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3a_comparison.R
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rm(list=ls())
machine = "leca"
# machine = "luke"
# machine = "froggy"
## LOAD R packages
if (machine == "luke")
{
.libPaths("/bettik/emabio/R_PKG_NIX/")
} else if (machine == "froggy")
{
.libPaths("/home/mayagueguen/R_PKG_NIX/")
}
library(raster)
library(rgdal)
## DEFINE paths to data and to SAGA executable file
if (machine == "leca")
{
# path.to.data = "C:/Users/gueguen/Documents/CLIMATE_DOWNSCALING/"
# path.to.SAGA = "C:/Program Files (x86)/SAGA-GIS/"
# path.to.data = "/media/gueguen/equipes/macroeco/GIS_DATA/CHELSA_DOWNSCALING/"
# path.to.data = "K:/LECA/macroeco/GIS_DATA/CHELSA_DOWNSCALING/"
# path.to.data = "/home/gueguen/Bureau/CHELSA_DOWNSCALING/"
path.to.data = "/run/user/30241/gvfs/smb-share:server=129.88.191.70,share=equipes/macroeco/GIS_DATA/CHELSA_DOWNSCALING/"
} else if (machine == "luke")
{
path.to.data = "/bettik/mayagueguen/CHELSA_DOWNSCALING/"
} else if (machine == "froggy")
{
path.to.data = "/scratch/mayagueguen/CHELSA_DOWNSCALING/"
}
path.to.SAGA = path.to.data
# path.to.SAGA = "C:/Users/renaud/Downloads/saga-7.2.0_x64/"
setwd(path.to.data)
zone_name.clouds = "World" ## DO NOT CHANGE !
zone_name.tempCHELSA = "World" ## DO NOT CHANGE !
zone_name.tempERA = "World" ## DO NOT CHANGE !
zone_name.GMTED = "FID30"
proj.res.clouds = 6000 ## DO NOT CHANGE !
proj.res.tempCHELSA = 4000 ## DO NOT CHANGE !
proj.res.tempERA = "100000" ## DO NOT CHANGE !
proj.res.GMTED = 310 ## DO NOT CHANGE !
# zone_name = "Bauges"
# DEM_name = "DEM/RAW/DEM_Bauges.img"
# zone_name = "Lautaret"
# DEM_name = "DEM/RAW/DEM_Lautaret.img"
zone_name = "Alps"
DEM_name = "DEM/RAW/DEM_Alps_ETRS89_resolution25.img"
# zone_name = "FrenchAlps"
# DEM_name = "DEM/RAW/DEM_FrenchAlps.img"
DEM_ras = raster(DEM_name)
proj.res = unique(res(DEM_ras))[1]
proj.name = "Mercator"
proj.value = "+proj=merc +lon_0=0 +k=1 +x_0=0 +y_0=0 +ellps=WGS84 +datum=WGS84 +units=m +no_defs "
setwd(path.to.SAGA)
# system("export SAGA_MLB=/home/gueguen/Documents/_SOFTWARES/SAGA_LST_Dirk/Release/")
###################################################################
### CREATE PATHWAYS and FILENAMES
###################################################################
zone.file.name = paste0(zone_name, "_", proj.name, "_resolution", proj.res)
zone.folder.name = paste0(zone.file.name, "/")
###################################################################
### LAND SURFACE TEMPERATURE computation
###################################################################
### WITH MAP VALUES
new.folder.name = paste0(zone_name, "_", proj.name,"_resolution", proj.res, "/")
lst.folder.name = paste0("LAND_SURFACE_TEMPERATURE/", zone_name, "_", proj.name,"_resolution", proj.res, "/")
