R 如何同时在多个栅格图层中导出我的结果?

R How to export my results in multiple rasters layers at the same time?

作为第一步,我导入了一个 table,其中包含多个采样站的每日数据(请参见下面的示例)。 随后,我将要为每个日期(天)创建栅格图层,并稍后使用不同的名称导出这些栅格。 由于我有一个包含每日数据的长时间序列(40 年),我希望创建一个循环(请参阅下面的程序),但我不能为输出栅格指定不同的名称。所以每次他都把我压到上一层。 我是循环编程的新手,你能帮我解决这个问题吗?

提前致谢

data=read.table(file="data.csv", sep=";", header=TRUE)
head(data)
LAMBX   LAMBY   DATE    S
600 24010   20180801    15.3
600 24010   20180802    12
600 24010   20180803    15
600 24010   20180804    14.8
600 24010   20180805    16.8
600 24010   20180806    15.1
601 24011   20180801    11
601 24011   20180802    14
601 24011   20180803    16.8
601 24011   20180804    15.1
601 24011   20180805    13.8
601 24011   20180806    12.7
602 24012   20180801    15.3
602 24012   20180802    14
602 24012   20180803    12
602 24012   20180804    16.8
602 24012   20180805    17.5
602 24012   20180806    15.1


library(dplyr)
library(sp)
library(raster)
# for each date I will do the following manipulations
for (i in data[,"DATE"]) {
# to delimit my study area
  table=filter(data, DATE == i & LAMBX %in% 601:602 & LAMBY %in% 24011:24012) 
# convert geographic coordinates
  table[,c("LAMBX", "LAMBY")]= 100*table[,c("LAMBX", "LAMBY")]

# spatialize the stations
  xy <- table[,c("LAMBX", "LAMBY")]
  sptable <- SpatialPointsDataFrame(coords = xy, data = table,
                                 proj4string = CRS("+proj=lcc +lat_1=46.8 +lat_0=46.8 +lon_0=0 +k_0=0.99987742 +x_0=600000 +y_0=2200000 +a=6378249.2 +b=6356515 +towgs84=-168,-60,320,0,0,0,0 +pm=paris +units=m +no_defs"))

# rasterize my SpatialPointsDataFrame
  rsptable <- rasterFromXYZ(as.data.frame(sptable)[, c("LAMBX", "LAMBY","S")],  crs="+proj=lcc +lat_1=46.8 +lat_0=46.8 +lon_0=0 +k_0=0.99987742 +x_0=600000 +y_0=2200000 +a=6378249.2 +b=6356515 +towgs84=-168,-60,320,0,0,0,0 +pm=paris +units=m +no_defs")
  # export my rasters layers
  writeRaster(rsptable, filename="S_date.tif", format="GTiff", overwrite=TRUE)
}

我在您的数据中没有看到 T_Q 变量,因此我将改用 S。他们的技巧是创建一个空列表对象,在每次循环迭代时填充。然后您可以创建结果的 stack。堆栈的每一层都是一个单独的日期。

library(dplyr)
library(sp)
library(raster)

data <- read.table(text = "
LAMBX   LAMBY   DATE    S
600 24010   20180801    15.3
600 24010   20180802    12
600 24010   20180803    15
600 24010   20180804    14.8
600 24010   20180805    16.8
600 24010   20180806    15.1
601 24011   20180801    11
601 24011   20180802    14
601 24011   20180803    16.8
601 24011   20180804    15.1
601 24011   20180805    13.8
601 24011   20180806    12.7
602 24012   20180801    15.3
602 24012   20180802    14
602 24012   20180803    12
602 24012   20180804    16.8
602 24012   20180805    17.5
602 24012   20180806    15.1", header = TRUE)

crs_string <- "+proj=lcc +lat_1=46.8 +lat_0=46.8 +lon_0=0 +k_0=0.99987742 +x_0=600000 +y_0=2200000 +a=6378249.2 +b=6356515 +towgs84=-168,-60,320,0,0,0,0 +pm=paris +units=m +no_defs"

res <- list()
for (i in seq_along(unique(data[,"DATE"]))){
  table <- filter(data,
                  DATE == unique(data[,"DATE"])[i] &
                  LAMBX %in% 601:602 &
                  LAMBY %in% 24011:24012)
  table[,c("LAMBX", "LAMBY")] <-  100 * table[,c("LAMBX", "LAMBY")]

  xy       <- table[,c("LAMBX", "LAMBY")]
  sptable  <- SpatialPointsDataFrame(coords = xy, data = table,
                                    proj4string = CRS(crs_string))
  rsptable <- rasterFromXYZ(
    as.data.frame(sptable)[, c("LAMBX", "LAMBY","S")],  crs = crs_string)
  res[[i]] <- rsptable
}

res <- stack(res)
writeRaster(res, filename="S_date.tif", format="GTiff", overwrite=TRUE)