raster

I have a matrix(raster) that I am computing the the mean of each row in this raster as: library (raster) r <- raster(nrows=10, ncols=10);r <- setValues(r, 1:ncell(r)) extent(r) = extent(c(xmn=-180,xmx=180,ymn=-90,ymx=90)) stepsize = (r@extent@ymax - r@extent@ymin) / r@nrows yvals = seq(r@extent@ymax - stepsize / 2, r@extent@ymin, -stepsize) The x-values will be the mean of each row in the raster: xvals = rowMeans(as.matrix(r)) plot(xvals, yvals) What I need is to know how many values were considered when computing the mean for each row (N)? Some pixels may have NA so the number of values will

I am trying to calculate the closest distance between locations in the ocean and points on land but not going through a coastline. Ultimately, I want to create a distance to land-features map. This map was created using rdist.earth and is a straight line distance. Therefore it is not always correct because it not taking into account the curvatures of the coastline. c<-matrix(coast_lonlat[,1], 332, 316, byrow=T) image(1:316, 1:332, t(c)) min_dist2_feature<-NULL for(q in 1:nrow(coast_lonlat)){ diff_lonlat <- rdist.earth(matrix(coast_lonlat[q,2:3],1,2),as.matrix(feature[,1:2]), miles = F) min

I want to create a visualization of a matrix for some academic work. I decided to go about this by having the pixels in the image correspond to the values in the matrix. I created the nice small png that follows: When properly scaled up, you get a very reasonable image: This is a screenshot from within inkscape. However, when export this as a pdf, both evince and chrome do a terrible job at upscaling what should be very trivial, and instead I get something that looks like: The pdf itself seems to scale appropriately well for printing, but unfortunately I do a lot of my editing without printing

I have a raster, obtained from a netcdf which is in (Lambert Conic Conformal projection): library(meteoForecast) wrf_temporary <- getRaster("temp", day = Sys.Date(), frames = 'complete', resolution = 36, service = "meteogalicia") wrf_temporary extent : -18, 4230, -18, 3726 (xmin, xmax, ymin, ymax) coord. ref. : +proj=lcc +lat_1=43 +lat_2=43 +lat_0=34.82300186157227 +lon_0=-14.10000038146973 +x_0=536402.34 +y_0=-18558.61 +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +units=km +no_defs Now I want to transform that wrf_temporary raster to "+proj=longlat +datum=WGS84" (lat long degree). What to do? I want

I need to calculate the centroids of a set of spatial zones based on a separate population grid dataset. Grateful for a steer on how to achieve this for the example below. Thanks in advance. require(raster) require(spdep) require(maptools) dat <- raster(volcano) # simulated population data polys <- readShapePoly(system.file("etc/shapes/columbus.shp",package="spdep")[1]) # set consistent coordinate ref. systems and bounding boxes proj4string(dat) <- proj4string(polys) <- CRS("+proj=longlat +datum=NAD27") extent(dat) <- extent(polys) # illustration plot plot(dat, asp = TRUE) plot(polys, add =

I have an image and i want to plot only 100*100 square with left hand bottom corner at 0,0. when i use below commands. Why do i get a white space around my cropped image? how can i avoid it and ensure that I get exact 100*100 image? If you want to repeat my example, you can use any image on line 1 (provided that the image is bigger than 100*100 pixels) r <- raster("C:/Users/nnnn/Desktop/geo.jpg") vector= getValues(r) plot(r) r par(mar=c(0,0,0,0)) par(oma=c(0,0,0,0)) par(mai=c(0,0,0,0)) par(omi=c(0,0,0,0)) plot(r,xlim=c(0,100),ylim=c(0,100),legend=FALSE,axes=FALSE) Aspect ratios are normally

I have several large rasters that I want to process in a PCA (to produce summary rasters). I have seen several examples whereby people seem to be simply calling prcomp or princomp. However, when I do this, I get the following error message: Error in as.vector(data): no method for coercing this S4 class to a vector Example code: files<-list.files() # a set of rasters layers<-stack(files) # using the raster package pca<-prcomp(layers) I have tried using a raster brick instead of stack but that doesn't seem to the issue. What method do I need to provide the command so that it can convert the