基于栅格层网格单元数差异的子集 R 栅格堆栈

Question

当上一层和下一层之间的差异都是NA时，我想创建光栅堆栈的子集并将它们写为新堆栈。 即，从第 1 层开始，我想创建光栅堆栈的子集，直到前一层和下一层之间没有重叠像素（即，两层之间的差异都是NA ）所以我想要的是； 从第 1 层开始，保留前一层和下一层之间至少有 1 个公共像素的所有层，将它们写为 1 堆栈，然后移动到下一层。 以下是示例数据和不成功的 for 循环。 在这个例子中，我想保留 1:8 层，命名并编写它们，然后从第 9 层重新开始，依此类推。

r <- raster(ncol=5, nrow=5)
set.seed(0)
#create raster layers with some values 
s <- stack(lapply(1:8, function(i) setValues(r, runif(ncell(r)))))
s1<-extend(s,c(-500,100,-400,100))

#to recreate the condition I am looking for, create 2 layers with `NA` vlaues
s2 <- stack(lapply(1:2, function(i) setValues(r, runif(ncell(r)))))
s1e<-extend(s2,c(-500,100,-400,100))
s1e[]<-NA

#Stack the layers
r_stk<-stack(s1,s1e)
plot(r_stk)

#here is the sample code showing what i am expecting here but could not get

required_rst_lst<-list() # sample list of raster layers with overlapping pixels I am hoping to create
for ( i in 1: nlayers(r_stk))
  # i<-1
  lr1<-subset(r_stk,i)
lr1
lr2<-subset(r_stk,i+1)
lr2
diff_lr<-lr1-lr2  
plot(diff_lr)

if ((sum(!is.na(getValues(diff_lr)))) ==0)) #??

required_rst_lst[[i]] #?? I want layers 1: 8 in this list 
#because the difference in these layers in not NA

Answer 1

像这样的东西可能对你有用。

您的示例数据

library(raster)
r <- raster(ncol=5, nrow=5)
set.seed(0)
s <- stack(lapply(1:8, function(i) setValues(r, runif(ncell(r)))))
s1 <- extend(s,c(-500,100,-400,100))

s2 <- stack(lapply(1:2, function(i) setValues(r, runif(ncell(r)))))
s1e <- extend(s2,c(-500,100,-400,100))
values(s1e) <- NA 
r_stk <- stack(s1,s1e)

解决方案：

out <- lst <- list()
nc <- ncell(r_stk)   
for (i in 1:nlayers(r_stk)) {
    if (i==1) {
        j <- 1
        s <- r_stk[[i]]
    } else {
        s <- s + r_stk[[i]]
    }
    if (freq(s, value=NA) == nc) {
        ii <- max(j, i-1)   
        out <- c(out, r_stk[[j:ii]])
        s <- r_stk[[i]]
        j <- i
    }
}
out <- c(out, r_stk[[j:i]])
out

#[[1]]
#class      : RasterStack 
#dimensions : 14, 9, 126, 8  (nrow, ncol, ncell, nlayers)
#resolution : 72, 36  (x, y)
#extent     : -468, 180, -414, 90  (xmin, xmax, ymin, ymax)
#crs        : +proj=longlat +datum=WGS84 +no_defs 
#names      :  layer.1.1,  layer.2.1,    layer.3,    layer.4,    layer.5,    layer.6,    layer.7,    layer.8 
#min values : 0.06178627, 0.01339033, 0.07067905, 0.05893438, 0.01307758, 0.03554058, 0.06380848, 0.10087313 
#max values :  0.9919061,  0.8696908,  0.9128759,  0.9606180,  0.9926841,  0.9850952,  0.8950941,  0.9437248 
#
#[[2]]
#class      : RasterLayer 
#dimensions : 14, 9, 126  (nrow, ncol, ncell)
#resolution : 72, 36  (x, y)
#extent     : -468, 180, -414, 90  (xmin, xmax, ymin, ymax)
#crs        : +proj=longlat +datum=WGS84 +no_defs 
#source     : memory
#names      : layer.1.2 
#values     : NA, NA  (min, max)
#
#[[3]]
#class      : RasterLayer 
#dimensions : 14, 9, 126  (nrow, ncol, ncell)
#resolution : 72, 36  (x, y)
#extent     : -468, 180, -414, 90  (xmin, xmax, ymin, ymax)
#crs        : +proj=longlat +datum=WGS84 +no_defs 
#source     : memory
#names      : layer.2.2 
#values     : NA, NA  (min, max)