r3000.tif

layername: egv_406

English name: Fractional cover of Allotment gardens within the 3 km landscape

Latvian name: Vasarnīcu kompleksu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.407 General_AllotmentGardens_r10000

filename: General_AllotmentGardens_r10000.tif

layername: egv_407

English name: Fractional cover of Allotment gardens within the 10 km landscape

Latvian name: Vasarnīcu kompleksu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.408 General_BareSoilQuarry_cell

filename: General_BareSoilQuarry_cell.tif

layername: egv_408

English name: Fractional cover of areas with Bare Soil, Quarries within the analysis cell (1 ha)

Latvian name: Atklātas augsnes un karjeru platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.409 General_BareSoilQuarry_r500

filename: General_BareSoilQuarry_r500.tif

layername: egv_409

English name: Fractional cover of areas with Bare Soil, Quarries within the 0.5 km landscape

Latvian name: Atklātas augsnes un karjeru platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.410 General_BareSoilQuarry_r1250

filename: General_BareSoilQuarry_r1250.tif

layername: egv_410

English name: Fractional cover of areas with Bare Soil, Quarries within the 1.25 km landscape

Latvian name: Atklātas augsnes un karjeru platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.411 General_BareSoilQuarry_r3000

filename: General_BareSoilQuarry_r3000.tif

layername: egv_411

English name: Fractional cover of areas with Bare Soil, Quarries within the 3 km landscape

Latvian name: Atklātas augsnes un karjeru platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.412 General_BareSoilQuarry_r10000

filename: General_BareSoilQuarry_r10000.tif

layername: egv_412

English name: Fractional cover of areas with Bare Soil, Quarries within the 10 km landscape

Latvian name: Atklātas augsnes un karjeru platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.413 General_Builtup_cell

filename: General_Builtup_cell.tif

layername: egv_413

English name: Fractional cover of Built-Up areas within the analysis cell (1 ha)

Latvian name: Apbūves platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.414 General_Builtup_r500

filename: General_Builtup_r500.tif

layername: egv_414

English name: Fractional cover of Built-Up areas within the 0.5 km landscape

Latvian name: Apbūves platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.415 General_Builtup_r1250

filename: General_Builtup_r1250.tif

layername: egv_415

English name: Fractional cover of Built-Up areas within the 1.25 km landscape

Latvian name: Apbūves platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.416 General_Builtup_r3000

filename: General_Builtup_r3000.tif

layername: egv_416

English name: Fractional cover of Built-Up areas within the 3 km landscape

Latvian name: Apbūves platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.417 General_Builtup_r10000

filename: General_Builtup_r10000.tif

layername: egv_417

English name: Fractional cover of Built-Up areas within the 10 km landscape

Latvian name: Apbūves platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.418 General_Farmland_cell

filename: General_Farmland_cell.tif

layername: egv_418

English name: Fractional cover of Farmland within the analysis cell (1 ha)

Latvian name: Lauksaimniecībā izmantojamo zemju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.419 General_Farmland_r500

filename: General_Farmland_r500.tif

layername: egv_419

English name: Fractional cover of Farmland within the 0.5 km landscape

Latvian name: Lauksaimniecībā izmantojamo zemju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.420 General_Farmland_r1250

filename: General_Farmland_r1250.tif

layername: egv_420

English name: Fractional cover of Farmland within the 1.25 km landscape

Latvian name: Lauksaimniecībā izmantojamo zemju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.421 General_Farmland_r3000

filename: General_Farmland_r3000.tif

layername: egv_421

English name: Fractional cover of Farmland within the 3 km landscape

Latvian name: Lauksaimniecībā izmantojamo zemju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.422 General_Farmland_r10000

filename: General_Farmland_r10000.tif

layername: egv_422

English name: Fractional cover of Farmland within the 10 km landscape

Latvian name: Lauksaimniecībā izmantojamo zemju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.423 General_ForestsWithoutInventory_cell

filename: General_ForestsWithoutInventory_cell.tif

layername: egv_423

English name: Fractional cover of Forests Without Inventory within the analysis cell (1 ha)

Latvian name: Netaksēto mežu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.424 General_ForestsWithoutInventory_r500

filename: General_ForestsWithoutInventory_r500.tif

layername: egv_424

English name: Fractional cover of Forests Without Inventory within the 0.5 km landscape

Latvian name: Netaksēto mežu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.425 General_ForestsWithoutInventory_r1250

filename: General_ForestsWithoutInventory_r1250.tif

layername: egv_425

English name: Fractional cover of Forests Without Inventory within the 1.25 km landscape

Latvian name: Netaksēto mežu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.426 General_ForestsWithoutInventory_r3000

filename: General_ForestsWithoutInventory_r3000.tif

layername: egv_426

English name: Fractional cover of Forests Without Inventory within the 3 km landscape

Latvian name: Netaksēto mežu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.427 General_ForestsWithoutInventory_r10000

filename: General_ForestsWithoutInventory_r10000.tif

layername: egv_427

English name: Fractional cover of Forests Without Inventory within the 10 km landscape

Latvian name: Netaksēto mežu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.428 General_GardensOrchards_cell

filename: General_GardensOrchards_cell.tif

layername: egv_428

English name: Fractional cover of Allotment gardens, Orchards within the analysis cell (1 ha)

Latvian name: Vasarnīcu kompleksu un augļudārzu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.429 General_GardensOrchards_r500

filename: General_GardensOrchards_r500.tif

layername: egv_429

English name: Fractional cover of Allotment gardens, Orchards within the 0.5 km landscape

Latvian name: Vasarnīcu kompleksu un augļudārzu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.430 General_GardensOrchards_r1250

filename: General_GardensOrchards_r1250.tif

layername: egv_430

English name: Fractional cover of Allotment gardens, Orchards within the 1.25 km landscape

Latvian name: Vasarnīcu kompleksu un augļudārzu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.431 General_GardensOrchards_r3000

filename: General_GardensOrchards_r3000.tif

layername: egv_431

English name: Fractional cover of Allotment gardens, Orchards within the 3 km landscape

Latvian name: Vasarnīcu kompleksu un augļudārzu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.432 General_GardensOrchards_r10000

filename: General_GardensOrchards_r10000.tif

layername: egv_432

English name: Fractional cover of Allotment gardens, Orchards within the 10 km landscape

Latvian name: Vasarnīcu kompleksu un augļudārzu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.433 General_Roads_cell

filename: General_Roads_cell.tif

layername: egv_433

English name: Fractional cover of Roads within the analysis cell (1 ha)

Latvian name: Ceļu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.434 General_ShrubsOrchards_cell

filename: General_ShrubsOrchards_cell.tif

layername: egv_434

English name: Fractional cover of Shrubs, Young stands, Orchards within the analysis cell (1 ha)

