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inputs.R
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inputs.R
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library(sf)
library(raster)
library(terra)
library(rmapshaper)
setwd("D:/geodata/project_data/gsp-gsocseq")
source('C:/Users/stephen.roecker/OneDrive - USDA/projects/gsp-gsocseq/code/functions.R')
# AOI ----
## CONUS ----
conus_sa <- read_sf(dsn = "D:/geodata/soils/gSSURGO_CONUS_FY20_july.gdb", layer = "SAPOLYGON")
conus_sa <- conus_sa %>%
ms_simplify() %>%
mutate(asym = "CONUS") %>%
ms_dissolve(field = "asym")
write_sf(conus_sa, dsn = "CONUS.shp")
aoi_conus_bufbox <- conus_sa %>%
mutate(asym = "CONUS") %>%
ms_dissolve(field = "asym") %>%
st_buffer(dist = 1000 * 100) %>%
st_transform(crs = 4326) %>%
st_bbox() %>%
st_as_sfc()
mapview::mapview(aoi_conus_bufbox)
write_sf(aoi_conus_bufbox, dsn = "AOI_CONUS_bufbox.shp", delete_dsn = TRUE)
## OCONUS ----
asym <- c("AS", "AK", "FM", "GU", "HI", "MH", "MP", "PR", "PW", "VI")
leg <- lapply(asym, function(x) get_legend_from_SDA(WHERE = paste0("areasymbol LIKE '", x, "%'")))
leg <- do.call("rbind", leg)
leg$asym <- substr(leg$areasymbol, 1, 2)
sapol <- {
split(leg, leg$asym) ->.;
lapply(., function(x) {
cat("fetching ", x$areasymbol, "\n")
temp = fetchSDA_spatial(x$areasymbol, geom.src = "sapolygon")
temp = sf::st_as_sf(temp)
}) ->.;
}
# saveRDS(sapol, file = "sapol_oconus.rds")
sapol <- readRDS("sapol_oconus.rds")
sapol_bndy <- lapply(sapol, function(x) {
x$asym = substr(x$areasymbol, 1, 2)
# if (asym == "AK") {
# split(x, x$areasymbol) ->.;
# lapply(., function(x) {
# test = as.data.frame(st_coordinates(x))
# x$test = any(test$X > 0)
# return(x)
# }) ->.;
# do.call("rbind", .) ->.;
# }
x$asym = ifelse(x$areasymbol %in% paste0("AK", 783:788), "AK2", x$asym)
temp = ms_simplify(x) %>%
ms_dissolve(field = "asym") %>%
ms_explode()
return(temp)
})
sapol_bufbox <- {
do.call("rbind", sapol_bndy) ->.;
split(., .$asym) ->.;
lapply(., function(x) {
temp <- x %>%
st_transform(crs = 6933) %>%
st_buffer(dist = 1000 * if(all(x$asym == "AK2")) 10 else 10) %>%
st_transform(crs = 4326) %>%
st_bbox() %>%
st_as_sfc() %>%
st_as_sf()
temp$asym <- unique(x$asym)
return(temp)
}) -> .;
}
# # manually construct AK bufbox
# sapol_bufbox$AK1 <- sapol_bufbox$AK
# st_bbox(sapol_bufbox$AK1)
# st_bbox(sapol_bufbox$AK2)
# sapol_bufbox$AK <- st_as_sf(
# st_as_sfc(
# st_bbox(c(
# xmin = -187.6,
# xmax = -129.87002,
# ymin = 51.07513,
# ymax = 71.68593
# ))),
# crs = st_crs(4326)
# )
# sapol_bufbox$AK$asym = "AK"
test <- sapol_bufbox$AK2
mapview::mapview(test)
lapply(sapol_bufbox, function(x) write_sf(x, dsn = paste0("AOIs/AOI_OCONUS_", x$asym, "_bufbox.shp")))
lapply(sapol_bndy, function(x) write_sf(x, dsn = paste0("AOIs/OCONUS_", x$asym, "_boundry.shp")))
# GSOC ----
setwd("D:/geodata/project_data/gsp-gsocseq")
gsoc <- rast("D:/geodata/soils/GSOCmap1.5.0.tif")
## CONUS ----
aoi <- read_sf(dsn = "AOIs/AOI_CONUS_bufbox.shp")
gsoc2 <- crop(gsoc, aoi)