library(foreach)
library(viridis)
# library(doParallel)
# registerDoParallel(cores = 8)
combi = expand.grid(mm = 1:12, i = 1:3)
cairo_pdf("COMPARISON_Chelsa_LST.pdf", width = 8.5, height = 7.7)
COR = foreach (mm = combi$mm, i = combi$i, .combine = "rbind") %do%
{
cat("\n ==> Calculate ", c("MIN","MEAN","MAX")[i], " Land Surface Temperature for month ", mm, "\n")
## Temperature REF (CHELSA)
input.name.temp = paste0("TEMP_", c("MIN","MEAN","MAX")[i], "_", zone.file.name, "_", mm, ".sdat")
input.name.temp = paste0("TEMPERATURE/", new.folder.name, input.name.temp)
input.name.temp.ori = paste0("CHELSA_", c("tmin", "temp", "tmax")[i], "10_", mm, "_1979-2013_V1.2_land.tif")
input.name.temp.ori = paste0("TEMPERATURE/RAW/", input.name.temp.ori)
## Land Surface Temperature
output.name = paste0("LST_", c("MIN_","MEAN_","MAX_")[i], zone.file.name, "_", mm, ".sdat")
output.name = paste0(lst.folder.name, output.name)
##
TEMP.ori = raster(input.name.temp.ori) ## ~ 1000m - world - long/lat
TEMP = raster(input.name.temp) ## 25m - alps - mercator
LST = raster(output.name) ## 25m - alps - mercator
##
no.pix = 500
##
TEMP.tmp1 = crop(TEMP, extent(TEMP, 9961, 11000, 34961, 36000)) ## 25m - crop - mercator
new_extent = projectExtent(TEMP.tmp1, crs = CRS(projection(TEMP.ori)))
TEMP.ori = crop(TEMP.ori, extent(new_extent)) ## ~ 1000m - crop - long/lat
TEMP.tmp0 = projectRaster(TEMP.ori, res = 1000, crs = CRS(projection(TEMP.tmp1))) ## 1000m - crop - mercator
TEMP.tmp0 = TEMP.tmp0 / 10
TEMP.tmp0 = crop(TEMP.tmp0, extent(TEMP.tmp0, 4, 29, 4, 29))
LST.tmp1 = crop(LST, extent(LST, 9961, 11000, 34961, 36000)) ## 25m - crop - mercator
LST.tmp2 = aggregate(LST.tmp1, fact = 40, fun = mean) ## 1000m - crop - mercator
##
PIX = sample(1:ncell(TEMP.tmp1), no.pix)
XY = xyFromCell(TEMP.tmp1, PIX)
PIX_TEMP_ori = TEMP.tmp0[cellFromXY(TEMP.tmp0, XY)]
PIX_TEMP = TEMP.tmp1[PIX]
PIX_LST = LST.tmp1[PIX]
PIX_LST_agg = LST.tmp2[cellFromXY(LST.tmp2, XY)]
##
PIX_agg = sample(1:ncell(LST.tmp2), no.pix)
LST.tmp3 = LST.tmp2 ## 1000m - crop - mercator
LST.tmp3[] = NA
LST.tmp3[PIX_agg] = PIX_agg
LST.tmp3 = disaggregate(LST.tmp3, fact = 40) ## 25m - crop - mercator
zon.cv = zonal(LST.tmp1, LST.tmp3, fun = 'cv')
zon.sd = zonal(LST.tmp1, LST.tmp3, fun = 'sd')
##
MIN = min(c(min(TEMP.tmp0[], na.rm = TRUE)
, min(TEMP.tmp1[], na.rm = TRUE)
, min(LST.tmp1[], na.rm = TRUE)
, min(LST.tmp2[], na.rm = TRUE)))
MAX = max(c(max(TEMP.tmp0[], na.rm = TRUE)
, max(TEMP.tmp1[], na.rm = TRUE)
, max(LST.tmp1[], na.rm = TRUE)
, max(LST.tmp2[], na.rm = TRUE)))
par(mfrow = c(3,2), mar = c(2, 2, 4, 0))
plot(TEMP.tmp0
, zlim = c(MIN, MAX)
, box = FALSE
, axes = FALSE
, col = viridis(100)
, main = "1000 m"
