raster

问题 I'm trying to find the mean daily temperature for counties in South Dakota from raster grids ('bil' files) found at http://prism.oregonstate.edu/. I am getting county boundaries from the 'maps' package. library(maps) library(raster) sd_counties <- map('county','south dakota') sd_raster <- raster('file_path') How do I extract the grid cells within each county? I think I need to turn each county into it's own polygon to do this, but how? Then, I should be able to do something like the following

问题 I hope you can help me. I have been trying to import multiple raster datasets into R, recode missing values for each raster data imported, link them to zipcodes and then export each raster data as a csv file with different names. I am trying to use a loop but so far I have only got errors. This is as far as I have gotten (dont laugh): import all 24 raster datasets file_names=as.list(dir(pattern="home.*")) listy<-lapply(file_names,raster, band=1) names(listy) <- paste0("hour", seq_along(0:23))

问题 Related to my previous question about calculate atan2 from two raster object in R?. It's possible to create a vector plot where the speed (slope) and direction (aspect) is displayed with a set of arrows (e.g. quiver in Matlab) based on this equation: for speed : ws <- sqrt(u^2+v^2) for direction : wd <- (180/pi)*(atan2(u,v)) my dataset sample can be downloaded here u <- raster(flname, varname = 'U') v <- raster(flname, varname = 'V') uv <- stack(u,v) I used rasterVis package to figure the

问题 How do i reconstruct the image from an array of data in javascript. And display it on my page. the data is not hex or binary but a color value [0-255] black and white, so 8 bits image. Could some one give me show direction on how to rebuild the image from such raster data. I refer native javascript image object. here is a simple snippet of the data. IMAGE {"data":[[9,6,7,7,8,8,8,8,8,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,10,10,9,9,10,9,9,10,9,10,10,10,10,9,9,9,9,9,10,9,9,10,9,10,9,9,9,10,9,9,10,9

问题 I have been using the extract function from the raster package to extract data from raster files using an area defined by shapefiles. However, I am having problems with the amount of memory that this process is now requiring. I do have a large number of shapefiles (~1000). The raster files are large (~1.6gb) My process is: shp <- mclapply(list.files(pattern="*.shp",full.names=TRUE), readShapePoly,mc.cores=6) ndvi <- raster("NDVI.dat") mc<- function(y) { temp <- gUnionCascaded(y) extract <-

问题 If have three rasters(as matrix): r1 <- raster(nrows=10, ncols=10); r1 <- setValues(r1, 1:ncell(r1)) r16 <- raster(nrows=10, ncols=10);r16 <- setValues(r16, 1:ncell(r16)) r30 <- raster(nrows=10, ncols=10);r30 <- setValues(r30, 1:ncell(r30)) I would like to linearly interpolate r1,c16,c30 to find the values in between i.e. r2,r3,r4,......r15 then r17,r18,r19,..........r29 . Is this possible using R? 回答1: Here is a way to do that library(raster) r <- raster(nrows=10, ncols=10); values(r) <- NA

问题 I've created Kernel home ranges from gps locations using the tool kernelUD from the package(adehabitatHR) using the code: 'udKerHref <- kernelUD(data[,1],h = "href", grid=100, kern = c("bivnorm"))' where data is a SpatialPointsDataFrame from 10 animals. I would now like to do two things: create a raster from the Kernel density values which I can multiply with another raster (Resource selection function raster) intersect other gps locations not used for building the home range with the raster

问题 I have a function that calculates a price based on the input slope and distance. I want to write the price to a raster as the rastervalue. How do I do that? OpenSource and ArcMap solutions would work. slopeRaster = "slope.tif" emptyRaster = "emptyraster.tif" # How do I create an empty raster? road = "road.shp" for cell in emptyraster: # get slope from sloperaster at cell location ... slope = ... # get distance to nearest road from center of cell ... distance = ... # calculate price for cell

问题 I need to compute number of three consecutive days when value of each pixel in a raster stack ( x ) is above a given threshold (defined by another raster y ). I tried using rle for the purpose with calc as follows after stacking x and y together into new raster a : library(raster) fn<-function(a) with(rle(a), sum(lengths>=3 & values>a[[nlayers(a)]])) calc(b,fn) However, I am getting the error: Error in .calcTest(x[1:5], fun, na.rm, forcefun, forceapply) : cannot use this function Reproducible

问题 I am stuck on the Energy Balance calculation of the water package. The example code I am following is at this website https://cran.r-project.org/web/packages/water/vignettes/Landsat8.html. I am using my own data and am able to read both my original landsat image and the surface reflectance image with my area of interests (aoi). I get the following error when I use this code. Energy.Balance <- METRIC.EB(image.DN = image, image.SR = image.SR, plain=TRUE, aoi=aoi, n = 5, WeatherStation =