# writeRaster(gsoc2, filename = "CONUS/CONUS_GSOCmap1.5.0.tif", progress = "text", overwrite = TRUE)
gsoc2 <- raster("CONUS/CONUS_GSOCmap1.5.0.tif")
## AK ----
ex <- ext(c(-187.693995463933, -129.8666668672, 51.0744147105421, 71.6827479614154))
aoi_ak1 <- read_sf(dsn = "AOIs/AOI_OCONUS_AK_bufbox.shp")
aoi_ak2 <- read_sf(dsn = "AOIs/AOI_OCONUS_AK2_bufbox.shp")
gsoc_ak1 <- crop(gsoc, vect(aoi_ak1), filename = "AK/AK1_GSOCmap1.5.0.tif")
gsoc_ak2 <- crop(gsoc, vect(aoi_ak2), filename = "AK/AK2_GSOCmap1.5.0.tif")
# # construct extent manually
# ak_ext <- ext(c(-187.693995463933, -129.8666668672, 51.0744147105421, 71.6827479614154))
# ak_r <- rast(ak_ext, res = res(gsoc), crs = crs(gsoc))
#
# gsoc_ak1 <- resample(gsoc_ak1, ak_r)
# gsoc_ak2 <- resample(gsoc_ak2, ak_r)
#
# gsoc_ak <- merge(gsoc_ak1, gsoc_ak2, filename = "AK/AK_GSOCmap1.5.0.tif", overwrite = TRUE)
# gsoc2 <- rast("AK_GSOCmap1.5.0.tif")
## CMS ----
cms_soc <- raster("D:/geodata/soils/CMS_SOC_Mexico_CONUS_1737/data/SOC_prediction_1991_2010.tif")
cms_soc_1km <- aggregate(cms_soc, fact = 4, fun = mean, progress = "text")
cms_soc_1km <- readAll(cms_soc_1km)
cms_soc_1km <- projectRaster(from = cms_soc_1km, to = ssurgo_st, filename = "cms_soc_1km.tif", method = "bilinear", progress = "text", overwrite = TRUE)
# clay ----
## CONUS ----
gdalUtilities::gdalwarp(
srcfile = "gnatsgo_fy20_1km_clay_wt.tif",
dstfile = "CONUS_gnatsgo_fy20_1km_clay_wt.tif",
t_srs = crs(gsoc2),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear"
)
# clay <- raster("gnatsgo_fy20_1km_clay_wt.tif")
# clay_4326 <- projectRaster(
# clay,
# gsoc2,
# filename = "CONUS_gnatsgo_fy20_1km_clay_wt.tif",
# method = "bilinear",
# progress = "text",
# overwrite = TRUE,
# datatype = "INT4S"
# )
## AK ----
aoi <- "AK1"
aoi <- "AK2"
gsoc_ak <- rast(paste0(aoi, "_GSOCmap1.5.0.tif"))
clay_ak <- rast("gnatsgo_ak_fy20_1km_clay_wt.tif")
clay_ak <- resample(
clay_ak,
gsoc_ak,
filename = paste0(aoi, "_gnatsgo_fy20_1km_clay_wt.tif"),
method = "bilinear",
overwrite = TRUE,
datatype = "INT4S"
)
# TerraClimate ----
setwd("D:/geodata/project_data/gsp-gsocseq/CONUS")
aoi <- "CONUS"
## Resample original data to GSOC extent ----
gsoc2 <- rast(paste0(aoi, "_GSOCmap1.5.0.tif"))
lf <- list.files()
idx <- grepl("_Stack_228_....._TC.tif", lf)
# file.remove(lf[idx])
# tmp8100
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_AverageTemperature_1981-2001.tif"),
dstfile = paste0(aoi, "_Temp_Stack_228_81-00_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# tmp0120
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_AverageTemperature_2001-2021.tif"),
dstfile = paste0(aoi, "_Temp_Stack_228_01-19_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# ppt8100
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_Precipitation_1981-2001.tif"),
dstfile = paste0(aoi, "_Prec_Stack_228_81-00_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# ppt0120
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_Precipitation_2001-2021.tif"),
