我有一个简单的栅格(使用R-package:raster创建).使用"rasterToPolygons"函数,我得到包含值"1"的所有栅格单元格的多边形:
library(raster)
dat = list()
dat$x = seq(1.5, by = 10, len = 10)
dat$y = seq(3.5, by = 10, len = 15)
dat$z = matrix(sample(c(0,1), size = 10*15, replace = T), 10, 15)
r=raster(dat);plot(r)
r_poly = rasterToPolygons(r, fun = function(r) {r == 1}, dissolve = F)
plot(r_poly, add = T)
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我不使用"dissolve = T"来避免所有多边形合并为一个大的多边形.相反,我希望获得一个新的SpatialPolygonsDataFrame,其中包含共享边或点的所有多边形.明确分开的多边形应该可以识别为单个多边形.基于新的SpatialPolygonsDataFrame,我想分析组合多边形的大小,如下所示:
b = extract(r,r_poly_new) # "r_poly_new" contains the combined polygons
str(b) # list of clearly separated polygons
tab = lapply(b,table)
tab
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我的问题有两个:1)如何组合共享边缘或点的多边形?2)如何将这些信息转换为允许分析组合多边形区域的格式?非常感谢您的反馈.
您可以首先用于raster::clump()识别已连接的栅格单元的集群,然后应用于rasterToPolygons()"多边形化"这些单元格.(请注意,每个丛的区域可以直接从未RasterLayer将其转换为a计算SpatialPolygonsDataFrame,如下所示):
library(rgeos) ## For the function gArea
## Clump and polygonize
Rclus <- clump(r)
SPclus <- rasterToPolygons(Rclus, dissolve=TRUE)
## Check that this works
plot(SPclus, col = seq_along(SPclus))
## Get cluster areas from RasterLayer object
transform(data.frame(freq(Rclus)),
area = count*prod(res(Rclus)))
## Get cluster areas from SpatialPolygons object
transform(data.frame(SPclus),
area = gArea(SPclus, byid=TRUE))
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