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hres_scale_ecoregion.R
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# this script builds on hres_scale_repeat.R but uses ecoregion and no impact area
# here we changed
# 1. remove lia mask (comented sections)
# 2. use ecoregion instead of biome
# 3. ensure all tiles covered
require(raster)
require(gdalUtils)
library(doParallel)
# number sample points to extract
N <- 100000
Nclust <- 10
download <- TRUE
wd <- "/media/hdd1/globTree"
# OPTION
rasterOptions(tmpdir = paste0(wd, "/tmp"))
# input filepaths (relative to wd)
soc_file <- "./input/henglSoils2mSum.tif"
# impact_file="./input/Low_Impact_MASK.tif_ll.tif"
# ecoreg_file = "./input/ecoreg.shp"
eco_reg_file <- "./input/ecoreg.shp"
agb_list <- "./input/Aboveground_live_woody_biomass_density.csv"
hansen_list <- "./input/getfiles.txt"
# number of paralele clusters
myclusters <- Nclust
cl <- makeCluster(myclusters) # 4 cores
registerDoParallel(cl)
# dirs
outDir <- "./output"
setwd(wd)
# ==============================================================================
# Read files
# ==============================================================================
# Hengl250m global t/Ha
soilC <- raster(soc_file)
# global very low impact areas mask at 1k
# vlia = raster(impact_file)
# Read global ecoregs
ecoregs <- shapefile(eco_reg_file)
dat <- read.csv(agb_list)
ntiles <- dim(dat)[1]
ntiles_seq <- 1:ntiles
# tile=1
foreach(tile = ntiles_seq) %dopar% {
startT1 <- Sys.time()
setwd(wd)
# check if file exists, rest of script in this loop
if (!file.exists(paste0("./logs/endTile_", tile))) {
write(1, file = paste0("./logs/startTile_", tile))
require(raster)
require(gdalUtils)
# ==============================================================================
# AGB
# ==============================================================================
print(tile)
# Establish grid (AGB covers only land so we get this first
dat <- read.csv(agb_list)
file2get <- dat$download[tile] # this url wrong!
fileName <- unlist(strsplit(as.character(file2get), "/"))[8]
# destfile = paste0("data/" , fileName, "_1km.tif")
position <- unlist(strsplit(as.character(fileName), "_t"))[1]
# url actually has form:
# http://gfw2-data.s3.amazonaws.com/climate/WHRC_biomass/WHRC_V4/Processed/80N_010E_t_aboveground_biomass_ha_2000.tif
# construct URL
# file2get = paste0("http://gfw2-data.s3.amazonaws.com/climate/WHRC_biomass/WHRC_V4/Processed/",position,"_t_aboveground_biomass_ha_2000.tif")
# file2get <- fileName
# fileName = unlist(strsplit(as.character(file2get), "/"))[8]
# ==============================================================================
# Download AGB
# ==============================================================================
dl_file <- paste0("./downloads/", fileName)
if (!file.exists(dl_file)) {
tryCatch(
expr = {
system(paste0("wget -q -O ./downloads/", fileName, " ", file2get))
message("success itertion ", tile)
},
error = function(e) {
message("* Caught an error on itertion ", tile)
print(e)
},
warning = function(w) {
print("got a warning")
},
finally = {
print("do not need finally bit")
}
)
}
AGB <- raster(paste0("./downloads/", fileName))
# ==============================================================================
# Download hansen
# ==============================================================================
dat <- read.csv(hansen_list, header = F)
id <- which(dat$V1 == dat$V1[grep(position, dat$V1)])
file2get <- dat$V1[id]
fileName <- unlist(strsplit(as.character(file2get), "/"))[6]
dl_file <- paste0("./downloads/", fileName)
if (!file.exists(dl_file)) {
system(paste0("wget -q -O ./downloads/", fileName, " ", file2get))
}
hansen <- raster(paste0("./downloads/", fileName))
# ==============================================================================
# HRES - tile loop (scales)
# ==============================================================================
# ntiles=length(AGB_list)
# for (tile in 1:ntiles){ # scale tghis as parallel jobs
# print(paste0("running tile ", tile))
# AGB= raster(paste0(wd,AGB_list[[tile]]))
# hansen=raster(paste0(wd,hansen_list[[tile]]))
# ===============================================================================
# Resample hengl250 -> hengl30
# ===============================================================================
startT <- Sys.time()
# rough crop to hansen tile
soil_crop <- crop(soilC, hansen, snap = "out")
## dissag to hansen res
# FACT = res(soil_crop)/res(hansen)
# soil_dis = disaggregate(soil_crop, fact = FACT)
## more accurate crop
# soil_crop = crop(soil_dis, hansen)
## resample to hansen
# writeRaster(soil_crop, paste0("./processing/soil_crop",tile,".tif"),overwrite=TRUE)
# myfile=paste0("./processing/soil_crop",tile,".tif")
# R2 = hansen
# Routput=paste0(myfile,"RESAMP",tile,".tif")
# t1 <- c(xmin(R2), ymin(R2), xmax(R2), ymax(R2))
# t2 <- c(res(R2)[1], res(R2)[2])
# gdalwarp(myfile, dstfile = Routput, tr = t2, te = t1, output_Raster = T, overwrite = T, verbose = T) #, co="COMPRESS=LZW" makes much smaller file but takes loads longer
## can rm big file after converted
# hengl30 = raster(paste0( myfile,"RESAMP",tile,".tif"))
# extent(hengl30)==extent(hansen)
# extent(AGB)==extent(hansen)
endT1 <- Sys.time() - startT
