R：将栅格聚合到 shapefile 多边形

Question

我想将栅格数据聚合到自定义 shapefile 中的每个多边形。

在这种情况下，我想获得撒哈拉以南非洲国家以下地区的平均城市化程度。

我的 sf 是这样的：

> africa_map
Simple feature collection with 543 features and 4 fields
Geometry type: MULTIPOLYGON
Dimension:     XY
Bounding box:  xmin: -25.36042 ymin: -46.96575 xmax: 63.49391 ymax: 27.66147
Geodetic CRS:  WGS 84
First 10 features:
    cname ccode        regname continent                       geometry
1  Angola    AO          Bengo    Africa MULTIPOLYGON (((13.371 -8.5...
2  Angola    AO       Benguela    Africa MULTIPOLYGON (((12.53336 -1...
3  Angola    AO            Bie    Africa MULTIPOLYGON (((16.61158 -1...
4  Angola    AO        Cabinda    Africa MULTIPOLYGON (((12.78266 -4...
5  Angola    AO Cuando Cubango    Africa MULTIPOLYGON (((21.9838 -16...
6  Angola    AO   Cuanza Norte    Africa MULTIPOLYGON (((15.40788 -7...
7  Angola    AO     Cuanza Sul    Africa MULTIPOLYGON (((13.7926 -11...

或绘制：

另一方面，栅格数据采用以下形式：

> imported_raster
class      : RasterLayer 
dimensions : 18000, 36082, 649476000  (nrow, ncol, ncell)
resolution : 1000, 1000  (x, y)
extent     : -18041000, 18041000, -9e+06, 9e+06  (xmin, xmax, ymin, ymax)
crs        : +proj=moll +lon_0=0 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs 
names      : GHS_BUILT_LDS1975_GLOBE_R2018A_54009_1K_V2_0 
values     : 0, 100  (min, max)

对于整个星球来说，这些比需要的更细粒度。为了加速计算，我首先聚合了栅格，然后将其转换为 shapefile，每个剩余的栅格像素都转换为 shapefile 中的点几何。然后，可以将此 shapefile 聚合到我的区域边界。不可否认，这不是很优雅（并且最终不起作用）。

library(tidyverse)
library(sf)
library(raster)
library(stars)
library(rgdal)

> # aggregate (to 25x25 km)
> imported_raster_ag <- aggregate(imported_raster, fact=25)
> 
> # convert to sp
> urbanized = rasterToPolygons(imported_raster_ag) 
> # convert to sf
> urbanized_sf <- st_as_sf(urbanized)

# compare projection
st_crs(africa_map)==st_crs(urbanized_sf)
# align projection
urbanized_sf <- st_transform(urbanized_sf, st_crs(africa_map))

urbanized_sf <- urbanized_sf %>% rename(urbanization = GHS_BUILT_LDS1975_GLOBE_R2018A_54009_1K_V2_0)

> urbanized_sf
Simple feature collection with 398872 features and 1 field (with 500 geometries empty)
Geometry type: POLYGON
Dimension:     XY
Bounding box:  xmin: -179.9999 ymin: -57.40086 xmax: 179.9963 ymax: 82.33738
Geodetic CRS:  WGS 84
First 10 features:
   urbanization                       geometry
1             0 POLYGON ((-117.1367 82.3373...
2             0 POLYGON ((-116.2261 82.3373...
3             0 POLYGON ((-115.3156 82.3373...
4             0 POLYGON ((-114.405 82.33738...
5             0 POLYGON ((-113.4944 82.3373...
6             0 POLYGON ((-112.5838 82.3373...
7             0 POLYGON ((-111.6732 82.3373...
8             0 POLYGON ((-110.7627 82.3373...
9             0 POLYGON ((-109.8521 82.3373...
10            0 POLYGON ((-108.9415 82.3373...

我的想法是，截至目前，我可以沿着其他 sf 的区域边界聚合这些点。但是，我收到一条错误消息，我发现的唯一推荐的修复方法只是重复它。

> urbanized_africa <- aggregate(urbanized_sf["urbanization"], by = africa_map$geometry, mean)
although coordinates are longitude/latitude, st_intersects assumes that they are planar
Error in CPL_geos_binop(st_geometry(x), st_geometry(y), op, par, pattern,  : 
  Evaluation error: IllegalArgumentException: Invalid number of points in LinearRing found 2 - must be 0 or >= 4.

> urbanized_sf_fixed <- sf::st_make_valid(urbanized_sf)
Error in CPL_geos_make_valid(x) : 
  Evaluation error: IllegalArgumentException: Invalid number of points in LinearRing found 2 - must be 0 or >= 4.

我想在我的转换过程中某处可能会损坏某些东西或者其他东西存在更根本的缺陷。将栅格数据聚合到 shapefile 多边形中的更优雅、最重要的是更实用的工作流是什么？

Answer 1

查看 extract 函数

在你的情况下是这样的

africamap$urbanized <- extract(imported_raster, africamap, fun="mean")

africamap应该还是先投影到光栅投影。如果您有 nodata 个值，那么在调用中添加一个 na.rm=TRUE 参数应该是明智的。

要缩短处理时间，您还可以将栅格裁剪到非洲。

exactextractr 包中还有一个更快的 extract 版本。您还可以利用 terra 而不是 raster 进行光栅处理。

R：将栅格聚合到 shapefile 多边形

R: Aggregating raster to shapefile polygons

r

polygon

raster

aggregation

sf