如何从具有不同范围和分辨率的 1 个栅格中减去 3 个栅格 [英] How to subtract 3 rasters from 1 raster with different extents and resolutions

问题描述

我有 4 个具有不同分辨率和范围的栅格.任何人都可以帮助我如何从栅格(d1)中减去 3 个栅格(a、b、c)以获得名为e"的新输出栅格

I have 4 rasters with different resolutions and extents. Can anyone help me how to subtract 3 rasters (a,b,c) from raster (d1) to get the new output raster named as "e"

就像 e= d1-a-b-c.`

like e= d1-a-b-c. `

d1
class      : RasterLayer 
dimensions : 180, 360, 64800  (nrow, ncol, ncell)
resolution : 1, 1  (x, y)
extent     : -1.110223e-16, 360, -90, 90  (xmin, xmax, ymin, ymax)
crs        : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
source     : memory
names      : Liquid_Water_Equivalent_Thickness 
values     : -249.2061, 806.3248  (min, max)

> a
class      : RasterLayer 
dimensions : 39, 46, 1794  (nrow, ncol, ncell)
resolution : 0.826087, 1.153846  (x, y)
extent     : 48, 86, 6, 51  (xmin, xmax, ymin, ymax)
crs        : +proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0 
source     : memory
names      : layer 
values     : 0, 0.4987984  (min, max)

> b
class      : RasterLayer 
dimensions : 39, 46, 1794  (nrow, ncol, ncell)
resolution : 0.826087, 1.153846  (x, y)
extent     : 48, 86, 6, 51  (xmin, xmax, ymin, ymax)
crs        : +proj=longlat +ellps=WGS84 +datum=WGS84 +towgs84=0,0,0 
source     : memory
names      : layer 
values     : 0, 555.5283  (min, max)

> c
class      : RasterLayer 
band       : 1  (of  4  bands)
dimensions : 46, 39, 1794  (nrow, ncol, ncell)
resolution : 1, 1  (x, y)
extent     : 47.5, 86.5, 5.5, 51.5  (xmin, xmax, ymin, ymax)
crs        : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
source     : D:/GLDAS Data/2002_GLDAS/GLDAS_NOAH10_M.A200201.001.grb.SUB.nc4 
names      : Average.layer.1.soil.moisture 
z-value    : 2 
zvar       : SoilMoist 
level      : 1

`

推荐答案

要做到这一点，您需要确保每个栅格的范围和分辨率相同，下面是我的代码，它制作了示例栅格和通过它们工作，使它们具有相同的范围和分辨率.这是带注释的代码:

To make this possible, you need to make sure the extents and the resolutions of every rasters are the same, here is my code below, which makes sample rasters and works through them to make them have the same extent and resolution. Here is the code with comments:

#### ----- Making Sample rasters ----- ####
e1 <- extent(-1.110223e-16, 360, -90, 90)
d1 <- raster(e1)
res(d1) <- 1
d1[] <- runif(64800, min = 0, max = 1)
#plot(d1)

e2 <- extent(48, 86, 6, 51)
a <- raster(e2)
res(a) <- c(0.826087, 1.153846)
a[] <- rnorm(1794, 5, 1)
#plot(a)

e3 <- extent(48, 86, 6, 51)
b <- raster(e3)
res(b) <- c(0.826087, 1.153846)
b[] <- rnorm(1794, 12, 1)

e3 <- extent(47.5, 86.5, 5.5, 51.5)
c <- raster(e3)
res(c) <- 1
c[] <- rnorm(1794, 12, 1)

crs(d1) = crs("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0")
crs(a) = crs("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0")
crs(b) = crs("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0")
crs(c) = crs("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0")
#### ----- Making Sample rasters ----- ####


##### Cropping all rasters to the lowest extent #####
ex <- intersect(intersect(intersect(extent(a), extent(b)), extent(c)), extent(d1))

d1_crop = crop(d1, ex)
a_crop = crop(a, ex)
b_crop = crop(b, ex)
c_crop = crop(c, ex)
##### Cropping all rasters to the lowest extent #####


##### Reprojecting the rasters to make them the same resolution, making them the same as d1's resolution #####
a_res = projectRaster(a_crop, d1_crop)
b_res = projectRaster(b_crop, d1_crop)
c_res = projectRaster(c_crop, d1_crop)
##### Reprojecting the rasters to make them the same resolution, making them the same as d1's resolution #####

##### Doing your calculations after the resolution and extents are the same.
e = d1_crop-a_res-b_res-c_res

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