I have more than 50 raster files (ASCII format) that I need to crop. I already exported the mask from ArcMap in ASCII format as well and loaded it into R. How can I make it work for all rasters in a row and export them with the same name as before (of course in a different folder to not overwrite)?
I know there is a crop function in the raster package, but I never used it so far. I only stacked them for further habitat analysis.
My Code so far:
#### Use only part of area
files2 <- list.files(path="D:/",full.names=TRUE, pattern = "\\.asc$")
files2
# Create a RasterLayer from first file
mask_raster <- raster(files2[1])
# Crop. But how??
crop(x = , y=mask_raster)
writeRaster(...)`
I did not find an easy solution to crop multiple rasters by a raster, but by a shape file. So I just went back to ArcMap and converted the raster into a shapefile. Then in R, crop and mask were the crucial steps. See code below (modified from Mauricio Zambrano-Bigiarini's code). Hope this helps.
# Reading the shapefile (mask to crop later)
Maskshp <- readOGR("mask.shp")
# Getting the spatial extent of the shapefile
e <- extent(Maskshp)
# for loop with (in this case) 60 runs
for (i in 1:60) {
# Reading the raster to crop
files <- list.files(path="...your path",full.names=TRUE, pattern = "\\.asc$")
Env_raster <- raster(files[i])
# Save the filename
filename <- (paste(basename(files[i]), sep=""))
# Crop the raster
Env_raster.crop <- crop(Env_raster, e, snap="out")
# Dummy raster with a spatial extension equal to the cropped raster,
# but full of NA values
crop <- setValues(Env_raster.crop, NA)
# Rasterize the catchment boundaries, with NA outside the catchment boundaries
Maskshp.r <- rasterize(Maskshp, crop)
# Putting NA values in all the raster cells outside the shapefile boundaries
Maskshp.masked <- mask(x=Env_raster.crop, mask=Maskshp.r)
plot(Maskshp.masked)
#Export file to working directory with original name as new name
writeRaster(Maskshp.masked, filename)
}
Related
I'm processing yearly multilayer netCDF files with daily precipitation data from CHIRPS. I have the files for the whole world, each file about 1.2gb large. I need to calculate indices from the precipitation data for each cell in the raster for a specific region. In order to do that I'm trying to crop the files to get a rectangular shape above my area of interest using the raster R package.
This is the code I'm using, exemplary for the first file.
library(ncdf4)
library(raster)
library(rgdal)
# Crop extent
crop_extent <- as(raster::extent(79, 89, 25, 31), "SpatialPolygons")
proj4string(crop_extent) <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
# Set directory with original files
setwd("~/data")
# Read file
chirps81 <- stack("chirps-v2.0.1981.days_p05.nc")
chirps81crop <-crop(chirps1981, crop_extent)
# Write cropped file back to different folder
setwd("~/croppeddata")
writeRaster(chirps81crop, "chirps81crop.nc", overwrite=TRUE)
For some reason however while writing the file the layers lose their name. In the original files and after cropping the names have layer names of the format "X1981.01.01". But after writing and reading the netCDF file with new file <- stack("chirps81crop.nc") the layer names are changed to the format 'X1' up to 'X365'. I think it should be fine working with it, assuming that the order of the layers didn't get mixed up but I don't understand what is happening to the layer names and if this happens because there is something wrong with the code.
It's the writeRaster() function that is losing the layer names, not the crop operation. It is possible to use lower level ncdf functions to assign a numeric value (not a string unfortunately) to each layer which will then show up in the name of the layers after reading. Taking inspiration from the example here, I created some code that shows this.
