你用的时候

rasterize

功能，重要的是指定

field

参数，否则默认会尝试为你创建一个;在您的情况下，它看起来像是从FID列创建的。

我做了一些猜测来重新生成一组可能与你的类似的工作多边形。

    
      library(maptools)
library(rgdal)
library(sp)
library(geosphere)
set seed for duplicatable results
set.seed(1)
some data that looks a little like yours
BINOMIAL <- c(“Controversial chimneyswift”, “Dull dungbeetle”,
“Easternmost eel”, “Jumping jaeger”, “Qualified queenconch”)
FID <- 0:(length(BINOMIAL) - 1)
RANGE <-  runif(length(BINOMIAL), min = 118, max = 3875370)
MyData <- cbind.data.frame(FID, BINOMIAL, RANGE)
row.names(MyData) <- FID
some semi-random polygons in your extent box
ext <- extent(c(-180, 180, -60, 90))
create_polygon <- function(n = 4, lat, lon, r) {
  lengths <- rnorm(n, r, r/3)
  smoother_lengths <- c(sort(lengths), rev(sort(lengths)))
  lengths <- smoother_lengths[sort(sample(n * 2, n))]
  lengths <- rep(lengths[1], length(lengths))
  directions <- sort(runif(n, 0, 360))
  p <- cbind(lon, lat)
  vertices <- t(mapply(destPoint, b = directions,
                       d = lengths, MoreArgs = list(p = p)))
  vertices <- rbind(vertices, vertices[1, ])
  sapply(vertices[,1], min, ext@xmax)
  sapply(vertices[,1], max, ext@xmin)
  sapply(vertices[,2], min, ext@ymax)
  sapply(vertices[,2], max, ext@ymin)
  Polygon(vertices)
}
rand_lats <- runif(nrow(MyData), min = -50, max = 60)
rand_lons <- runif(nrow(MyData), min = -100, max = 100)
rand_sides <- sample(4:20, nrow(MyData), replace = TRUE)
rand_sizes <- rnorm(nrow(MyData), mean = 5e+06, sd = 1e+06)
make_species_polygon <- function(i) {
  p.i <- list(create_polygon(rand_sides[i], rand_lats[i],
                             rand_lons[i], rand_sizes[i]))
  P.i <- Polygons(p.i, FID[i])
}
polys <- SpatialPolygons(lapply(1:nrow(MyData), make_species_polygon))
spdf <- SpatialPolygonsDataFrame(Sr = polys, data = MyData)
t.shp <- tempfile(pattern = “MyShapefile”, fileext = “.shp”)
raster::shapefile(spdf, t.shp)
</code>
  

    
  ## now we get into your code
library(raster)
library(rgdal)
library(maptools)
define porjection
projection1 <- CRS (“+proj=longlat +ellps=WGS84 +towgs84=0,0,0,0,0,0,0 +no_defs”)
 
I don’t know what your shapefile looks like exactly,
but substituting t.shp the tempfile that I created above
also since the function readShapePoly is deprecated
instead I use the recommended new function rgdal::readOGR()
 
sp <- rgdal::readOGR(t.shp)
#
I don’t know what your tiff file looks like exactly,
but I can duplicate its characteristics
for speed I have decreased resolution by a factor of 10
#
raster1 <- raster(nrow = 1800, ncol = 4320, ext)
rasterize our species polygon to the same resoluton of loaded raster
r.sp <- rasterize(x = sp, y = raster1, field = MyData$RANGE) 
t.tif <- tempfile(pattern = “MyRastfile”, fileext = “.tif”)
writeRaster(r.sp, t.tif, format = “GTiff”, overwrite = TRUE)
</code>
  

    
      raster(t.tif)
class       : RasterLayer
dimensions  : 1800, 4320, 7776000  (nrow, ncol, ncell)
resolution  : 0.08333333, 0.08333333  (x, y)
extent      : -180, 180, -60, 90  (xmin, xmax, ymin, ymax)
coord. ref. : NA
data source : [[“a file name in your temp directory”]]
names       : MyRastfile1034368f3cec
values      : 781686.3, 3519652  (min, max)
</code>