dstfile = paste0(aoi, "_Prec_Stack_228_01-19_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# pet8100
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_PET_1981-2001.tif"),
dstfile = paste0(aoi, "_PET_Stack_228_81-00_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# pet0120
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_PET_2001-2021.tif"),
dstfile = paste0(aoi, "_PET_Stack_228_01-19_TC.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear",
srcnodata = -3.4e+38,
dstnodata = -99999
)
# ## merge rasters ----
# aoi <- "AK"
#
# aois <- c("AK1", "AK2")
# vars <- list(
# tmp8100 = "Temp_Stack_228_81_00_TC",
# tmp0121 = "Temp_Stack_228_01_20_TC",
# ppt8100 = "Prec_Stack_228_81_00_TC",
# ppt0121 = "Prec_Stack_228_01_20_TC",
# pet8100 = "PET_Stack_228_81-00_TC",
# pet0121 = "PET_Stack_228_01-20_TC"
# )
#
# fn <- lapply(vars, function(x) paste0(paste(aois, x, sep = "_"), ".tif"))
#
# lapply(fn, function(x) {
# cat("merging", x, as.character(Sys.time()), "\n")
#
# # r1 <- readAll(raster(x[1]))
# # r2 <- readAll(raster(x[2]))
# r1 <- rast(x[1])
# r2 <- rast(x[2])
#
# test2 = merge(
# r1, r2,
# filename = gsub("AK1", "AK", x[1]),
# overwrite = TRUE
# )
# # gdalUtilities::gdalwarp(
# # srcfile = x,
# # dstfile = gsub("AK1", "AK", x[1])
# # )
# })
## convert variables ----
aoi <- "CONUS"
tmp8100 <- rast(paste0(aoi, "_Temp_Stack_228_81-00_TC.tif"))
tmp0119 <- rast(paste0(aoi, "_Temp_Stack_228_01-19_TC.tif"))
pet8100 <- rast(paste0(aoi, "_PET_Stack_228_81-00_TC.tif"))
pet0119 <- rast(paste0(aoi, "_PET_Stack_228_01-19_TC.tif"))
tmp8100 <- tmp8100 * 0.1
tmp0119 <- tmp0119 * 0.1
pet8100 <- pet8100 * 0.1
pet0119 <- pet0119 * 0.1
writeRaster(
tmp8100, filename = paste0(aoi, "_Temp_Stack_228_81-00_TC.tif"), overwrite = TRUE
)
writeRaster(
tmp0119, filename = paste0(aoi, "_Temp_Stack_228_01-19_TC.tif"), overwrite = TRUE
)
writeRaster(
pet8100, filename = paste0(aoi, "_PET_Stack_228_81-00_TC.tif"), overwrite = TRUE
)
writeRaster(
pet0119, filename = paste0(aoi, "_PET_Stack_228_01-19_TC.tif"), overwrite = TRUE
)
## load converted data ----
aoi <- "CONUS"
tmp8100 <- rast(paste0(aoi, "_Temp_Stack_228_81-00_TC.tif"))
tmp0119 <- rast(paste0(aoi, "_Temp_Stack_228_01-19_TC.tif"))
ppt8100 <- rast(paste0(aoi, "_Prec_Stack_228_81-00_TC.tif"))
ppt0119 <- rast(paste0(aoi, "_Prec_Stack_228_01-19_TC.tif"))
pet8100 <- rast(paste0(aoi, "_PET_Stack_228_81-00_TC.tif"))
pet0119 <- rast(paste0(aoi, "_PET_Stack_228_01-19_TC.tif"))
# create list of raster names by month
mos <- formatC(1:12, width = 2, flag = "0")
names(mos) <- month.abb
mos8100 <- lapply(mos, function(x) paste0(1981:2000, x))
mos0119 <- lapply(mos, function(x) paste0(2001:2019, x))
## average months ----
tmp8100_avg <- avgRS(tmp8100, "tmmx", mos8100)
tmp0119_avg <- avgRS(tmp0119, "tmmx", mos0119)
ppt8100_avg <- avgRS(ppt8100, "pr", mos8100)
ppt0119_avg <- avgRS(ppt0119, "pr", mos0119)
pet8100_avg <- avgRS(pet8100, "pet", mos8100)
pet0119_avg <- avgRS(pet0119, "pet", mos0119)
# cache files
writeRaster(
