我正在学习空间数据帧。我创建了一个简单的示例,它使用反距离加权 (IDW) 根据初始点集在网格上插入值。我现在想获得每个初始点的插值。我认为这应该相对容易,但很难找到一种优雅的方法。换句话说,我想在“geog2.idw”中为 40 个点 (x,y) 中的每个点找到最接近的网格值。
代码
#adjusted from example created by Brian J. Knaus
#packages
library(gstat)
require(gstat)
require(lattice)
require(raster)
require(sp)
##### ##### ##### ##### #####
# Generate data.
set.seed(1)
x <- runif(40, -123, -110)
set.seed(2)
y <- runif(40, 40, 48)
set.seed(3)
z <- runif(40, 0, 1)
# Create spatial data.frame.
geog2 <- data.frame(x,y,z)
# Assigning coordinates results in spdataframe.
coordinates(geog2) = ~x+y
#create grid
pixels <- 100
geog.grd <- expand.grid(x=seq(floor(min(coordinates(geog2)[,1])),
ceiling(max(coordinates(geog2)[,1])),
length.out=pixels),
y=seq(floor(min(coordinates(geog2)[,2])),
ceiling(max(coordinates(geog2)[,2])),
length.out=pixels))
#
grd.pts <- SpatialPixels(SpatialPoints((geog.grd)))
grd <- as(grd.pts, "SpatialGrid")
##### ##### ##### ##### #####
# IDW interpolation.
geog2.idw <- idw(z ~ 1, geog2, grd, idp=6)
spplot(geog2.idw["var1.pred"])
##### ##### ##### ##### #####
# Image.
par(mar=c(2,2,1,1))
#
image(geog2.idw, xlim=c(-125, -110), ylim=c(40, 47))
#
contour(geog2.idw, add=T, lwd=0.5)
#
map("state", lwd=1, add=T)
map("county", lty=3, lwd=0.5, add=T)
#
points(x, y, pch=21, bg=c(1:4))
#######
最佳答案
您可以将x
和y
转换为SpatialPoints
:SpatialPoints(cbind(x,y))
和使用函数over
:
pts <- SpatialPoints(cbind(x, y))
pts.idw <- over(pts, geog2.idw["var1.pred"])
# Writing extracted values on the map:
image(geog2.idw, xlim=c(-125, -110), ylim=c(40, 47))
contour(geog2.idw, add=T, lwd=0.5)
map("state", lwd=1, add=T)
map("county", lty=3, lwd=0.5, add=T)
text(pts, round(pts.idw[,"var1.pred"],4), col = "blue")
关于r - 在 R 中的空间数据框中查找最近的网格值,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30096740/