Latvian name: Krūmāju, jaunaudžu un augļudārzu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.435 General_ShrubsOrchards_r500

filename: General_ShrubsOrchards_r500.tif

layername: egv_435

English name: Fractional cover of Shrubs, Young stands, Orchards within the 0.5 km landscape

Latvian name: Krūmāju, jaunaudžu un augļudārzu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.436 General_ShrubsOrchards_r1250

filename: General_ShrubsOrchards_r1250.tif

layername: egv_436

English name: Fractional cover of Shrubs, Young stands, Orchards within the 1.25 km landscape

Latvian name: Krūmāju, jaunaudžu un augļudārzu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.437 General_ShrubsOrchards_r3000

filename: General_ShrubsOrchards_r3000.tif

layername: egv_437

English name: Fractional cover of Shrubs, Young stands, Orchards within the 3 km landscape

Latvian name: Krūmāju, jaunaudžu un augļudārzu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.438 General_ShrubsOrchards_r10000

filename: General_ShrubsOrchards_r10000.tif

layername: egv_438

English name: Fractional cover of Shrubs, Young stands, Orchards within the 10 km landscape

Latvian name: Krūmāju, jaunaudžu un augļudārzu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.439 General_ShrubsOrchardsGardens_cell

filename: General_ShrubsOrchardsGardens_cell.tif

layername: egv_439

English name: Fractional cover of Shrubs, Young stands, Orchards, Allotment gardens within the analysis cell (1 ha)

Latvian name: Krūmāju, jaunaudžu, augļudārzu un vasarnīcu kompleksu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.440 General_ShrubsOrchardsGardens_r500

filename: General_ShrubsOrchardsGardens_r500.tif

layername: egv_440

English name: Fractional cover of Shrubs, Young stands, Orchards, Allotment gardens within the 0.5 km landscape

Latvian name: Krūmāju, jaunaudžu, augļudārzu un vasarnīcu kompleksu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.441 General_ShrubsOrchardsGardens_r1250

filename: General_ShrubsOrchardsGardens_r1250.tif

layername: egv_441

English name: Fractional cover of Shrubs, Young stands, Orchards, Allotment gardens within the 1.25 km landscape

Latvian name: Krūmāju, jaunaudžu, augļudārzu un vasarnīcu kompleksu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.442 General_ShrubsOrchardsGardens_r3000

filename: General_ShrubsOrchardsGardens_r3000.tif

layername: egv_442

English name: Fractional cover of Shrubs, Young stands, Orchards, Allotment gardens within the 3 km landscape

Latvian name: Krūmāju, jaunaudžu, augļudārzu un vasarnīcu kompleksu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.443 General_ShrubsOrchardsGardens_r10000

filename: General_ShrubsOrchardsGardens_r10000.tif

layername: egv_443

English name: Fractional cover of Shrubs, Young stands, Orchards, Allotment gardens within the 10 km landscape

Latvian name: Krūmāju, jaunaudžu, augļudārzu un vasarnīcu kompleksu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.444 General_SwampsMiresBogsHelophytes_cell

filename: General_SwampsMiresBogsHelophytes_cell.tif

layername: egv_444

English name: Fractional cover of Swamps, Mires, Bogs, Reed-, Sedge-, Rush- Beds within the analysis cell (1 ha)

Latvian name: Purvu, niedrāju, grīslāju, meldrāju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.445 General_SwampsMiresBogsHelophytes_r500

filename: General_SwampsMiresBogsHelophytes_r500.tif

layername: egv_445

English name: Fractional cover of Swamps, Mires, Bogs, Reed-, Sedge-, Rush- Beds within the 0.5 km landscape

Latvian name: Purvu, niedrāju, grīslāju, meldrāju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.446 General_SwampsMiresBogsHelophytes_r1250

filename: General_SwampsMiresBogsHelophytes_r1250.tif

layername: egv_446

English name: Fractional cover of Swamps, Mires, Bogs, Reed-, Sedge-, Rush- Beds within the 1.25 km landscape

Latvian name: Purvu, niedrāju, grīslāju, meldrāju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.447 General_SwampsMiresBogsHelophytes_r3000

filename: General_SwampsMiresBogsHelophytes_r3000.tif

layername: egv_447

English name: Fractional cover of Swamps, Mires, Bogs, Reed-, Sedge-, Rush- Beds within the 3 km landscape

Latvian name: Purvu, niedrāju, grīslāju, meldrāju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.448 General_SwampsMiresBogsHelophytes_r10000

filename: General_SwampsMiresBogsHelophytes_r10000.tif

layername: egv_448

English name: Fractional cover of Swamps, Mires, Bogs, Reed-, Sedge-, Rush- Beds within the 10 km landscape

Latvian name: Purvu, niedrāju, grīslāju, meldrāju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.449 General_Trees_cell

filename: General_Trees_cell.tif

layername: egv_449

English name: Fractional cover of Trees, Shrubs, Clear-cuts within the analysis cell (1 ha)

Latvian name: Koku, krūmu un izcirtumu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.450 General_Trees_r500

filename: General_Trees_r500.tif

layername: egv_450

English name: Fractional cover of Trees, Shrubs, Clear-cuts within the 0.5 km landscape

Latvian name: Koku, krūmu un izcirtumu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.451 General_Trees_r1250

filename: General_Trees_r1250.tif

layername: egv_451

English name: Fractional cover of Trees, Shrubs, Clear-cuts within the 1.25 km landscape

Latvian name: Koku, krūmu un izcirtumu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.452 General_Trees_r3000

filename: General_Trees_r3000.tif

layername: egv_452

English name: Fractional cover of Trees, Shrubs, Clear-cuts within the 3 km landscape

Latvian name: Koku, krūmu un izcirtumu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.453 General_Trees_r10000

filename: General_Trees_r10000.tif

layername: egv_453

English name: Fractional cover of Trees, Shrubs, Clear-cuts within the 10 km landscape

Latvian name: Koku, krūmu un izcirtumu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.454 General_TreesOutsideForests_cell

filename: General_TreesOutsideForests_cell.tif

layername: egv_454

English name: Fractional cover of Tree covered areas Outside Forests within the analysis cell (1 ha)

Latvian name: Ar kokiem klāto teritoriju ārpus mežiem platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.455 General_TreesOutsideForests_r500

filename: General_TreesOutsideForests_r500.tif

layername: egv_455

English name: Fractional cover of Tree covered areas Outside Forests within the 0.5 km landscape

Latvian name: Ar kokiem klāto teritoriju ārpus mežiem platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.456 General_TreesOutsideForests_r1250

filename: General_TreesOutsideForests_r1250.tif

layername: egv_456

English name: Fractional cover of Tree covered areas Outside Forests within the 1.25 km landscape