tmp8100_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Temp_Stack_81-00_TC.tif"), overwrite = TRUE
)
writeRaster(
tmp0119_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Temp_Stack_01-19_TC.tif"), overwrite = TRUE
)
writeRaster(
ppt8100_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Prec_Stack_81-00_TC.tif"), overwrite = TRUE
)
writeRaster(
ppt0119_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Prec_Stack_01-19_TC.tif"), overwrite = TRUE
)
writeRaster(
pet8100_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_PET_Stack_81-00_TC.tif"), overwrite = TRUE
)
writeRaster(
pet0119_avg, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_PET_Stack_01-19_TC.tif"), overwrite = TRUE
)
# load cached files
tmp8100_avg <- rast(paste0(aoi, "_Temp_Stack_81-00_TC.tif"))
tmp0121_avg <- rast(paste0(aoi, "_Temp_Stack_01-19_TC.tif"))
ppt8100_avg <- rast(paste0(aoi, "_Prec_Stack_81-00_TC.tif"))
ppt0121_avg <- rast(paste0(aoi, "_Prec_Stack_01-19_TC.tif"))
pet8100_avg <- rast(paste0(aoi, "_PET_Stack_81-00_TC.tif"))
pet0120_avg <- rast(paste0(aoi, "_PET_Stack_01-19_TC.tif"))
## average by year ----
# create list of raster names by year
yrs8100 <- lapply(1981:2000, function(x) paste0(x))
yrs8100 <- lapply(yrs8100, function(x) paste0(x, formatC(1:12, width = 2, flag = "0")))
yrs0119 <- lapply(2001:2019, function(x) paste0(x))
yrs0119 <- lapply(yrs0119, function(x) paste0(x, formatC(1:12, width = 2, flag = "0")))
tmp8100_avg_yr <- avgRS(tmp8100, "tmmx", yrs8100)
tmp0119_avg_yr <- avgRS(tmp0119, "tmmx", yrs0119)
ppt8100_sum_yr <- sumRS(ppt8100, "pr", yrs8100)
ppt0119_sum_yr <- sumRS(ppt0119, "pr", yrs0119)
pet8100_avg_yr <- avgRS(pet8100, "pet", yrs8100)
pet0119_avg_yr <- avgRS(pet0119, "pet", yrs0119)
# cache averages by year
writeRaster(
tmp8100_avg_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Temp_Stack_81-00_TC_yr.tif"), overwrite = TRUE
)
writeRaster(
tmp0119_avg_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Temp_Stack_01-19_TC_yr.tif"), overwrite = TRUE
)
writeRaster(
ppt8100_sum_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Prec_Stack_81-00_TC_yr.tif"), overwrite = TRUE
)
writeRaster(
ppt0119_sum_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_Prec_Stack_01-19_TC_yr.tif"), overwrite = TRUE
)
writeRaster(
pet8100_avg_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_PET_Stack_81-00_TC_yr.tif"), overwrite = TRUE
)
writeRaster(
pet0119_avg_yr, gdal = c("COMPRESS=DEFLATE"),
filename = paste0(aoi, "_PET_Stack_01-19_TC_yr.tif"), overwrite = TRUE
)
# load cached averages by year
tmp8100_avg_yr <- rast(paste0(aoi, "_Temp_Stack_81-00_TC_yr.tif"))
tmp0121_avg_yr <- rast(paste0(aoi, "_Temp_Stack_01-19_TC_yr.tif"))
ppt8100_sum_yr <- rast(paste0(aoi, "_Prec_Stack_81-00_TC_yr.tif"))
ppt0121_sum_yr <- rast(paste0(aoi, "_Prec_Stack_01-19_TC_yr.tif"))
pet8100_avg_yr <- rast(paste0(aoi, "_PET_Stack_81-00_TC_yr.tif"))
pet0120_avg_yr <- rast(paste0(aoi, "_PET_Stack_01-19_TC_yr.tif"))
