注意:我抛出这个部分是为了了解是否有更优雅的方式来做这些。所以,请空间类型,提出任何改进建议。
(特别是第 2 步,它设置了一个 "SpatialPoints" 网格,其中包含将提取值的点,对我来说似乎总是令人痛苦的低级。)
这使用over() 从"SpatialPolygonDataFrame" 中提取属性,该坐标位于为此目的而构建的"SpatialPoints" 对象中包含的坐标。
library(rgdal)
## (1) Read in an example shapefile
dsn <- system.file("vectors", package = "rgdal")[1]
scot_BNG <- readOGR(dsn=dsn, layer="scot_BNG")
scot_BNG <- scot_BNG[1:5,] # Let's just use part of it
## (2) Set up a SpatialPoints object with the grid of points
## for which you want to extract values
res <- 10000 ## Distance between grid points (30 in OP's question)
BB <- bbox(scot_BNG)
BB <- res*round(BB/res) ## Pretty up the bounding box
GT <- GridTopology(cellcentre.offset = BB[,1],
cellsize = c(res, res),
cells.dim = (c(diff(BB[1,]), diff(BB[2,]))/res) + 1)
SP <- SpatialPoints(GT, proj4string = CRS(proj4string(scot_BNG)))
## (3) Extract the values
vals <- over(SP, scot_BNG)
res <- cbind(coordinates(SP), vals)
## Finally, have a look at a few of the points.
x <- res[!is.na(res$SP_ID),]
rbind(head(x,3), tail(x,3))[1:10]
# x y SP_ID NAME ID_x COUNT SMR LONG LAT PY
# 4 230000 970000 0 Sutherland 12 5 279.3 58.06 4.64 37521
# 5 240000 970000 0 Sutherland 12 5 279.3 58.06 4.64 37521
# 25 220000 960000 0 Sutherland 12 5 279.3 58.06 4.64 37521
# 425 260000 780000 4 Bedenoch 17 2 186.9 57.06 4.09 27075
# 426 270000 780000 4 Bedenoch 17 2 186.9 57.06 4.09 27075
# 427 280000 780000 4 Bedenoch 17 2 186.9 57.06 4.09 27075