library(ncdf4)
library(raster)
library(rgdal)
# Crop extent
crop_extent <- as(raster::extent(5.74, 5.75, 50.96, 50.97), "SpatialPolygons")
proj4string(crop_extent) <- "+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs"
# make a sample file
r <- raster(system.file("external/test.grd", package="raster"))
r.latlon <- projectRaster(r, crs = proj4string(crop_extent))
writeRaster(x=r.latlon, filename = 'test.nc', format = 'CDF', overwrite=TRUE)
# read the sample as a 2 layer stack and crop it
test <- stack('test.nc', 'test.nc')
writeRaster(test, 'teststack.nc', overwrite=TRUE, format='CDF')
testcrop <- crop(test, crop_extent)
names(testcrop)
# [1] "test.1" "test.2"
# write the cropped file and make the zname equal to Layer
writeRaster(testcrop, 'testcrop.nc', overwrite=TRUE, format='CDF', zname='Layer')
# open the cdf file directly
nc <- nc_open('testcrop.nc', write = T)
# give the layers numbers starting from 10 so
# we can see them easily
layers = 1:nlayers(testcrop) + 10
layers
# [1] 11 12
ncvar_put(nc, 'Layer', layers)
nc_close(nc)
newtestcrop <- stack('testcrop.nc')
names(newtestcrop)
# [1] "X11" "X12"
nc <- nc_open('testcrop.nc', write = F)
layers = ncvar_get(nc, 'Layer')
layers
# [1] 11 12
nc_close(nc)
So it is possible to get names with numbers under your control when writing the raster, but I don't know enough about your environment to determine if this will help since it might be tricky to map the names you need to a single unambiguous number.
I hope you don't mind me offering a non-R solution, but this task is much easier from the command line using CDO:
cdo sellonlatbox,79,89,25,31 chirps-v2.0.1981.days_p05.nc cropped_file.nc
Which indices did you want to calculate? I suspect it is possible to calculate those quickly and easily with CDO functions too...
How do I loop through all rasters (TIFF) in a folder and extract values using a point shapefile which has several coordinates then have the output as a dataframe?
library(raster)
library(rgdal)
files <- list.files(path=".", pattern="tif$", full.names=TRUE) # select all the tiff files in the directory
s <- stack(files) # stack all of them using r raster library
shp <- shapefile("points.shp") # read the point shape file
ext <- extract(s, shp) # extract the values from raster stack.
I'd like to crop GeoTiff Raster Files using the two mentioned packages, "rgdal" and "raster". Everything works fine, except that the quality of the resulting output tif is very poor and in greyscale rather than colour. The original data are high quality raster maps from the swiss federal office of Topography, example files can be downloaded here.
This is my code:
## install.packages("rgdal")
## install.packages("raster")
library("rgdal")
library("raster")
tobecroped <- raster("C:/files/krel_1129_2012_254dpi_LZW.tif")
ex <- raster(xmn=648000, xmx=649000, ymn=224000, ymx=225000)
projection(ex) <- proj4string(tobecroped)
output <- "c:/files/output.tif"
crop(x = tobecroped, y = ex, filename = output)
In order to reproduce this example, download the sample data and extract it to the folder "c:/files/". Oddly enough, using the sample data the quality of the croped image is alright, but still greyscale.
I played around using the options "datatype", "format", but didnt get anywhere with that. Can anybody point out a solution? Should I supply more information the the input data?
EDIT:
Josh's example works superb with the sample data 2. Unfortunately, the data I have seems to be older and somewhat different. Can you tell me what option I choose if you read the following GDALinfo:
# packages same as above
OldInFile = "C:/files/krel1111.tif"
dataType(raster(OldInFile)
[1] "INT1U"
GDALinfo(OldInFile)
rows 4800
columns 7000
bands 1
lower left origin.x 672500
lower left origin.y 230000
res.x 2.5
res.y 2.5
ysign -1
oblique.x 0
oblique.y 0
driver GTiff
projection +proj=somerc +lat_0=46.95240555555556 +lon_0=7.439583333333333+k_0=1 +x_0=600000+y_0=200000 +ellps=bessel +units=m+no_defs
file C:/files/krel1111.tif
apparent band summary:
GDType hasNoDataValue NoDataValue blockSize1 blockSize2
1 Byte FALSE 0 1 7000
apparent band statistics:
Bmin Bmax Bmean Bsd
1 0 255 NA NA
Metadata:
AREA_OR_POINT=Area
TIFFTAG_RESOLUTIONUNIT=2 (pixels/inch)
TIFFTAG_XRESOLUTION=254
TIFFTAG_YRESOLUTION=254
Warning message:
statistics not supported by this driver
Edit (2015-03-10):
If one simply wants to crop out a subset of an existing GeoTIFF and save the cropped part to a new *.tif file, using gdalUtils::gdal_translate() may be the most straightforward solution:
library(raster) # For extent(), xmin(), ymax(), et al.
library(gdalUtils) # For gdal_translate()
inFile <- "C:/files/krel_1129_2012_254dpi_LZW.tif"
outFile <- "subset.tif"
ex <- extent(c(686040.1, 689715.9, 238156.3, 241774.2))
gdal_translate(inFile, outFile,
projwin=c(xmin(ex), ymax(ex), xmax(ex), ymin(ex)))
Looks like you need to change two details.