Latvian name: Ar kokiem klāto teritoriju ārpus mežiem platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.457 General_TreesOutsideForests_r3000

filename: General_TreesOutsideForests_r3000.tif

layername: egv_457

English name: Fractional cover of Tree covered areas Outside Forests within the 3 km landscape

Latvian name: Ar kokiem klāto teritoriju ārpus mežiem platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.458 General_TreesOutsideForests_r10000

filename: General_TreesOutsideForests_r10000.tif

layername: egv_458

English name: Fractional cover of Tree covered areas Outside Forests within the 10 km landscape

Latvian name: Ar kokiem klāto teritoriju ārpus mežiem platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.459 General_Water_cell

filename: General_Water_cell.tif

layername: egv_459

English name: Fractional cover of Waterbodies within the analysis cell (1 ha)

Latvian name: Ūdenstilpju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.460 General_Water_r500

filename: General_Water_r500.tif

layername: egv_460

English name: Fractional cover of Waterbodies within the 0.5 km landscape

Latvian name: Ūdenstilpju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.461 General_Water_r1250

filename: General_Water_r1250.tif

layername: egv_461

English name: Fractional cover of Waterbodies within the 1.25 km landscape

Latvian name: Ūdenstilpju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.462 General_Water_r3000

filename: General_Water_r3000.tif

layername: egv_462

English name: Fractional cover of Waterbodies within the 3 km landscape

Latvian name: Ūdenstilpju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.463 General_Water_r10000

filename: General_Water_r10000.tif

layername: egv_463

English name: Fractional cover of Waterbodies within the 10 km landscape

Latvian name: Ūdenstilpju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.464 Wetlands_Bogs_cell

filename: Wetlands_Bogs_cell.tif

layername: egv_464

English name: Fractional cover of Raised Bogs within the analysis cell (1 ha)

Latvian name: Augsto purvu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.465 Wetlands_Bogs_r500

filename: Wetlands_Bogs_r500.tif

layername: egv_465

English name: Fractional cover of Raised Bogs within the 0.5 km landscape

Latvian name: Augsto purvu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.466 Wetlands_Bogs_r1250

filename: Wetlands_Bogs_r1250.tif

layername: egv_466

English name: Fractional cover of Raised Bogs within the 1.25 km landscape

Latvian name: Augsto purvu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.467 Wetlands_Bogs_r3000

filename: Wetlands_Bogs_r3000.tif

layername: egv_467

English name: Fractional cover of Raised Bogs within the 3 km landscape

Latvian name: Augsto purvu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.468 Wetlands_Bogs_r10000

filename: Wetlands_Bogs_r10000.tif

layername: egv_468

English name: Fractional cover of Raised Bogs within the 10 km landscape

Latvian name: Augsto purvu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.469 Wetlands_Mires_cell

filename: Wetlands_Mires_cell.tif

layername: egv_469

English name: Fractional cover of Transitional Mires within the analysis cell (1 ha)

Latvian name: Pārejas purvu platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.470 Wetlands_Mires_r500

filename: Wetlands_Mires_r500.tif

layername: egv_470

English name: Fractional cover of Transitional Mires within the 0.5 km landscape

Latvian name: Pārejas purvu platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.471 Wetlands_Mires_r1250

filename: Wetlands_Mires_r1250.tif

layername: egv_471

English name: Fractional cover of Transitional Mires within the 1.25 km landscape

Latvian name: Pārejas purvu platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.472 Wetlands_Mires_r3000

filename: Wetlands_Mires_r3000.tif

layername: egv_472

English name: Fractional cover of Transitional Mires within the 3 km landscape

Latvian name: Pārejas purvu platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.473 Wetlands_Mires_r10000

filename: Wetlands_Mires_r10000.tif

layername: egv_473

English name: Fractional cover of Transitional Mires within the 10 km landscape

Latvian name: Pārejas purvu platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.474 Wetlands_ReedSedgeRushBeds_cell

filename: Wetlands_ReedSedgeRushBeds_cell.tif

layername: egv_474

English name: Fractional cover of Reed-, Sedge-, Rush-, Beds within the analysis cell (1 ha)

Latvian name: Niedrāju, grīslāju, meldrāju platības īpatsvars analīzes šūnā (1 ha)

Procedure:

Code

# libs ----

6.475 Wetlands_ReedSedgeRushBeds_r500

filename: Wetlands_ReedSedgeRushBeds_r500.tif

layername: egv_475

English name: Fractional cover of Reed-, Sedge-, Rush-, Beds within the 0.5 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju platības īpatsvars 0,5 km ainavā

Procedure:

Code

# libs ----

6.476 Wetlands_ReedSedgeRushBeds_r1250

filename: Wetlands_ReedSedgeRushBeds_r1250.tif

layername: egv_476

English name: Fractional cover of Reed-, Sedge-, Rush-, Beds within the 1.25 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju platības īpatsvars 1,25 km ainavā

Procedure:

Code

# libs ----

6.477 Wetlands_ReedSedgeRushBeds_r3000

filename: Wetlands_ReedSedgeRushBeds_r3000.tif

layername: egv_477

English name: Fractional cover of Reed-, Sedge-, Rush-, Beds within the 3 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju platības īpatsvars 3 km ainavā

Procedure:

Code

# libs ----

6.478 Wetlands_ReedSedgeRushBeds_r10000

filename: Wetlands_ReedSedgeRushBeds_r10000.tif

layername: egv_478

English name: Fractional cover of Reed-, Sedge-, Rush-, Beds within the 10 km landscape

Latvian name: Niedrāju, grīslāju, meldrāju platības īpatsvars 10 km ainavā

Procedure:

Code

# libs ----

6.479 EO_NDMI-LYmed-average_cell

filename: EO_NDMI-LYmed-average_cell.tif

layername: egv_479

English name: Median vegetation water content (NDMI) for the last year within the analysis cell (1 ha)

Latvian name: Mediānā pēdējā gada ūdens satura veģetācijā indeksa (NDMI) vērtība, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows preprocessing. Arithmetic mean value at analysis cell calculated with egvtools::input2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented. Last year is 2024.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDMI-LYmed-average_cell.tif ----
egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDMI-LYmed-average_cell.tif",
                 layername = "egv_479",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.480 EO_NDMI-LYmedian-iqr_cell

filename: EO_NDMI-LYmedian-iqr_cell.tif

layername: egv_480

English name: Spatial variability of last year’s median vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējā gada mediānajai ūdens saturam veģetācijā indeksa (NDMI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Procedure: Directly follows preprocessing. First Q1 and then Q3 is calculated for every cell with egvtools::input2egv(). Finally, subtracting Q1 from Q3 and writing final raster with specified layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented. Last year is 2024.