# ===============================================================================
# Resample VLIA1l1km -> vlia30
# ===============================================================================
# rough crop to hansen tile
# vlia_crop = crop(vlia, hansen, snap="out")
## dissag to hansen res
# FACT = res(vlia_crop)/res(hansen)
# vlia_dis = disaggregate(vlia_crop, fact = FACT)
## more accurate crop
# vlia_crop = crop(vlia_dis, hansen)
## resample to hansen
# writeRaster(vlia_crop, paste0("./processing/vlia_crop",tile,".tif"), overwrite=TRUE)
# myfile=paste0("./processing/vlia_crop",tile,".tif")
# R2 = hansen
# Routput=paste0(myfile,"RESAMP",tile,".tif")
# t1 <- c(xmin(R2), ymin(R2), xmax(R2), ymax(R2))
# t2 <- c(res(R2)[1], res(R2)[2])
# gdalwarp(myfile, dstfile = Routput, tr = t2, te = t1, output_Raster = T, overwrite = T, verbose = T) #, co="COMPRESS=LZW" makes much smaller file but takes loads longer
# vlia30 = raster(paste0(myfile,"RESAMP",tile,".tif"))
# ==============================================================================
# Mask layers by vlia
# ==============================================================================
# mask hansen by vlia
# hansen_vlia =hansen*vlia30
# writeRaster(hansen_vlia,paste0("./processing/hansen_mask",tile,".tif"),overwrite=T)
## mask AGB by vlia
# AGB_vlia =AGB*vlia30
# writeRaster(AGB_vlia,paste0("./processing/AGB_mask",tile,".tif"),overwrite=T)
## mask soc by vlia
# hengl30_vlia =hengl30*vlia30
# writeRaster(hengl30_vlia,paste0("./processing/hengl30_mask",tile,".tif"),overwrite=T)
# ==============================================================================
# *** Analysis starts here ***
# implemented on hpc /home/caduff/src/globTree/analysis
# ==============================================================================
# read in files
dir.create(outDir)
# hansen_vlia=raster(paste0("./processing/hansen_mask",tile,".tif"))
# AGB_vlia=raster(paste0("./processing/AGB_mask",tile,".tif"))
# hengl30_vlia=raster(paste0("./processing/hengl30_mask",tile,".tif"))
ecoreg <- crop(ecoregs, hansen)
# parallel code
# cl <- makeCluster(myclusters) # 4 cores
# registerDoParallel(cl)
allmyecoreg <- as.vector(unique(ecoreg$ECO_NAME)) # all ecoregs in grid
# allmyecoreg=c(1,7)
# foreach(myecoreg=allmyecoreg) %dopar% {
for (myecoreg in allmyecoreg) {
regID <- unique(ecoreg$ECO_ID[ecoreg$ECO_NAME == myecoreg])
startT <- Sys.time()
myrast <- AGB
n <- length(unlist(strsplit(myrast@file@name, "/")))
print(myecoreg)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
if (!file.exists(paste0(outDir, "/", name, "_", myecoreg, ".txt"))) {
z <- ecoreg[ecoreg$ECO_NAME == myecoreg, ]
x <- spsample(z, n = N, type = "random")
data <- extract(myrast, x)
# mean(data, na.rm=T)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
write.table(data, paste0(outDir, "/AGB_tile", tile, "_eco", regID, ".txt"), row.names = FALSE)
} else {
print(paste(paste0(outDir, "/", name, "_", myecoreg, ".txt"), "exists!"))
}
endT2 <- Sys.time() - startT
startT <- Sys.time()
myrast <- soil_crop # hengl30
# myrast=hengl30
print(myecoreg)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
if (!file.exists(paste0(outDir, "/", name, "_", myecoreg, ".txt"))) {
z <- ecoreg[ecoreg$ECO_NAME == myecoreg, ]
x <- spsample(z, n = N, type = "random")
data <- extract(myrast, x)
# mean(data, na.rm=T)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
write.table(data, paste0(outDir, "/SOC_tile", tile, "_eco", regID, ".txt"), row.names = FALSE)
} else {
print(paste(paste0(outDir, "/", name, "_", myecoreg, ".txt"), "exists!"))
}
endT3 <- Sys.time() - startT
startT <- Sys.time()
myrast <- hansen
print(myecoreg)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
if (!file.exists(paste0(outDir, "/", name, "_", myecoreg, ".txt"))) {
z <- ecoreg[ecoreg$ECO_NAME == myecoreg, ]
x <- spsample(z, n = N, type = "random")
data <- extract(myrast, x)
# mean(data, na.rm=T)
name <- strsplit(unlist(strsplit(myrast@file@name, "/"))[n], ".tif")
write.table(data, paste0(outDir, "/CANOPY_tile", tile, "_eco", regID, ".txt"), row.names = FALSE)
} else {
print(paste(paste0(outDir, "/", name, "_", myecoreg, ".txt"), "exists!"))
}
endT4 <- Sys.time() - startT
}
# clean up
# system(paste0("rm ",wd,"/processing/soil_crop",tile, ".tif"))
# system(paste0("rm ",wd,"/processing/soil_crop",tile, ".tifRESAMP",tile,".tif"))
write(1, file = paste0("./logs/endTile_", tile))
} # end of if file exists condition
if (file.exists(paste0("./logs/endTile_", tile))) {
print(paste("tile", tile, "already computed!"))
}
} # end parallel
endT5 <- Sys.time() - startT1