Francisco Rodriguez-Sanchez 2017-05-16
library(knitr)
opts_chunk$set(cache = TRUE, message = FALSE)
library(raster)library(rgis)sp.extent <- c(-10, 5, 35, 44)tile1 <- getData('worldclim', download = TRUE, var = 'prec', res = 0.5,
lon = -5, lat = 36)
tile2 <- getData('worldclim', download = TRUE, var = 'prec', res = 0.5,
lon = 0, lat = 36)
wc1 <- merge(tile1, tile2)
worldclim1 <- sum(wc1)
worldclim1 <- crop(worldclim1, sp.extent)
#plot(worldclim1)pmonth <- stack(unzip("C:/Users/FRS/Dropbox/GIS.layers/WORLDCLIM/v2/Present/wc2.0_30s_prec.zip", exdir = tempdir())[-13])
pmonth <- crop(pmonth, sp.extent)
worldclim2 <- sum(pmonth)
#plot(worldclim2)atlas <- raster(ungzip("C:/Users/FRS/Dropbox/GIS.layers/AtlasClimaticoDigitalPenIb/pluvio_anual.nc.gz", ext = "gz"))
atlas.geo <- projectRaster(atlas, worldclim1)
atlas.geo <- atlas.geo/10
#plot(atlas.geo)locs <- cbind(x = c(-5.3541, -2.9125, -5.0875, -5.8625, -8.1458, -1.7875, -8.6541),
y = c(36.6958, 37.8375, 40.1958, 40.07916, 40.04583, 43.2208, 42.6791))
P.worldclimv1.4 <- worldclim1[cellFromXY(worldclim1, locs)]
P.worldclimv2 <- worldclim2[cellFromXY(worldclim2, locs)]
P.atlas <- atlas.geo[cellFromXY(atlas.geo, locs)]
knitr::kable(data.frame(locs, P.worldclimv1.4, P.worldclimv2, P.atlas), digits = c(4,4,0,0,0))| x | y | P.worldclimv1.4 | P.worldclimv2 | P.atlas |
|---|---|---|---|---|
| -5.3541 | 36.6958 | 824 | 796 | 1237 |
| -2.9125 | 37.8375 | 539 | 509 | 1046 |
| -5.0875 | 40.1958 | 366 | 377 | 1259 |
| -5.8625 | 40.0792 | 599 | 814 | 1216 |
| -8.1458 | 40.0458 | 1203 | 1228 | 1877 |
| -1.7875 | 43.2208 | 1346 | 1330 | 2512 |
| -8.6541 | 42.6791 | 1240 | 1480 | 1966 |
compar <- stack(worldclim1, worldclim2, atlas.geo)
names(compar) <- c("Worldclimv1.4", "Worldclimv2", "IberianAtlas")
locs.sp <- as.data.frame(locs)
coordinates(locs.sp) <- c("x", "y")
proj4string(locs.sp) <- projection(worldclim2)
library(rasterVis)
levelplot(compar, par.settings = viridisTheme, main = "Annual Precipitation") +
layer(sp.points(locs.sp, pch = 1, col = "red", cex = 2))