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDMI-LYmedian-iqr_cell.tif ----

p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_480",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_480",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDMI-LYmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.481 EO_NDMI-STiqr-median_cell

filename: EO_NDMI-STiqr-median_cell.tif

layername: egv_481

English name: Average short-term seasonality of vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Sezonalitāte pēdējo piecu gadu vidējam ūdens satura veģetācijā indeksa (NDMI) vērtībai, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDMI-STiqr-median_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STiqr.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDMI-STiqr-median_cell.tif",
                 layername = "egv_481",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.482 EO_NDMI-STmedian-average_cell

filename: EO_NDMI-STmedian-average_cell.tif

layername: egv_482

English name: Median short-term vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Mediānā pēdējo piecu gadu ūdens satura veģetācijā indeksa (NDMI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDMI-STmedian-average_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDMI-STmedian-average_cell.tif",
                 layername = "egv_482",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.483 EO_NDMI-STmedian-iqr_cell

filename: EO_NDMI-STmedian-iqr_cell.tif

layername: egv_483

English name: Spatial variability of short-term median vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējo piecu gadu mediānajai ūdens saturam veģetācijā indeksa (NDMI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDMI-STmedian-iqr_cell.tif ----


p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_483",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_483",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDMI-STmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.484 EO_NDMI-STp25-min_cell

filename: EO_NDMI-STp25-min_cell.tif

layername: egv_484

English name: Minimum short-term 25th percentile of vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Minimālā 25. procentiles pēdējo piecu gadu ūdens satura veģetācijā indeksa (NDMI) vērtība, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows preprocessing. Minimum value at analysis cell calculated with egvtools::input2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented. Short-term is last five years (2020-2024).

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDMI-STp25-min_cell.tif ----


egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STp25.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDMI-STp25-min_cell.tif",
                 layername = "egv_484",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.485 EO_NDMI-STp75-max_cell

filename: EO_NDMI-STp75-max_cell.tif

layername: egv_485

English name: Maximum short-term 75th percentile of vegetation water content (NDMI) within the analysis cell (1 ha)

Latvian name: Maksimālā 75. procentiles pēdējo piecu gadu ūdens satura veģetācijā indeksa (NDMI) vērtība, vidējais analīzes šūnā (1 ha)

Procedure: Directly follows preprocessing. Maximum value at analysis cell calculated with egvtools::input2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented. Short-term is last five years (2020-2024).

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDMI-STp75-max_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDMI-STp75.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDMI-STp75-max_cell.tif",
                 layername = "egv_485",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.486 EO_NDVI-LYmedian-average_cell

filename: EO_NDVI-LYmedian-average_cell.tif

layername: egv_486

English name: Median vegetation index (NDVI) for the last year within the analysis cell (1 ha)

Latvian name: Mediānā pēdējā gada veģetācijas indeksa (NDVI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDVI-LYmedian-average_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDVI-LYmedian-average_cell.tif",
                 layername = "egv_486",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.487 EO_NDVI-LYmedian-iqr_cell

filename: EO_NDVI-LYmedian-iqr_cell.tif

layername: egv_487

English name: Spatial variability of last year’s median vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējā gada mediānajai veģetācijas indeksa (NDVI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDVI-LYmedian-iqr_cell.tif ----


p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_487",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_487",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDVI-LYmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.488 EO_NDVI-STiqr-median_cell

filename: EO_NDVI-STiqr-median_cell.tif

layername: egv_488

English name: Average short-term seasonality of vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Sezonalitāte pēdējo piecu gadu vidējam veģetācijas indeksa (NDVI) vērtībai, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDVI-STiqr-median_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STiqr.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDVI-STiqr-median_cell.tif",
                 layername = "egv_488",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.489 EO_NDVI-STmedian-average_cell

filename: EO_NDVI-STmedian-average_cell.tif

layername: egv_489

English name: Median short-term vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Mediānā pēdējo piecu gadu veģetācijas indeksa (NDVI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDVI-STmedian-average_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDVI-STmedian-average_cell.tif",
                 layername = "egv_489",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.490 EO_NDVI-STmedian-iqr_cell

filename: EO_NDVI-STmedian-iqr_cell.tif

layername: egv_490

English name: Spatial variability of short-term median vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējo piecu gadu mediānajai veģetācijas indeksa (NDVI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDVI-STmedian-iqr_cell.tif ----


p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_490",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_490",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDVI-STmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.491 EO_NDVI-STp25-min_cell

filename: EO_NDVI-STp25-min_cell.tif

layername: egv_491

English name: Minimum short-term 25th percentile of vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Minimālā 25. procentiles pēdējo piecu gadu veģetācijas indeksa (NDVI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDVI-STp25-min_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STp25.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDVI-STp25-min_cell.tif",
                 layername = "egv_491",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.492 EO_NDVI-STp75-max_cell

filename: EO_NDVI-STp75-max_cell.tif

layername: egv_492

English name: Maximum short-term 75th percentile of vegetation index (NDVI) within the analysis cell (1 ha)

Latvian name: Maksimālā 75. procentiles pēdējo piecu gadu veģetācijas indeksa (NDVI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDVI-STp75-max_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDVI-STp75.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDVI-STp75-max_cell.tif",
                 layername = "egv_492",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.493 EO_NDWI-LYmedian-average_cell

filename: EO_NDWI-LYmedian-average_cell.tif

layername: egv_493

English name: Median water index (NDWI) for the last year within the analysis cell (1 ha)

Latvian name: Mediānā pēdējā gada ūdens indeksa (NDWI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDWI-LYmedian-average_cell.tif",
                 layername = "egv_493",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.494 EO_NDWI-LYmedian-iqr_cell

filename: EO_NDWI-LYmedian-iqr_cell.tif

layername: egv_494

English name: Spatial variability of last year’s median water index (NDWI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējā gada mediānajai ūdens indeksa (NDWI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDWI-LYmedian-iqr_cell.tif ----


p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_494",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-LYmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_494",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDWI-LYmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.495 EO_NDWI-STiqr-median_cell

filename: EO_NDWI-STiqr-median_cell.tif

layername: egv_495

English name: Average short-term seasonality of water index (NDWI) within the analysis cell (1 ha)

Latvian name: Sezonalitāte pēdējo piecu gadu vidējam ūdens indeksa (NDWI) vērtībai, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDWI-STiqr-median_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STiqr.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDWI-STiqr-median_cell.tif",
                 layername = "egv_495",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.496 EO_NDWI-STmedian-average_cell

filename: EO_NDWI-STmedian-average_cell.tif

layername: egv_496

English name: Median short-term water index (NDWI) within the analysis cell (1 ha)

Latvian name: Mediānā pēdējo piecu gadu ūdens indeksa (NDWI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDWI-STmedian-average_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "average",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDWI-STmedian-average_cell.tif",
                 layername = "egv_496",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.497 EO_NDWI-STmedian-iqr_cell

filename: EO_NDWI-STmedian-iqr_cell.tif

layername: egv_497

English name: Spatial variability of short-term median water index (NDWI) within the analysis cell (1 ha)

