使用 R 开发地理专题地图 [英] Developing Geographic Thematic Maps with R

问题描述

显然，R 中有许多用于各种空间分析的包.这可以在
_{(来源:eduardoleoni.com)}

图书馆(地图工具)在这里替换你的 shapefilestate.map <- readShapeSpatial("BRASIL.shp")County.map <- readShapeSpatial("55mu2500gsd.shp")## 这是我们将要绘制的变量counties.map@data$noise <- rnorm(nrow(counties.map@data))

热图函数

plot.heat <- function(counties.map,state.map,z,title=NULL,breaks=NULL,reverse=FALSE,cex.legend=1,bw=.2,col.vec=NULL,plot.legend=TRUE) {##分解值变量if (is.null(breaks)) {休息=序列(楼层(min(counties.map@data[,z],na.rm=TRUE)*10)/10,上限(最大值(counties.map@data[,z],na.rm=TRUE)*10)/10,.1)}counties.map@data$zCat <- cut(counties.map@data[,z],breaks,include.lowest=TRUE)切点 <- 级别(counties.map@data$zCat)if (is.null(col.vec)) col.vec <- heat.colors(length(levels(counties.map@data$zCat)))如果(反向){cutpointsColors <- rev(col.vec)} 别的 {cutpointsColors <- col.vec}级别(counties.map@data$zCat)<-cutpointsColors情节(counties.map,border=gray(.8), lwd=bw,axes = FALSE, las = 1,col=as.character(counties.map@data$zCat))if (!is.null(state.map)) {情节(state.map，add=TRUE，lwd=1)}##with(counties.map.c,text(x,y,name,cex=0.75))if (plot.legend) legend("bottomleft", cutpoints, fill = cutpointsColors,bty="n",title=title,cex=cex.legend)##title("制图")}

画出来

plot.heat(counties.map,state.map,z="noise",breaks=c(-Inf,-2,-1,0,1,2,Inf))

There are clearly a number of packages in R for all sorts of spatial analysis. That can by seen in the CRAN Task View: Analysis of Spatial Data. These packages are numerous and diverse, but all I want to do is some simple thematic maps. I have data with county and state FIPS codes and I have ESRI shape files of county and state boundaries and the accompanying FIPS codes which allows joining with the data. The shape files could be easily converted to other formats, if needed.

So what's the most straight forward way to create thematic maps with R?

This map looks like it was created with an ESRI Arc product, but this is the type of thing I would like to do with R:

alt text http://www.infousagov.com/images/choro.jpg Map copied from here.

解决方案

The following code has served me well. Customize it a little and you are done.
_{(source: eduardoleoni.com)}

library(maptools)
substitute your shapefiles here
state.map <- readShapeSpatial("BRASIL.shp")
counties.map <- readShapeSpatial("55mu2500gsd.shp")
## this is the variable we will be plotting
counties.map@data$noise <- rnorm(nrow(counties.map@data))

heatmap function

plot.heat <- function(counties.map,state.map,z,title=NULL,breaks=NULL,reverse=FALSE,cex.legend=1,bw=.2,col.vec=NULL,plot.legend=TRUE) {
  ##Break down the value variable
  if (is.null(breaks)) {
    breaks=
      seq(
          floor(min(counties.map@data[,z],na.rm=TRUE)*10)/10
          ,
          ceiling(max(counties.map@data[,z],na.rm=TRUE)*10)/10
          ,.1)
  }
  counties.map@data$zCat <- cut(counties.map@data[,z],breaks,include.lowest=TRUE)
  cutpoints <- levels(counties.map@data$zCat)
  if (is.null(col.vec)) col.vec <- heat.colors(length(levels(counties.map@data$zCat)))
  if (reverse) {
    cutpointsColors <- rev(col.vec)
  } else {
    cutpointsColors <- col.vec
  }
  levels(counties.map@data$zCat) <- cutpointsColors
  plot(counties.map,border=gray(.8), lwd=bw,axes = FALSE, las = 1,col=as.character(counties.map@data$zCat))
  if (!is.null(state.map)) {
    plot(state.map,add=TRUE,lwd=1)
  }
  ##with(counties.map.c,text(x,y,name,cex=0.75))
  if (plot.legend) legend("bottomleft", cutpoints, fill = cutpointsColors,bty="n",title=title,cex=cex.legend)
  ##title("Cartogram")
}

plot it

plot.heat(counties.map,state.map,z="noise",breaks=c(-Inf,-2,-1,0,1,2,Inf))

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