3
我的以下问题建立在这个帖子上提出@jbaums解决方案:Global Raster of geographic distances如何基于网格细胞子集栅格值
为了再现例子的目的,我有距离到的栅格数据集最近的海岸线:
library(rasterVis); library(raster); library(maptools)
data(wrld_simpl)
# Create a raster template for rasterizing the polys.
r <- raster(xmn=-180, xmx=180, ymn=-90, ymx=90, res=1)
# Rasterize and set land pixels to NA
r2 <- rasterize(wrld_simpl, r, 1)
r3 <- mask(is.na(r2), r2, maskvalue=1, updatevalue=NA)
# Calculate distance to nearest non-NA pixel
d <- distance(r3) # if claculating distances on land instead of ocean: d <- distance(r3)
# Optionally set non-land pixels to NA (otherwise values are "distance to non-land")
d <- d*r2
levelplot(d/1000, margin=FALSE, at=seq(0, maxValue(d)/1000, length=100),colorkey=list(height=0.6), main='Distance to coast (km)')
的数据是这样的:
从这里,我需要子集距离栅格(d),或创建一个新的光栅,仅包含细胞距离海岸线不到200公里。我试图使用getValues()来确定值为< = 200(如下所示)的单元格,但目前为止没有成功。谁能帮忙?我在正确的轨道上吗?
#vector of desired cell numbers
my.pts <- which(getValues(d) <= 200)
# create raster the same size as d filled with NAs
bar <- raster(ncols=ncol(d), nrows=nrow(d), res=res(d))
bar[] <- NA
# replace the values with those in d
bar[my.pts] <- d[my.pts]
太棒了!有用。谢谢@Ouistiti! – fabfab