Latvian name: Telpiskā variabilitāte pēdējo piecu gadu mediānajai ūdens indeksa (NDWI) vērtībai, starpkvartiļu apgabals analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDWI-STmedian-iqr_cell.tif ----

p25rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_497",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STmedian.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_497",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/EO_NDWI-STmedian-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.498 EO_NDWI-STp25-min_cell

filename: EO_NDWI-STp25-min_cell.tif

layername: egv_498

English name: Minimum short-term 25th percentile of water index (NDWI) within the analysis cell (1 ha)

Latvian name: Minimālā 25. procentiles pēdējo piecu gadu ūdens indeksa (NDWI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EO_NDWI-STp25-min_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STp25.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDWI-STp25-min_cell.tif",
                 layername = "egv_498",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.499 EO_NDWI-STp75-max_cell

filename: EO_NDWI-STp75-max_cell.tif

layername: egv_499

English name: Maximum short-term 75th percentile of water index (NDWI) within the analysis cell (1 ha)

Latvian name: Maksimālā 75. procentiles pēdējo piecu gadu ūdens indeksa (NDWI) vērtība, vidējais analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# EO_NDWI-STp75-max_cell.tif ----

egvrez=input2egv(input="./Geodata/2024/S2indices/Mosaics/EO_NDWI-STp75.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "min",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/RAW/",
                 outfilename = "EO_NDWI-STp75-max_cell.tif",
                 layername = "egv_499",
                 idw_weight = 2,
                 plot_gaps = FALSE,
                 plot_final = FALSE)
egvrez

6.500 SoilChemistry_ESDAC-CN_cell

filename: SoilChemistry_ESDAC-CN_cell.tif

layername: egv_500

English name: Average value of Topsoil Carbon-Nitrogen ratio (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas oglekļa-slāpekļa attiecība (ESDAC v2.0) analīzes šūnā (1 ha)

Procedure: Directly derived from Soil chemistry. Processed with egvtools::downscale2egv() with fill gaps = TRUE performing inverse distance weighted (power = 2) filling of gaps at the border and smooth = FALSE to keep as original values as reasonable (there is bilinear interpolation involved when projecting from 500 m to 100 m resolution of different CRS).

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# CN ----

egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/CN/CN.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-CN_cell.tif",
  layer_name    = "egv_500",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.501 SoilChemistry_ESDAC-CaCo3_cell

filename: SoilChemistry_ESDAC-CaCo3_cell.tif

layername: egv_501

English name: Average value of Topsoil Calcium Carbonates Content (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas kalcija karbonātu apjoms (ESDAC v2.0) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# CaCO3 ----


egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/Caco3/CaCO3.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-CaCo3_cell.tif",
  layer_name    = "egv_501",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.502 SoilChemistry_ESDAC-K_cell

filename: SoilChemistry_ESDAC-K_cell.tif

layername: egv_502

English name: Average value of Topsoil Sodium Content (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas kālija apjoms (ESDAC v2.0) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# K ----

egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/K/K.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-K_cell.tif",
  layer_name    = "egv_502",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.503 SoilChemistry_ESDAC-N_cell

filename: SoilChemistry_ESDAC-N_cell.tif

layername: egv_503

English name: Average value of Topsoil Nitrogen Content (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas slāpekļa apjoms (ESDAC v2.0) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# N ----

egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/N/N.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-N_cell.tif",
  layer_name    = "egv_503",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.504 SoilChemistry_ESDAC-P_cell

filename: SoilChemistry_ESDAC-P_cell.tif

layername: egv_504

English name: Average value of Topsoil Phosphorous Content (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas fosfora apjoms (ESDAC v2.0) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# P ----

egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/P/P.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-P_cell.tif",
  layer_name    = "egv_504",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.505 SoilChemistry_ESDAC-phH2O_cell

filename: SoilChemistry_ESDAC-phH2O_cell.tif

layername: egv_505

English name: Average value of Topsoil pH reaction in water (ESDAC v2.0) within the analysis cell (1 ha)

Latvian name: Augsnes virskārtas reakcija (pH) ūdens šķīdumā (ESDAC v2.0) analīzes šūnā (1 ha)

Code

# libs ----
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}


# pH_H2O ----

egv=downscale2egv(
  template_path = "./Templates/TemplateRasters/LV100m_10km.tif",
  grid_path     = "./Templates/TemplateGrids/tikls1km_sauzeme.parquet",
  rawfile_path  = "./Geodata/2024/Soils/ESDAC/chemistry/chemistry/pH_H2O/pH_H2O.tif",
  out_path      = "./RasterGrids_100m/2024/RAW/",
  file_name     = "SoilChemistry_ESDAC-phH2O_cell.tif",
  layer_name    = "egv_505",
  fill_gaps     = TRUE,
  smooth        = FALSE,
  plot_result   = TRUE)
egv

6.506 SoilTexture_Clay_cell

filename: SoilTexture_Clay_cell.tif

layername: egv_506

English name: Fractional cover of Clay Soils within the analysis cell (1 ha)

Latvian name: Augsnes granulometriskās klases “māls” platības īpatsvars analīzes šūnā (1 ha)

Procedure: Derived from Soil texture product. First, layer is reclassified so that class of interest is 1, other classes are 0. Then processed with egvtools::input2egv() with fill gaps = TRUE performing inverse distance weighted (power = 2) filling of gaps at the border.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# input ----
combtext=rast("./RasterGrids_10m/2024/SoilTXT_combined.tif")

# EGVs cell ----

# SoilTexture_Clay_cell.tif egv_506

clay10=ifel(combtext==3,1,0)

input2egv(input=clay10,
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "SoilTexture_Clay_cell.tif",
          layername="egv_506",
          return_visible = TRUE)

6.507 SoilTexture_Clay_r500

filename: SoilTexture_Clay_r500.tif

layername: egv_507

English name: Fractional cover of Clay Soils within the 0.5 km landscape

Latvian name: Augsnes granulometriskās klases “māls” platības īpatsvars 0,5 km ainavā

Procedure: Derived from SoilTexture_Clay_cell. First processed with egvtools::radius_function(), then rewritten to ensure layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_cell.tif"),
  layer_prefixes = c("SoilTexture_Clay"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Clay_r500.tif egv_507

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r500.tif")
names(slanis)="egv_507"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r500.tif",
            overwrite=TRUE)

6.508 SoilTexture_Clay_r1250

filename: SoilTexture_Clay_r1250.tif

layername: egv_508

English name: Fractional cover of Clay Soils within the 1.25 km landscape

Latvian name: Augsnes granulometriskās klases “māls” platības īpatsvars 1,25 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_cell.tif"),
  layer_prefixes = c("SoilTexture_Clay"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# SoilTexture_Clay_r1250.tif    egv_508

