这是一个玩具的例子,我一直在摔跤
# Make points point1 <- c(.5,.5) point2 <- c(.6,.6) point3 <- c(3,3) mpt <- st_multipoint(rbind(point1,point2,point3)) # create multipoint # Make polygons square1 <- rbind(c(0,0),c(1,1),c(0,0)) square2 <- rbind(c(0,c(2,2),0)) square3 <- rbind(c(0,c(-1,-1),0)) mpol <- st_multipolygon(list(list(square1),list(square2),list(square2))) # create multipolygon # Convert to class' sf' pts <- st_sf(st_sfc(mpt)) polys <- st_sf(st_sfc(mpol)) # Determine which points fall inside which polygons st_join(pts,polys,join = st_contains)
最后一行生产
Error in as.data.frame.default(x[[i]],optional = TRUE,stringsAsFactors = stringsAsFactors) :
cannot coerce class "c("sfc_MULTIPOINT","sfc")" to a data.frame
如何做一个空间连接来确定哪些点落在哪个多边形？
解决方法
我也在围绕sf包的功能,所以道歉,如果这是不正确的或有更好的方法.我认为这里的一个问题是,如果你在你的例子中建立几何体,那么你不会得到你的想法：
> pts Simple feature collection with 1 feature and 0 fields geometry type: MULTIPOINT dimension: XY bBox: xmin: 0.5 ymin: 0.5 xmax: 3 ymax: 3 epsg (SRID): NA proj4string: NA st_sfc.mpt. 1 MULTIPOINT(0.5 0.5,0.6 0.6... > polys Simple feature collection with 1 feature and 0 fields geometry type: MULTIPOLYGON dimension: XY bBox: xmin: 0 ymin: 0 xmax: 2 ymax: 2 epsg (SRID): NA proj4string: NA st_sfc.mpol. 1 MULTIPOLYGON(((0 0,1 0,1 ...
您可以看到,您在pts和poly中只有一个“功能”.这意味着您正在构建一个“多边形”功能(即由3个部分组成的多边形),而不是三个不同的多边形.点数也一样.
在挖了一下之后,我发现使用WKT符号来形成不同的(在我看来更容易)的方式来构建几何体：
polys <- st_as_sfc(c("POLYGON((0 0,0 1,1 1,0 0))","POLYGON((0 0,0 2,2 2,2 0,0 0 ))",0 -1,-1 -1,-1 0,0 0))")) %>%
st_sf(ID = paste0("poly",1:3))
pts <- st_as_sfc(c("POINT(0.5 0.5)","POINT(0.6 0.6)","POINT(3 3)")) %>%
st_sf(ID = paste0("point",1:3))
> polys
Simple feature collection with 3 features and 1 field
geometry type: POLYGON
dimension: XY
bBox: xmin: -1 ymin: -1 xmax: 2 ymax: 2
epsg (SRID): NA
proj4string: NA
ID .
1 poly1 POLYGON((0 0,1 0...
2 poly2 POLYGON((0 0,2 0...
3 poly3 POLYGON((0 0,...
> pts
Simple feature collection with 3 features and 1 field
geometry type: POINT
dimension: XY
bBox: xmin: 0.5 ymin: 0.5 xmax: 3 ymax: 3
epsg (SRID): NA
proj4string: NA
ID .
1 point1 POINT(0.5 0.5)
2 point2 POINT(0.6 0.6)
3 point3 POINT(3 3)
你可以看到现在,poly和pts有三个特征.
我们现在可以找到“交叉矩阵”：
# Determine which points fall inside which polygons pi <- st_contains(polys,pts,sparse = F) %>% as.data.frame() %>% mutate(polys = polys$ID) %>% select(dim(pi)[2],1:dim(pi)[1]) colnames(pi)[2:dim(pi)[2]] = levels(pts$ID) > pi polys point1 point2 point3 1 poly1 TRUE TRUE FALSE 2 poly2 TRUE TRUE FALSE 3 poly3 FALSE FALSE FALSE
意义(在注释中指出@symbolixau),多边形1和2包含点1和2,而多边形3不包含任何点.点3不是包含在任何多边形中.
HTH.