, legend.width = 2
, legend.mar = 10
)
plot(TEMP.tmp1
, zlim = c(MIN, MAX)
, box = FALSE
, axes = FALSE
, col = viridis(100)
, main = "25 m"
, legend = FALSE
)
plot(LST.tmp2
, zlim = c(MIN, MAX)
, box = FALSE
, axes = FALSE
, col = viridis(100)
, legend.width = 2
, legend.mar = 10
)
plot(LST.tmp1
, zlim = c(MIN, MAX)
, box = FALSE
, axes = FALSE
, col = viridis(100)
, legend = FALSE
)
mtext(text = paste0(c("MIN","MEAN","MAX")[i], " - "
, c("January", "February", "March", "April"
, "May", "June", "July", "August",
"September", "October", "November", "December")[mm])
, side = 3, line = -2, at = 0.46, font = 2, outer = TRUE)
mtext(text = "CHELSA", side = 2, line = -5, at = 0.82, font = 2, outer = TRUE)
mtext(text = "LST", side = 2, line = -5, at = 0.485, font = 2, outer = TRUE)
mtext(text = "<---->", side = 2, line = -13.5, at = 0.65, col = "orange", font = 2, outer = TRUE)
mtext(text = "<---->", side = 4, line = -18, at = 0.65, col = "darkblue", font = 2, outer = TRUE)
mtext(text = "------------------------------------------>", side = 3, line = -6, at = 0.46, outer = TRUE)
mtext(text = "<-------------", side = 4, line = -14, at = 0.65, outer = TRUE)
mtext(text = "<------------------------------------------", side = 1, line = -23, at = 0.46, outer = TRUE)
plot(PIX_TEMP, PIX_LST
, col = "darkblue", pch = 20
, xlim = c(MIN, MAX), ylim = c(MIN, MAX)
, xlab = "CHELSA", ylab = "LST")
points(PIX_TEMP_ori, PIX_LST_agg, col = "orange", pch = 20)
abline(v = 0, h = 0, lty = 2)
abline(lm(PIX_LST ~ PIX_TEMP), lty = 1, lwd = 2, col = "darkblue")
abline(lm(PIX_LST_agg ~ PIX_TEMP_ori), lty = 1, lwd = 2, col = "orange")
legend("topleft"
, legend = c("CHELSA (25m) ~ LST (25m)", "CHELSA (1km) ~ LST (1km)")
, col = c("darkblue", "orange")
, pch = 15
, bty = 'n')
hist(zon.sd[,2], breaks = 1000, main = "Standard deviation\n LST (25m) values within 1000m pixel\n (degrees)")
##
corr1 = cor.test(PIX_TEMP, PIX_LST)
corr2 = cor.test(PIX_TEMP, PIX_LST_agg)
corr3 = cor.test(PIX_TEMP_ori, PIX_LST_agg)
##
return(data.frame(MONTH = mm
, STAT = c("MIN","MEAN","MAX")[i]
, P_VALUE_1 = corr1$p.value
, COR_1 = corr1$estimate
, P_VALUE_2 = corr2$p.value
, COR_2 = corr2$estimate
, P_VALUE_3 = corr3$p.value
, COR_3 = corr3$estimate
))
}
dev.off()
save(COR, file = "COR.RData")
par(mfrow = c(1,1))
plot(COR[, c(4,6,8)], col = c("darkblue", "darkgreen", "orange"))
library(reshape2)
tmp = melt(COR[, c(2,4,6,8)])
tmp = tmp[which(tmp$variable %in% c("COR_1", "COR_3")), ]
boxplot(value ~ variable * STAT, tmp)
# plot(COR$COR_1, COR$COR_2, col = "coral", pch = 20
# , xlim = range(COR$COR_1), ylim = range(COR[, c(6,8)]))
# points(COR$COR_1, COR$COR_3, col = "brown", pch = 20)
# abline(a = 0, b = 1, lty = 2, lwd = 2, col = "brown")