## calculate NPP ----
# Calculate eq 1 from MIAMI MODEL (g DM/m2/day)
npp8100_ppt <- 3000 * (1 - exp(-0.000664 * ppt8100_sum_yr))
# Calculate eq 2 from MIAMI MODEL (g DM/m2/day)
npp8100_tmp <- 3000 / (1 + exp(1.315 - 0.119 * tmp8100_avg_yr))
npp8100 <- lapply(1:20, function(i) {
cat("calculating min from ", i, "\n")
npp <- min(npp8100_tmp[[i]], npp8100_ppt[[i]], na.rm = TRUE)
})
npp8100 <- rast(npp8100)
npp8100_TnCHaYr <- npp8100 * 1/100 * 0.5
writeRaster(npp8100_TnCHaYr, filename = paste0(aoi, "_NPP_MIAMI_tnC_Ha_Year_STACK_81-00.tif"), overwrite = TRUE, gdal = c("COMPRESS=DEFLATE"))
npp8100_TnCHaYr_avg <- mean(npp8100_TnCHaYr)
names(npp8100_TnCHaYr_avg) <- "NPP_MIAMI_MEAN_81-00_AOI"
writeRaster(npp8100_TnCHaYr_avg, filename = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI.tif"), overwrite = TRUE, gdal = c("COMPRESS=DEFLATE"))
# Uncertainties ----
## Min ----
tmp8100_avg_yr <- rast(paste0(aoi, "_Temp_Stack_81-00_TC_yr.tif"))
ppt8100_sum_yr <- rast(paste0(aoi, "_Prec_Stack_81-00_TC_yr.tif"))
tmp8100_min_avg <- tmp8100_avg_yr * 1.02
ppt8100_min_sum <- ppt8100_sum_yr * 0.95
npp8100_min_sum_ppt <- 3000 * (1 - exp(-0.000664 * ppt8100_min_sum))
npp8100_min_avg_tmp <- 3000 / (1 + exp(1.315 - 0.119 * tmp8100_min_avg))
npp8100_min <- lapply(1:20, function(i) {
cat("calculating min from ", i, "\n")
npp <- min(npp8100_min_sum_ppt[[i]], npp8100_min_avg_tmp[[i]], na.rm = TRUE)
})
npp8100_min <- rast(npp8100_min)
npp8100_min_TnCHaYr <- npp8100_min * 1/100 * 0.5
writeRaster(npp8100_min_TnCHaYr,
filename = paste0(aoi, "_NPP_MIAMI_tnC_Ha_Year_STACK_81-00_MIN.tif"),
overwrite = TRUE,
gdal = c("COMPRESS=DEFLATE")
)
npp8100_min_TnCHaYr_avg <- mean(npp8100_min_TnCHaYr)
names(npp8100_min_TnCHaYr_avg) <- "NPP_MIAMI_MEAN_81-00_AOI_MIN"
writeRaster(npp8100_min_TnCHaYr_avg,
filename = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI_MIN.tif"),
overwrite = TRUE,
gdal = c("COMPRESS=DEFLATE")
)
## Max ----
tmp8100_avg_yr <- rast(paste0(aoi, "_Temp_Stack_81-00_TC_yr.tif"))
ppt8100_sum_yr <- rast(paste0(aoi, "_Prec_Stack_81-00_TC_yr.tif"))
tmp8100_max_avg <- tmp8100_avg_yr * 0.98
ppt8100_max_sum <- ppt8100_sum_yr * 1.05
npp8100_max_sum_ppt <- 3000 * (1 - exp(-0.000664 * ppt8100_max_sum))
npp8100_max_avg_tmp <- 3000 / (1 + exp(1.315 - 0.119 * tmp8100_max_avg))
npp8100_max <- lapply(1:20, function(i) {
cat("calculating min from ", i, "\n")
npp <- min(npp8100_max_sum_ppt[[i]], npp8100_max_avg_tmp[[i]], na.rm = TRUE)
})
npp8100_max <- rast(npp8100_max)
npp8100_max_TnCHaYr <- npp8100_max * 1/100 * 0.5
writeRaster(npp8100_max_TnCHaYr,
filename = paste0(aoi, "_NPP_MIAMI_tnC_Ha_Year_STACK_81-00_MAX.tif"),
overwrite = TRUE,
gdal = c("COMPRESS=DEFLATE")
)
npp8100_max_TnCHaYr_avg <- mean(npp8100_max_TnCHaYr)
names(npp8100_max_TnCHaYr_avg) <- "NPP_MIAMI_MEAN_81-00_AOI_MAX"
writeRaster(npp8100_max_TnCHaYr_avg,
filename = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI_MAX.tif"),
overwrite = TRUE,
gdal = c("COMPRESS=DEFLATE")
)
# Vegetation Cover ----
aoi <- "CONUS"
gsoc2 <- rast(paste0(aoi, "_GSOCmap1.5.0.tif"))