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r1250.tif")
names(slanis)="egv_508"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r1250.tif",
            overwrite=TRUE)

6.509 SoilTexture_Clay_r3000

filename: SoilTexture_Clay_r3000.tif

layername: egv_509

English name: Fractional cover of Clay Soils within the 3 km landscape

Latvian name: Augsnes granulometriskās klases “māls” platības īpatsvars 3 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_cell.tif"),
  layer_prefixes = c("SoilTexture_Clay"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Clay_r3000.tif    egv_509

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r3000.tif")
names(slanis)="egv_509"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r3000.tif",
            overwrite=TRUE)

6.510 SoilTexture_Clay_r10000

filename: SoilTexture_Clay_r10000.tif

layername: egv_510

English name: Fractional cover of Clay Soils within the 10 km landscape

Latvian name: Augsnes granulometriskās klases “māls” platības īpatsvars 10 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_cell.tif"),
  layer_prefixes = c("SoilTexture_Clay"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# SoilTexture_Clay_r10000.tif   egv_510

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r10000.tif")
names(slanis)="egv_510"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Clay_r10000.tif",
            overwrite=TRUE)

6.511 SoilTexture_Organic_cell

filename: SoilTexture_Organic_cell.tif

layername: egv_511

English name: Fractional cover of Organic Soils within the analysis cell (1 ha)

Latvian name: Augsnes granulometriskās klases “organiskās augsnes” platības īpatsvars analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# input ----
combtext=rast("./RasterGrids_10m/2024/SoilTXT_combined.tif")

# EGVs cell ----

# SoilTexture_Organic_cell.tif  egv_511

org10=ifel(combtext==4,1,0)

input2egv(input=org10,
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "SoilTexture_Organic_cell.tif",
          layername="egv_511",
          return_visible = TRUE)

6.512 SoilTexture_Organic_r500

filename: SoilTexture_Organic_r500.tif

layername: egv_512

English name: Fractional cover of Organic Soils within the 0.5 km landscape

Latvian name: Augsnes granulometriskās klases “organiskās augsnes” platības īpatsvars 0,5 km ainavā

Procedure: Derived from SoilTexture_Organic_cell. First processed with egvtools::radius_function(), then rewritten to ensure layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_cell.tif"),
  layer_prefixes = c("SoilTexture_Organic"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Organic_r500.tif  egv_512

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r500.tif")
names(slanis)="egv_512"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r500.tif",
            overwrite=TRUE)

6.513 SoilTexture_Organic_r1250

filename: SoilTexture_Organic_r1250.tif

layername: egv_513

English name: Fractional cover of Organic Soils within the 1.25 km landscape

Latvian name: Augsnes granulometriskās klases “organiskās augsnes” platības īpatsvars 1,25 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_cell.tif"),
  layer_prefixes = c("SoilTexture_Organic"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# SoilTexture_Organic_r1250.tif egv_513

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r1250.tif")
names(slanis)="egv_513"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r1250.tif",
            overwrite=TRUE)

6.514 SoilTexture_Organic_r3000

filename: SoilTexture_Organic_r3000.tif

layername: egv_514

English name: Fractional cover of Organic Soils within the 3 km landscape

Latvian name: Augsnes granulometriskās klases “organiskās augsnes” platības īpatsvars 3 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_cell.tif"),
  layer_prefixes = c("SoilTexture_Organic"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Organic_r3000.tif egv_514

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r3000.tif")
names(slanis)="egv_514"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r3000.tif",
            overwrite=TRUE)

6.515 SoilTexture_Organic_r10000

filename: SoilTexture_Organic_r10000.tif

layername: egv_515

English name: Fractional cover of Organic Soils within the 10 km landscape

Latvian name: Augsnes granulometriskās klases “organiskās augsnes” platības īpatsvars 10 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_cell.tif"),
  layer_prefixes = c("SoilTexture_Organic"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Organic_r10000.tif    egv_515

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r10000.tif")
names(slanis)="egv_515"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Organic_r10000.tif",
            overwrite=TRUE)

6.516 SoilTexture_Sand_cell

filename: SoilTexture_Sand_cell.tif

layername: egv_516

English name: Fractional cover of Sand Soils within the analysis cell (1 ha)

Latvian name: Augsnes granulometriskās klases “smilts” platības īpatsvars analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# input ----
combtext=rast("./RasterGrids_10m/2024/SoilTXT_combined.tif")

# EGVs cell ----

# SoilTexture_Sand_cell.tif egv_516

sand10=ifel(combtext==1,1,0)
plot(sand10)

input2egv(input=sand10,
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "SoilTexture_Sand_cell.tif",
          layername="egv_516",
          return_visible = TRUE)

6.517 SoilTexture_Sand_r500

filename: SoilTexture_Sand_r500.tif

layername: egv_517

English name: Fractional cover of Sand Soils within the 0.5 km landscape

Latvian name: Augsnes granulometriskās klases “smilts” platības īpatsvars 0,5 km ainavā

Procedure: Derived from SoilTexture_Sand_cell. First processed with egvtools::radius_function(), then rewritten to ensure layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_cell.tif"),
  layer_prefixes = c("SoilTexture_Sand"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Sand_r500.tif egv_517

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r500.tif")
names(slanis)="egv_517"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r500.tif",
            overwrite=TRUE)

6.518 SoilTexture_Sand_r1250

filename: SoilTexture_Sand_r1250.tif

layername: egv_518

English name: Fractional cover of Sand Soils within the 1.25 km landscape

Latvian name: Augsnes granulometriskās klases “smilts” platības īpatsvars 1,25 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_cell.tif"),
  layer_prefixes = c("SoilTexture_Sand"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Sand_r1250.tif    egv_518

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r1250.tif")
names(slanis)="egv_518"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r1250.tif",
            overwrite=TRUE)

6.519 SoilTexture_Sand_r3000

filename: SoilTexture_Sand_r3000.tif

layername: egv_519

English name: Fractional cover of Sand Soils within the 3 km landscape

Latvian name: Augsnes granulometriskās klases “smilts” platības īpatsvars 3 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_cell.tif"),
  layer_prefixes = c("SoilTexture_Sand"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Sand_r3000.tif    egv_519

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r3000.tif")
names(slanis)="egv_519"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r3000.tif",
            overwrite=TRUE)

6.520 SoilTexture_Sand_r10000

filename: SoilTexture_Sand_r10000.tif

layername: egv_520

English name: Fractional cover of Sand Soils within the 10 km landscape

Latvian name: Augsnes granulometriskās klases “smilts” platības īpatsvars 10 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_cell.tif"),
  layer_prefixes = c("SoilTexture_Sand"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Sand_r10000.tif   egv_520

