我想获取附近(例如,在x
米中的值(像素值),坐标(y
和status
)和属性(buffer=6
) )(随机栅格(pts
),使用栅格数据包中的提取功能。我尝试在data.frame
中组织结果,但没有成功。
library(raster)
#create some GeoTIFF rasters
r <- raster(ncol=10, nrow=10)
s <- stack(lapply(1:8, function(i) setValues(r, runif(ncell(r)))))
f1 <- file.path(tempdir(), "sl1.tif")
f2 <- file.path(tempdir(), "sl2.tif")
writeRaster(s[[1:4]], f1, overwrite=TRUE)
writeRaster(s[[5:8]], f2, overwrite=TRUE)
# 10 random points in the rasters
set.seed(5)
pts <- sampleRandom(s[[1]], 10, xy=TRUE)[,1:2]
status<-c(rep(c("A","B"),5))
pts<-as.data.frame(cbind(pts,status))
i<-c(1,2)
pts[ , i]<-apply(pts[ , i], 2,
function(x) as.numeric(as.character(x)))
#read all rasters
f <- c(f1, f2)
ras <- lapply(f, brick)
# extract raster values in 10 random coordinates and 6 meters around and organize the results
RES<-NULL
for(i in 1:length(ras)){
value <- raster::extract(ras[[i]],pts[,1:2], buffer=6)
RES<-rbind(RES,cbind(pts,coordinates(value),value)) #create a data frame of the results
}
RES
Error in data.frame(..., check.names = FALSE) :
arguments imply differing number of rows: 10, 4
我当然有不同数量的行!!我想创建一个最终数据帧,其输出具有随机坐标({{1}中的xy),邻点xy(6m缓冲区周围的x2和y2像素坐标),状态(重复pts
状态,我认为邻居的状态与父坐标pts
相同,并且每个图层的值都类似:
pts
答案 0 :(得分:1)
简化的示例数据(请勿在示例中写入磁盘!)
library(raster)
set.seed(5)
r <- raster(ncol=10, nrow=10, crs="+proj=utm +zone=1 +datum=WGS84", xmn=0, xmx=50, ymn=0, ymx=50)
s1 <- stack(lapply(1:4, function(i) setValues(r, runif(ncell(r)))))
s2 <- stack(lapply(1:4, function(i) setValues(r, runif(ncell(r)))))
ras <- list(s1, s2)
pts <- data.frame(pts=sampleRandom(s1, 10, xy=TRUE)[,1:2], status=rep(c("A","B"),5))
解决方案
查看改进的,更通用的版本 here
# get xy from buffer cells
cell <- extract(r, pts[,1:2], buffer=6, cellnumbers=T)
xy <- xyFromCell(r, do.call(rbind, cell)[,1])
res <- list()
for (i in 1:length(ras)) {
v <- raster::extract(ras[[i]], pts[,1:2], buffer=6)
# add point id
for (j in 1:length(v)) {
v[[j]] <- cbind(point=j, v[[j]])
}
#add layer id and xy
res[[i]] <- cbind(layer=i, xy, do.call(rbind, v))
}
res <- do.call(rbind, res)
添加原始点的坐标
pts$point <- 1:nrow(pts)
res <- merge(res, pts)
head(res)
# point layer x y layer.1 layer.2 layer.3 layer.4 pts.x pts.y status
#1 1 1 7.5 37.5 0.72070097 0.98188917 0.44275430 0.77354202 7.5 32.5 A
#2 1 1 2.5 32.5 0.44473056 0.36640641 0.78783480 0.25482562 7.5 32.5 A
#3 1 1 7.5 32.5 0.05936247 0.17737527 0.08365037 0.02629751 7.5 32.5 A
#4 1 1 12.5 32.5 0.27514918 0.01776222 0.05997353 0.48397076 7.5 32.5 A
#5 1 1 7.5 27.5 0.23519875 0.24867338 0.20373370 0.23957656 7.5 32.5 A
#6 1 2 2.5 32.5 0.33440265 0.98600510 0.94576856 0.85867224 7.5 32.5 A