# vars <- paste0(aoi, "_NDVI_2000-2020_prop_gt_06_CR_MES_", formatC(1:12, width = 2, flag = "0"), ".tif")
vars <- paste0("NDVI_2000-2020_prop_gt_06_CR_MES_", formatC(1:12, width = 2, flag = "0"), "_conus.tif")
veg <- rast(vars)
veg[is.na(veg)] <- 0
veg <- (veg * -0.4) + 1
names(veg) <- paste0("COV_", formatC(1:12, width = 2, flag = "0"))
writeRaster(veg,
filename = paste0(aoi, "_Cov_stack_AOI.tif"),
overwrite = TRUE,
gdal = c("COMPRESS=DEFLATE")
)
fn <- paste0(aoi, "_Cov_stack_AOI2.tif")
if (file.exists(fn)) file.remove(fn)
gdalUtilities::gdalwarp(
srcfile = paste0(aoi, "_Cov_stack_AOI.tif"),
dstfile = paste0(aoi, "_Cov_stack_AOI2.tif"),
te = c(bbox(gsoc2)),
tr = res(gsoc2),
r = "bilinear"
)
veg <- rast(paste0(aoi, "_Cov_stack_AOI2.tif"))
veg2 <- mask(veg, gsoc2)
writeRaster(veg2, filename = paste0(aoi, "_Cov_stack_AOI.tif"), gdal = c("COMPRESS=DEFLATE"), overwrite = TRUE)
# Landcover ----
# http://www.fao.org/geonetwork/srv/en/main.home?uuid=ba4526fd-cdbf-4028-a1bd-5a559c4bff38
aoi <- "CONUS"
gsoc2 <- rast(paste0(aoi, "_GSOCmap1.5.0.tif"))
lc <- rast("D:/geodata/land_use_land_cover/GlcShare_v10_Dominant/glc_shv10_DOM.Tif")
crs(lc) <- "+init=epsg:4326"
lc2 <- crop(lc, gsoc2) #)
lc2 <- resample(lc2, gsoc2, method = "ngb", datatype = "INT1S")
names(lc2) <- "LU"
writeRaster(lc2, filename = paste0(aoi, "_glc_shv10_DOM.tif"), overwrite = TRUE)
LU_AOI <- rast(paste0(aoi, "_glc_shv10_DOM.tif"))
# DR layer ----
dr <- (
LU_AOI == 2 | LU_AOI == 12| LU_AOI == 13) * 1.44 +
(LU_AOI == 4) * 0.25 +
(LU_AOI == 3 | LU_AOI == 5 | LU_AOI == 6 | LU_AOI == 8) * 0.67
names(dr) <- "DR"
writeRaster(dr, file = paste0(aoi, "_glc_shv10_DOM_DR.tif"), overwrite = TRUE)
# Stack layers ----
aoi <- "CONUS"
setwd("D:/geodata/project_data/gsp-gsocseq/CONUS")
## Spin up layers ----
vars <- c(SOC = paste0(aoi, "_GSOCmap1.5.0.tif"),
CLAY = paste0(aoi, "_gnatsgo_fy20_1km_clay_wt.tif"),
TEMP = paste0(aoi, "_Temp_Stack_81-00_TC.tif"),
PREC = paste0(aoi, "_Prec_Stack_81-00_TC.tif"),
PET = paste0(aoi, "_PET_Stack_81-00_TC.tif"),
DR = paste0(aoi, "_glc_shv10_DOM_DR.tif"),
LU = paste0(aoi, "_glc_shv10_DOM.tif"),
COV = paste0(aoi, "_Cov_stack_AOI.tif")
)
su_rs <- lapply(names(vars), function(x) {
r <- rast(vars[x])
n <- nlyr(r)
names(r) <- if (n > 1) {
paste0(x, "_", formatC(1:nlyr(r), width = 2, flag = "0"))
} else x
return(r)
})
su_rs <- rast(su_rs)
# writeRaster(su_rs, filename = "Stack_Set_SPIN_UP_AOI.tif", filetype = "GTiff", overwrite = TRUE)
su_df <- as.data.frame(su_rs, xy = TRUE, cells = TRUE, na.rm = FALSE)
su_df <- su_df[
as.character(su_df$LU) %in% c(2, 3, 5, 12, 13)
& complete.cases(su_df),
]
su_sf <- st_as_sf(
su_df,
coords = c("x", "y"),
crs = 4326
)
saveRDS(su_df, file = paste0(aoi, "_su_df.RDS"))
saveRDS(su_sf, file = paste0(aoi, "_su_sf.RDS"))
test <- st_make_grid(su_sf)
test <- test[76]
su_sub <- crop(su_rs, vect(test))
saveRDS(test, "tile_crop.rds")
# writeRaster(su_sub, filename = "Stack_Set_SPIN_UP_AOI.tif", filetype = "GTiff", overwrite = TRUE)
# subset for testing
set.seed(42)