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r10000.tif")
names(slanis)="egv_520"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Sand_r10000.tif",
            overwrite=TRUE)

6.521 SoilTexture_Silt_cell

filename: SoilTexture_Silt_cell.tif

layername: egv_521

English name: Fractional cover of Silt Soils within the analysis cell (1 ha)

Latvian name: Augsnes granulometriskās klases “smilšmāls un mālsmilts” platības īpatsvars analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template10=rast("./Templates/TemplateRasters/LV10m_10km.tif")
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# input ----
combtext=rast("./RasterGrids_10m/2024/SoilTXT_combined.tif")

# EGVs cell ----

# SoilTexture_Silt_cell.tif egv_521

silt10=ifel(combtext==2,1,0)

input2egv(input=silt10,
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "SoilTexture_Silt_cell.tif",
          layername="egv_521",
          return_visible = TRUE)

6.522 SoilTexture_Silt_r500

filename: SoilTexture_Silt_r500.tif

layername: egv_522

English name: Fractional cover of Silt Soils within the 0.5 km landscape

Latvian name: Augsnes granulometriskās klases “smilšmāls un mālsmilts” platības īpatsvars 0,5 km ainavā

Procedure: Derived from SoilTexture_Silt_cell. First processed with egvtools::radius_function(), then rewritten to ensure layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_cell.tif"),
  layer_prefixes = c("SoilTexture_Silt"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Silt_r500.tif egv_522

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r500.tif")
names(slanis)="egv_522"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r500.tif",
            overwrite=TRUE)

6.523 SoilTexture_Silt_r1250

filename: SoilTexture_Silt_r1250.tif

layername: egv_523

English name: Fractional cover of Silt Soils within the 1.25 km landscape

Latvian name: Augsnes granulometriskās klases “smilšmāls un mālsmilts” platības īpatsvars 1,25 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_cell.tif"),
  layer_prefixes = c("SoilTexture_Silt"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Silt_r1250.tif    egv_523

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r1250.tif")
names(slanis)="egv_523"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r1250.tif",
            overwrite=TRUE)

6.524 SoilTexture_Silt_r3000

filename: SoilTexture_Silt_r3000.tif

layername: egv_524

English name: Fractional cover of Silt Soils within the 3 km landscape

Latvian name: Augsnes granulometriskās klases “smilšmāls un mālsmilts” platības īpatsvars 3 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_cell.tif"),
  layer_prefixes = c("SoilTexture_Silt"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# SoilTexture_Silt_r3000.tif    egv_524

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r3000.tif")
names(slanis)="egv_524"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r3000.tif",
            overwrite=TRUE)

6.525 SoilTexture_Silt_r10000

filename: SoilTexture_Silt_r10000.tif

layername: egv_525

English name: Fractional cover of Silt Soils within the 10 km landscape

Latvian name: Augsnes granulometriskās klases “smilšmāls un mālsmilts” platības īpatsvars 10 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# EGVs radii ----

radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_cell.tif"),
  layer_prefixes = c("SoilTexture_Silt"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# SoilTexture_Silt_r10000.tif   egv_525

slanis=rast("./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r10000.tif")
names(slanis)="egv_525"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/SoilTexture_Silt_r10000.tif",
            overwrite=TRUE)

6.526 Terrain_ASL-average_cell

filename: Terrain_ASL-average_cell.tif

layername: egv_526

English name: Average value of height Above Sea Level (m) within the analysis cell (1 ha)

Latvian name: Augstums virs jūras līmeņa (m) analīzes šūnā (1 ha)

Procedure: Derived from Digital elevation/terrain models. Processed with egvtools::input2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")

# Terrain_ASL-average_cell.tif  egv_526

input2egv(input="./Geodata/2024/DEM/mozDEM_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_ASL-average_cell.tif",
          layername="egv_526",
          return_visible = TRUE,
          plot_final = TRUE)

6.527 Terrain_Aspect-average_cell

filename: Terrain_Aspect-average_cell.tif

layername: egv_527

English name: Average value of Terrain Aspect (degree) within the analysis cell (1 ha)

Latvian name: Nogāzes vidējais vērsuma virziens analīzes šūnā (1 ha)

Procedure: Derived from Terrain products. Processed with egvtools::input2egv(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_Aspect-average_cell.tif   egv_527
input2egv(input="./RasterGrids_10m/2024/Terrain_Aspect_udeni2_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_Aspect-average_cell.tif",
          layername="egv_527",
          return_visible = TRUE,
          plot_final = TRUE)

6.528 Terrain_Aspect-iqr_cell

filename: Terrain_Aspect-iqr_cell.tif

layername: egv_528

English name: Variability of Terrain Aspect (degree) within the analysis cell (1 ha)

Latvian name: Nogāzes vērsuma variabilitāte analīzes šūnā (1 ha)

Procedure: Derived from Terrain products. First Q1 and then Q3 is calculated for every cell with egvtools::input2egv(). Finally, subtracting Q1 from Q3 and writing final raster with specified layername. To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_Aspect-iqr_cell.tif   egv_528
p25rez=input2egv(input="./RasterGrids_10m/2024/Terrain_Aspect_udeni2_10m.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_528",
                 idw_weight = 2)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./RasterGrids_10m/2024/Terrain_Aspect_udeni2_10m.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_528",
                 idw_weight = 2)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/Terrain_Aspect-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.529 Terrain_DiS-area_cell

filename: Terrain_DiS-area_cell.tif

layername: egv_529

English name: Fractional cover of Terrain Sinks within the analysis cell (1 ha)

Latvian name: Reljefa depresiju bez virszemes noteces platības īpatsvars analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_DiS-area_cell.tif egv_529
dis=rast("./RasterGrids_10m/2024/Terrain_DiS_udeni2_10m.tif")
dis2=ifel(dis>0,1,dis)

input2egv(input=dis2,
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_DiS-area_cell.tif",
          layername="egv_529",
          return_visible = TRUE,
          plot_final = TRUE)

6.530 Terrain_DiS-area_r500

filename: Terrain_DiS-area_r500.tif

layername: egv_530

English name: Fractional cover of Terrain Sinks within the 0.5 km landscape

Latvian name: Reljefa depresiju bez virszemes noteces platības īpatsvars 0,5 km ainavā

Procedure: Derived from Terrain products. Processed with egvtools::radius_function(). To protect against possible data loss at edge cells, inverse distance weighted (power = 2) gap filling is implemented. After zonal statistics, file is rewritten to ensure layername.

