从路径列表中分组/堆叠栅格并提取每个组的最小值

Question

我有一个栅格路径列表（qazxsw poi = 912栅格路径，912个栅格（19年）（12个月）（4周））如下：

rplist

我需要每月按月读取栅格组（例如属于RMI_2000_02的栅格），然后将每个叠加单元格的最小值作为单独的栅格提取（忽略NA值，如果有的话）。

  [1] "C:/Users/Eric/Downloads/Results/RMI_2000_02_18.tif"
  [2] "C:/Users/Eric/Downloads/Results/RMI_2000_02_26.tif"
  [3] "C:/Users/Eric/Downloads/Results/RMI_2000_03_05.tif"
  [4] "C:/Users/Eric/Downloads/Results/RMI_2000_03_13.tif"
  [5] "C:/Users/Eric/Downloads/Results/RMI_2000_03_21.tif"
  [...] "......"
  [912] "C:/Users/Eric/Downloads/Results/RMI_2019_03_21.tif"

从这里我不知道我可以用rs做什么（如上所述）但应该是：

################### SETTING UP WORKING DIRECTORY ############################
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))

# list rasters in workin directory
rplist <- list.files(getwd(),full.names = TRUE)

Answer 1

为了得到一个好的答案，你应该提供一些示例数据（不是外部文件，使用R附带的数据，或使用代码创建一些）。您可以做的是创建一个RasterStack

1. read rasters using rplist
2. group them by month for each year
3. extract the min raster

和一个矢量s，它将需要组合的图层分组，然后执行

v

现在有示例数据

x <- stackApply(s, v, fun=min, na.rm=TRUE)

Answer 2

一种方法如下：

library(raster)
# RasterStack with 12 layers
s <- stack(system.file("external/rlogo.grd", package="raster")) 
s <- stack(s, s*2, s*3, s*4)
# make one layer with only NAs
values(s[[2]]) <- NA

# 12 corresponding dates
d <- paste0("RMI_2000", rep(sprintf("_%02d", 1:3), each=4), "_0", 1:4)
d
# [1] "RMI_2000_01_01" "RMI_2000_01_02" "RMI_2000_01_03" "RMI_2000_01_04" "RMI_2000_02_01" "RMI_2000_02_02" "RMI_2000_02_03" "RMI_2000_02_04" "RMI_2000_03_01" "RMI_2000_03_02" "RMI_2000_03_03" "RMI_2000_03_04"


# transform date into an index (stripping of the label and the week number)
i <- substr(d, 4, 11)
i
#[1] "2000_01" "2000_01" "2000_01" "2000_01" "2000_02" "2000_02" "2000_02" "2000_02" "2000_03" "2000_03" "2000_03" "2000_03"


ss <- stackApply(s, i, min, na.rm=TRUE)
ss
#class       : RasterBrick 
#dimensions  : 77, 101, 7777, 3  (nrow, ncol, ncell, nlayers)
#resolution  : 1, 1  (x, y)
#extent      : 0, 101, 0, 77  (xmin, xmax, ymin, ymax)
#coord. ref. : +proj=merc +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
#data source : in memory
#names       : index_2000_01, index_2000_02, index_2000_03 
#min values  :             0,             0,             0 
#max values  :           255,           510,           765