First, the *.tif file you're reading in has three bands, so should be read in using stack(). (Using raster() on it will only read in a single band (the first one, by default) producing a monochromatic or 'greyscale' output).
Second (for reasons mentioned here) writeRaster() will by default write out the values as real numbers (Float64 on my machine). To explicitly tell it you instead want to use bytes, give it the argument datatype='INT1U'.
library("rgdal")
library("raster")
inFile <- "C:/files/krel_1129_2012_254dpi_LZW.tif"
outFile <- "out.tif"
## Have a look at the format of your input file to:
## (1) Learn that it contains three bands (so should be read in as a RasterStack)
## (2) Contains values written as Bytes (so you should write output with datatype='INT1U')
GDALinfo(inFile)
## Read in as three separate layers (red, green, blue)
s <- stack(inFile)
## Crop the RasterStack to the desired extent
ex <- raster(xmn=648000, xmx=649000, ymn=224000, ymx=225000)
projection(ex) <- proj4string(s)
s2 <- crop(s, ex)
## Write it out as a GTiff, using Bytes
writeRaster(s2, outFile, format="GTiff", datatype='INT1U', overwrite=TRUE)
All of which outputs the following tiff file:
I have about 40 spatial rasters in the .tiff format in a folder. I'm trying to generate histograms from each of the rasters in R, and save each histogram as a jpeg in a separate folder. I wrote code to loop through each of the raster, create a histogram and save it using the 'jpeg' package.
setwd("G:/Research/MODIS Albedo Oct 08-July 09/Test")
library(raster)
library(jpeg)
files <- list.files(path="G:/Research/MODIS Albedo Oct 08-July 09/Test", pattern=".tif",all.files=T, full.names=F, no.. = T) #generate a list of rasters in the folder
number<-length(files) #count the number of rasters
for(r in 1:number) #loop over each raster in the folder
{
x<-raster(files[r], header=F) #load one raster file
jpeg("G:/Research/MODIS Albedo Oct 08-July 09/test_histplots/r.jpg") #create jpeg using the name 'r' generated by loop
hist(x) #generate histogram
dev.off()
}
I want each of the generated jpeg to have a different name, ideally a subset of the original raster name. For example, if the original name of the raster is 'MODIS101_265', the jpeg's name should be 265. Here, 265 is the Julian date in the year. I'm assuming that this might involve using a format specifier like %d in C, but I'm not sure how this works in R.
When I run the above code, I get only one histogram. It seems the code is correctly looping over the original rasters, but saving all resultant histograms to a single jpeg.
Any advice will be helpful! Thanks!
Regular expression using gsub are your friend for getting the number out of the name. Assuming that all of your files are named the way your example is ("MODIS101_265.tif"), then the code below will work for you.
Also, welcome to R where for loops are slow and can usually be replaced by the faster lapply.
saveMyHist <- function(fileName) {
fileNum <- as.numeric(gsub(".*_(\\d+)\\.tif", "\\1", fileName))
x <- raster(fileName, header=F)
jpeg(sprintf("G:/Research/MODIS Albedo Oct 08-July 09/test_histplots/%03d.jpg",
fileNum))
hist(x)
dev.off()
}
files <- list.files("/Users/home/Documents/Development/Rtesting",
pattern=".tif",all.files=T, full.names=F, no.. = T)
lapply(files, saveMyHist)
I have a shape file with two different region with 12 sub region each.I want separate shape file of these 24 sub region from that shape file.I have also tried by using package maptools and rgeos but could not figure it.Any logarithm would be very much appreciated. Thanks.
sharif
You can split your data in a loop based on the unique value in the column of interest and write out the subset data. I am using rgdal in leu of maptools but you could easily change the code to use maptools functions for reading/writing shapefiles.
require(sp)
require(rgdal)
# READ SHAPEFILE
dat <- readOGR("C:/DATA", "dat")
# CREATE VECTOR OF UNIQUE SUBREGION VALUES
y <- unique(dat#data$SUBREGIONS)
# CREATE SHAPEFILE FOR EACH SUBREGION AND WRITE OUT
for (i in 1:length(y) ) {
temp <- dat[dat$SUBREGIONS == y[i], ]
writeOGR(temp, dsn=getwd(), y[i], driver="ESRI Shapefile",
overwrite_layer=TRUE)
}