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_cell.tif"),
  layer_prefixes = c("Terrain_DiS-area"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r500"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# Terrain_DiS-area_r500.tif egv_530
slanis=rast("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r500.tif")
names(slanis)="egv_530"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r500.tif",
            overwrite=TRUE)

6.531 Terrain_DiS-area_r1250

filename: Terrain_DiS-area_r1250.tif

layername: egv_531

English name: Fractional cover of Terrain Sinks within the 1.25 km landscape

Latvian name: Reljefa depresiju bez virszemes noteces platības īpatsvars 1,25 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_cell.tif"),
  layer_prefixes = c("Terrain_DiS-area"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r1250"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)

# Terrain_DiS-area_r1250.tif    egv_531
slanis=rast("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r1250.tif")
names(slanis)="egv_531"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r1250.tif",
            overwrite=TRUE)

6.532 Terrain_DiS-area_r3000

filename: Terrain_DiS-area_r3000.tif

layername: egv_532

English name: Fractional cover of Terrain Sinks within the 3 km landscape

Latvian name: Reljefa depresiju bez virszemes noteces platības īpatsvars 3 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_cell.tif"),
  layer_prefixes = c("Terrain_DiS-area"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r3000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# Terrain_DiS-area_r3000.tif    egv_532
slanis=rast("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r3000.tif")
names(slanis)="egv_532"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r3000.tif",
            overwrite=TRUE)

6.533 Terrain_DiS-area_r10000

filename: Terrain_DiS-area_r10000.tif

layername: egv_533

English name: Fractional cover of Terrain Sinks within the 10 km landscape

Latvian name: Reljefa depresiju bez virszemes noteces platības īpatsvars 10 km ainavā

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# radii
radius_function(
  kvadrati_path  = "./Templates/TemplateGrids/tiles/",
  radii_path     = "./Templates/TemplateGridPoints/tiles/",
  tikls100_path  = "./Templates/TemplateGrids/tikls100_sauzeme.parquet",
  template_path  = "./Templates/TemplateRasters/LV100m_10km.tif",
  input_layers   = c("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_cell.tif"),
  layer_prefixes = c("Terrain_DiS-area"),
  output_dir     = "./RasterGrids_100m/2024/RAW/",
  n_workers      = 5,
  radii          = c("r10000"),
  radius_mode    = "sparse",
  extract_fun    = "mean",
  fill_missing   = TRUE,
  IDW_weight     = 2,
  future_max_size = 5 * 1024^3)


# Terrain_DiS-area_r10000.tif   egv_533
slanis=rast("./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r10000.tif")
names(slanis)="egv_533"
slanis2=project(slanis,template100)
writeRaster(slanis2,
            "./RasterGrids_100m/2024/RAW/Terrain_DiS-area_r10000.tif",
            overwrite=TRUE)

6.534 Terrain_DiS-max_cell

filename: Terrain_DiS-max_cell.tif

layername: egv_534

English name: Maximum Depth in Terrain Sink within the analysis cell (1 ha)

Latvian name: Reljefa depresiju lielākais dziļums analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_DiS-max_cell.tif  egv_534
input2egv(input="./RasterGrids_10m/2024/Terrain_DiS_udeni2_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "max",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_DiS-max_cell.tif",
          layername="egv_534",
          return_visible = TRUE,
          plot_final = TRUE)

6.535 Terrain_DiS-mean_cell

filename: Terrain_DiS-mean_cell.tif

layername: egv_535

English name: Average Depth in Terrain Sink within the analysis cell (1 ha)

Latvian name: Reljefa depresiju vidējais dziļums analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_DiS-mean_cell.tif egv_535
input2egv(input="./RasterGrids_10m/2024/Terrain_DiS_udeni2_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_DiS-mean_cell.tif",
          layername="egv_535",
          return_visible = TRUE,
          plot_final = TRUE)

6.536 Terrain_Slope-average_cell

filename: Terrain_Slope-average_cell.tif

layername: egv_536

English name: Average value of Terrain Slope (degree) within the analysis cell (1 ha)

Latvian name: Nogāzes slīpuma vidējā vērtība analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_Slope-average_cell.tif    egv_536
input2egv(input="./RasterGrids_10m/2024/Terrain_Slope_udeni2_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_Slope-average_cell.tif",
          layername="egv_536",
          return_visible = TRUE,
          plot_final = TRUE)

6.537 Terrain_Slope-iqr_cell

filename: Terrain_Slope-iqr_cell.tif

layername: egv_537

English name: Variability of Terrain Slope (degree) within the analysis cell (1 ha)

Latvian name: Nogāzes slīpuma variabilitāte analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_Slope-iqr_cell.tif    egv_537
p25rez=input2egv(input="./RasterGrids_10m/2024/Terrain_Slope_udeni2_10m.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q1",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p25.tif",
                 layername = "egv_537",
                 idw_weight = 2)
p25rez_r=rast("./RasterGrids_100m/2024/draza_p25.tif")


p75rez=input2egv(input="./RasterGrids_10m/2024/Terrain_Slope_udeni2_10m.tif",
                 egv_template= "./Templates/TemplateRasters/LV100m_10km.tif",
                 summary_function = "q3",
                 missing_job = "FillOutput",
                 outlocation = "./RasterGrids_100m/2024/",
                 outfilename = "draza_p75.tif",
                 layername = "egv_537",
                 idw_weight = 2)
p75rez_r=rast("./RasterGrids_100m/2024/draza_p75.tif")

iqr_rez=p75rez_r-p25rez_r
iqr_rez
plot(iqr_rez)

writeRaster(iqr_rez,
            "./RasterGrids_100m/2024/RAW/Terrain_Slope-iqr_cell.tif",
            overwrite=TRUE)

unlink("./RasterGrids_100m/2024/draza_p75.tif")
unlink("./RasterGrids_100m/2024/draza_p25.tif")

6.538 Terrain_TWI-average_cell

filename: Terrain_TWI-average_cell.tif

layername: egv_538

English name: Average value of Topographic Wetness Index (TWI) within the analysis cell (1 ha)

Latvian name: Topogrāfiskā mitruma indeksa vidējā vērtība analīzes šūnā (1 ha)

Code

# libs ----
if(!require(terra)) {install.packages("terra"); require(terra)}
if(!require(egvtools)) {remotes::install_github("aavotins/egvtools"); require(egvtools)}

# templates ----
template100=rast("./Templates/TemplateRasters/LV100m_10km.tif")


# Terrain_TWI-average_cell.tif  egv_538
input2egv(input="./RasterGrids_10m/2024/Terrain_TWI_udeni2_10m.tif",
          egv_template="./Templates/TemplateRasters/LV100m_10km.tif",
          summary_function = "average",
          missing_job = "FillOutput",
          idw_weight = 2,
          outlocation = "./RasterGrids_100m/2024/RAW/",
          outfilename = "Terrain_TWI-average_cell.tif",
          layername="egv_538",
          return_visible = TRUE,
          plot_final = TRUE)