raster

I was working with spatial data to get ready for analyses - I have a DEM at the desired extent of my study area, though I have ~39 other layers at the national scale (US). Is there a way to crop all of these 39 layers to the same extent as the DEM at once? Also, I will be overlaying the output with other layers in a different projection. Is it possible to adjust the projection and pixel size of the output layers? I am trying to use freeware as much as possible for my data manipulation... I had the problem above, but have written a function in R to do all of this in a batch - see below. I had

Really simple problem with the raster package, also using ncdf4 to load in an ECMWF Era-Interim Netcdf file. Simply doing this: a <- nc_open("SSTs.nc") B <- brick(a, varname="sst") Returns this: Error in (function (classes, fdef, mtable) : unable to find an inherited method for function ‘brick’ for signature ‘"ncdf4"’ The file is just SST data over the whole globe, for 1 month (Jan2016). When I convert it into an array (i.e. extract dimensions/variable, and convert time to UTC, shove it into an array) I don't get the same error, but the raster package says it supports .nc files straight in (so

Im wondering if someone has built a raster of the continents of the world where each cell equals the distance of that cell cell to the nearest shore. This map would highlight the land areas that are most isolated inland. I would imagine this would simply rasterize a shapefile of the global boundaries and then calculate the distances. You can do this with raster::distance , which calculates the distance from each NA cell to the closest non- NA cell. You just need to create a raster that has NA for land pixels, and some other value for non-land pixels. Here's how: library(raster) library

Given raster object r , how can I create a new raster with the same extent and resolution, with cell values equal to the latitude (or longitude) of the corresponding cell in r ? For example, r might look like: r <- raster(matrix(runif(100), ncol=10)) If your question is about create a new raster object which has the same extent and resolution of another raster object you can use command template template is Raster* or Extent object used to set the extent (and CRS in case of a Raster* object). If not NULL, arguments xmn, xmx, ymn, ymx and crs (unless template is an Extent object) are ignored r

I am trying to simply subtract two rasters and save the result in another raster. One of the input images is a tif-file, the other is a vrt-file. (Output is tif) The files are very big, so I open them, divide them into tiles and run through each of them and then subtracting. The problem is that it is extremely slow! import gdal import numpy as np rA = gdal.Open(raFileName) rB = gdal.Open(rbFileName) nodataA = rA.GetRasterBand(1).GetNoDataValue() nodataB = rB.GetRasterBand(1).GetNoDataValue() raster = gdal.GetDriverByName('GTiff').Create(outputFileName, ncols, nrows, 1 ,gdal.GDT_Float32,[

I'm wondering if I have maximized the speed at which a mean of an area buffered around a point in a raster can be extracted. Can performance be improved any further on these LOCALLY? I use parallel mclapply already, and I know I could get further gains by setting up and running this on a cluster (use a cluster or get more cpu's is not the answer I'm looking for). Replicate some data: library(raster) library(parallel) library(truncnorm) library(gdalUtils) library(velox) library(sf) ras <- raster(ncol=1000, nrow=1000, xmn=2001476, xmx=11519096, ymn=9087279, ymx=17080719) ras[]=rtruncnorm(n=ncell

Is there a way to check if a file has raster elements in it? I would be interested to do this for the .pdf, .eps and .ai formats. If the file is only vector I am converting it to .svg and if it has some raster elements I have to convert it to .png file. I am working in PHP but I can utilize any command line tools as well. For instance I am considering using Inkscape to do the actual conversion. No there is not. The following is a theoretical computer science proof for eps which proofs, that the asked property can not be computed. PostScript(ps) and also Encapsulated PostScript(eps) are turing