r-raster

问题 I am wondering how I can draw an image of the population proportion (pop.prop) at these locations (x and y) so that I can see the population distribution clearly? The data is shown below: pts.pr = pts.cent[pts.cent$PIDS==3, ] pop = rnorm(nrow(pts.pr), 0, 1) pop.prop = exp(pop)/sum(exp(pop)) pts.pr.data = as.data.frame(cbind(pts.pr@coords, cbind(pop.prop))) x y pop.prop 3633 106.3077 38.90931 0.070022855 3634 106.8077 38.90931 0.012173106 3756 106.3077 38.40931 0.039693085 3878 105.8077 37

问题 I am having trouble reproducing my results exactly when I make predictions with predict() and a saved gbm model object. I am using the raster package to predict to a raster. Each time I run predict() with the same model object and inputs (a raster stack), I get slightly different values (max value within 0.7 for a range of predictions from 0.08 to 12.30 for example). However, there seems to be a limited amount of outcomes. For example, I can get the results to reproduce if I run predict

问题 library(raster) r <- raster('glc2000_v1_1') # http://forobs.jrc.ec.europa.eu/products/glc2000/products/glc2000_v1_1_Grid.zip extent(r) # class : Extent # xmin : -180.0045 # xmax : 179.9955 # ymin : -56.01339 # ymax : 89.99554 ext <- extent(-69,-63,-3,3) r1 <- crop(r,ext) #Warning message: #In .getRat(x, ratvalues, ratnames, rattypes) : NAs introduced by coercion If I try to crop a smaller area, it works fine. ext <- extent(-68,-64,-2,2) r1 <- crop(r,ext) # works fine This error is preventing

问题 To whom this may concern: Here is the source code: GRA_D1<- raster(files[[1]]) //Sets up an empty output raster: GRA_D1<- writeStart(GRA_D1,filename='GRA_D1.tif', format='GTiff', overwrite=TRUE) //Write to the raster, for loop: for(i in 1:dim(GRA_D1)[1]){ //Extract raster values at rows d.Frame<- matrix(NA,ncol=2,nrow=dim(GRA_D1)[2]) d.Frame[,1]<- getValues(r1[[1]],i) d.Frame[,2]<- getValues(r1[[2]],i) w.Frame<- as.data.frame(d.Frame) names(w.Frame)<- c("D1_pred_disAg","D1_pred_RK") //Apply

问题 I have a function that reads a multi-band image in as a raster brick object, iterates through the bands doing various calculations, and then writes the raster out as a new .tif. All of this works fine, but the file size of the new image file is roughly four times greater (I assume because the original image has 4 bands). I'm wondering if there's a parameter in the writeRaster() function that I'm unaware of, or if there's some other way I can ensure that the output image is basically the same

问题 With the raster below, with an increased number of NA values library(raster) filename <- system.file("external/test.grd", package="raster") r <- raster(filename) r[r<300] <- NA summary(getValues(r)) is it possible to 'fill in' only the NA cells? I have been using this helpful post but as seen below, NA values remain in the final product. fill.na <- function(x, i=5) { if( is.na(x)[i] ) { return( round(mean(x, na.rm=TRUE),0) ) } else { return( round(x[i],0) ) } } r2 <- focal(r, w = matrix(1,3,3

问题 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

问题 I am trying to figure our the proportion of an area that has a slope of 0, +/- 5 degrees. Another way of saying it is anything above 5 degrees and below 5 degrees are bad. I am trying to find the actual number, and a graphic. To achieve this I turned to R and using the Raster package. Let's use a generic country, in this case, the Philippines {list.of.packages <- c("sp","raster","rasterVis","maptools","rgeos") new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,

问题 I am attempting to aggregate daily data (35 years) to monthly then calculate seasonal mean using the raster package in R (I know how to do it with CDO). Below is my code, which outputs 4 seasonal means for all years (140 layers). How can I loop to output only 4 layers ( for the 4 seasons)?. I appreciate your help. dailydata <- brick ("dailyrain.nc") dates <- seq(as.Date("1981-01-01"), as.Date("2015-12-31"), by="day") months <- format(dates, "%Y-%m") Aggregate2Monthly <- function(x) { agg <-

问题 I have a Spatialline that I converted from a polygon shapefile (digitized manually based on features in "imagebrick" - this means that spatially the "polyline" and "imagebrick" are overlapped as I wanted) polyline <- as(shapefiles_data[1,],"SpatialLines") > polyline class : SpatialLines features : 1 extent : 357714.3, 357719, 4076030, 4076035 (xmin, xmax, ymin, ymax) coord. ref. : +proj=utm +zone=11 +datum=NAD27 +units=m +no_defs +ellps=clrk66 +nadgrids=@conus,@alaska,@ntv2_0.gsb,@ntv1_can