idx <- sample(1:nrow(su_df), 20000)
su_df <- su_df[idx, ]
su_sf <- su_sf[idx, ]
saveRDS(su_df, file = "su_df.RDS")
saveRDS(su_sf, file = "su_sf.RDS")
# set.seed(42)
# su_sf_sub <- su_sf[sample(1:nrow(su_sf), 100000), ]
# saveRDS(su_sf_sub, file = paste0(aoi, "_su_sf.RDS"))
## Warm up layers ----
su_sf <- readRDS(file = paste0(aoi, "_su_sf.RDS"))
n_wu <- 18
vars <- c(SOC = paste0(aoi, "_GSOCmap1.5.0.tif"),
CLAY = paste0(aoi, "_gnatsgo_fy20_1km_clay_wt.tif"),
COV = paste0(aoi, "_Cov_stack_AOI.tif"),
LU = paste0(aoi, "_glc_shv10_DOM.tif"),
DR = paste0(aoi, "_glc_shv10_DOM_DR.tif"),
TEMP = paste0(aoi, "_Temp_Stack_228_01-19_TC.tif"),
PREC = paste0(aoi, "_Prec_Stack_228_01-19_TC.tif"),
PET = paste0(aoi, "_PET_Stack_228_01-19_TC.tif"),
NPP = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI.tif"),
NPP_MIN = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI_MIN.tif"),
NPP_MAX = paste0(aoi, "_NPP_MIAMI_MEAN_81-00_AOI_MAX.tif")
)
# LU <- stack(replicate(n_wu, raster("CONUS_glc_shv10_DOM.tif")))
wu_rs <- rast(vars)
# wu_sub <- crop(wu_rs[[1:16]], vect(test))
# writeRaster(wu_sub[[1:16]], filename = "Stack_Set_WARM_UP_AOI.tif", filetype = "GTiff", overwrite = TRUE)
### partition points (if too large) ----
su_sf$id <- 1:nrow(su_sf)
su_sf$idx <- as.integer(
cut(su_sf$id,
breaks = quantile(su_sf$id, p = seq(0, 1, 0.1)),
include.lowest = TRUE)
)
test <- lapply(1:10, function(x) {
cat("extracting part", x, as.character(Sys.time()), "\n")
su_sf_sub <- su_sf[which(su_sf$idx == x), ]
temp <- vect(su_sf_sub)
# temp <- su_pts[1:100, ]
wu_ex <- extract(wu_rs, temp, xy = TRUE, cells = TRUE)
# wu_ex <- as.data.frame(extract(wu_rs, temp, sp = TRUE))
wu_ex <- cbind(id = su_sf_sub$id,
idx = x,
su_cell = su_sf_sub$cell,
wu_ex
)
saveRDS(wu_ex, file = paste0("CONUS_", x, "_wu_df.rds"))
})
# f_p <- paste0("CONUS_", 1:10, "_wu_df.rds")
#
# wu_pts_p1 <- lapply(f_p[1:5], function(x){
# temp <- readRDS(file = x)
# })
# wu_pts_p1 <- data.table::rbindlist(wu_pts_p1)
# data.table::fwrite(wu_pts_p1, file = "wu_pts_p1.csv")
#
#
# wu_pts_p2 <- lapply(f_p[6:10], function(x) {
# temp <- readRDS(file = x)
# })
# wu_pts_p2 <- data.table::rbindlist(wu_pts_p2)
# data.table::fwrite(wu_pts_p2, file = "wu_pts_p2.csv")
#
#
# wu_pts_p1 <- data.table::fread(file = "wu_pts_p1.csv")
# wu_pts_p2 <- data.table::fread(file = "wu_pts_p2.csv")
# wu_pts <- rbind(wu_pts_p1, wu_pts_p2)
# data.table::fwrite(wu_pts, file = "wu_pts.csv")
### don't partition points (if # of points is small) ----
su_v <- vect(su_sf)
wu_ex <- extract(wu_rs, su_v, xy = TRUE, cells = TRUE)
saveRDS(wu_ex, file = paste0(aoi, "_wu_df.rds"))
# tiles <- st_as_sf(st_make_grid(aoi, n = c(6, 6)))
# tiles$tile <- 1:nrow(tiles)
#
# # iterate over tiles and extract points
# test <- lapply(1:34, function(x) {
#
# cat("cropping ", x, as.character(Sys.time()), "\n")
#
# # crop raster stack
# tiles_sub <- vect(tiles[tiles$tile == x, ])
# # tiles_sub <- as(tiles[tiles$tile == x, ], "Spatial")
# rs_sub <- crop(wu_rs, tiles_sub)
#
# # mask non-ag landuses
# LU <- c(2, 3, 5, 12)
# rs_sub$CONUS_glc_shv10_DOM[! rs_sub$CONUS_glc_shv10_DOM %in% LU] <- NA
#
# # extract points
# lu_pts <- as.points(rs_sub$CONUS_glc_shv10_DOM)
# wu_pts <- extract(rs_sub, lu_pts, xy = TRUE)
#
# # save points
# saveRDS(wu_pts, file = paste0("wu_pts_tile_", x, "_v2.rds"))
#
# return(dim(wu_pts))
# })
#
#
# f_p1 <- paste0("wu_pts_tile_", 1:21, "_v2.rds")
# f_p2 <- paste0("wu_pts_tile_", 22:34, "_v2.rds")
#
# wu_pts_p1 <- lapply(f_p1, function(x){
# temp <- readRDS(file = x)
# temp <- temp[complete.cases(temp), ]
# })
# # saveRDS(do.call("rbind", wu_pts_p1), file = "wu_pts_v2_part1.rds")
# wu_pts_p2 <- lapply(f_p2, function(x){
# temp <- readRDS(file = x)
# temp <- temp[complete.cases(temp), ]
# })
# # saveRDS(do.call("rbind", wu_pts_p2), file = "wu_pts_v2_part2.rds")
# # file.remove(f)
## Forward Run ----
aoi <- "CONUS"
su_sf <- readRDS(file = paste0(aoi, "_su_sf.RDS"))
vars <- c(SOC = paste0(aoi, "_GSOCmap1.5.0.tif"),
CLAY = paste0(aoi, "_gnatsgo_fy20_1km_clay_wt.tif"),
TEMP = paste0(aoi, "_Temp_Stack_01-19_TC.tif"),
PREC = paste0(aoi, "_Prec_Stack_01-19_TC.tif"),
PET = paste0(aoi, "_PET_Stack_01-19_TC.tif"),
DR = paste0(aoi, "_glc_shv10_DOM_DR.tif"),
LU = paste0(aoi, "_glc_shv10_DOM.tif"),
COV = paste0(aoi, "_Cov_stack_AOI.tif")
)
fr_rs <- lapply(names(vars), function(x) {
r <- rast(vars[x])
n <- nlyr(r)
names(r) <- if (n > 1) {
paste0(x, "_", formatC(1:nlyr(r), width = 2, flag = "0"))
} else x
return(r)
})
fr_rs <- rast(fr_rs)
# writeRaster(fr_rs, filename = "Stack_Set_FOWARD.tif", filetype = "GTiff", overwrite = TRUE)
su_v <- vect(su_sf)
fr_df <- extract(fr_rs, su_v, xy = TRUE, cells = TRUE)
saveRDS(fr_df, file = paste0(aoi, "_fr_df.RDS"))
## AK ----
su_ak1 <- readRDS("AK1_su_df.RDS")
su_ak2 <- readRDS("AK2_su_df.RDS")
wu_ak1 <- readRDS("AK1_wu_df.rds")
wu_ak2 <- readRDS("AK2_wu_df.rds")
fr_ak1 <- readRDS("AK1_fr_df.rds")
fr_ak2 <- readRDS("AK2_fr_df.rds")
su_ak <- rbind(
cbind(aoi = "AK1", su_ak1),
cbind(aoi = "AK2", su_ak2)
)
saveRDS(su_ak, file = "su_df.RDS")
wu_ak <- rbind(
cbind(aoi = "AK1", wu_ak1),
cbind(aoi = "AK2", wu_ak2)
)
saveRDS(wu_ak, file = "wu_df.RDS")
data.table::fwrite(wu_ak, file = "wu_df.csv")
fr_ak <- rbind(
cbind(aoi = "AK1", fr_ak1),
cbind(aoi = "AK2", fr_ak2)
)
saveRDS(fr_ak, file = "fr_df.RDS")
# inspect outputs
write_sf(test2, dsn = "test.gpkg", driver = "GPKG", overwrite = TRUE)
gdalUtilities::gdal_rasterize(
src_datasource = "test.gpkg",
a = "CLAY",
dst_filename = "test_clay.tif",
of = "GTiff",
te = bbox(gsoc),
tr = res(gsoc),
co = c("COMPRESS=DEFLATE"),
a_srs = "EPSG:4326",
a_nodata = -999
)
# Define Target Points ----
pts <- raster("CONUS_glc_shv10_DOM.tif")
pts <- rasterToPoints(pts, spatial = TRUE)
pts$CONUS_glc_shv10_DOM <- as.character(pts$CONUS_glc_shv10_DOM)
pts <- subset(pts, CONUS_glc_shv10_DOM %in% c(2, 3, 5, 12))
table(pts$CONUS_glc_shv10_DOM)
pts <- as(pts, 'SpatialPoints')
write_sf(st_as_sfc(pts), dsn = "target_points.shp")