在 R 中制作 choropleth:合并来自多个州的邮政编码 shapefile [英] making a choropleth in R: merging zip code shapefiles from multiple states

问题描述

受到此处帖子的启发，使用 R 开发地理专题地图，我正在考虑根据邮政编码构建一个区域分布图.我已经从 http://www 下载了新罕布什尔州和缅因州的形状文件.census.gov/geo/www/cob/z52000.html，但我对合并或合并来自这两个州的 .shp 文件很感兴趣.

Motivated by the post here, Developing Geographic Thematic Maps with R, I was thinking about constructing a choropleth map based on zip codes. I've downloaded the shape files for New Hampshire and Maine from http://www.census.gov/geo/www/cob/z52000.html, but I'm interested in combining or merging the .shp files from these two states.

在使用 readShapeSpatial() 读取两个 .shp 文件后，maptools 包中是否有一种机制可以对它们进行这种合并或串联?如果例如，也欢迎输入使用 RgoogleMaps 包会更容易.

Is there a mechanism in the maptools package for doing this kind of merge or concatenation of two .shp files after you read them in using readShapeSpatial()? Also welcome input if e.g. using the RgoogleMaps package would be easier.

推荐答案

我跟进了 Roman Luštrik 发布的链接，下面的回答是对 http://r-sig-geo.2731867.n2.nabble.com/suggestion-to-MERGE-or-UNION-3-shapefiles-td5914413.html#a5916751.

I followed up on the link posted by Roman Luštrik, and the following answer is a slight modification of http://r-sig-geo.2731867.n2.nabble.com/suggestion-to-MERGE-or-UNION-3-shapefiles-td5914413.html#a5916751.

以下代码将允许您合并从 .shp 文件="nofollow">人口普查 2000 年 5 位邮政编码制表区 (ZCTA) 制图边界文件并绘制它们.

The following code will allow you to merge the .shp files obtained from Census 2000 5-Digit ZIP Code Tabulation Areas (ZCTAs) Cartographic Boundary Files and plot them.

在本例中，我下载了马萨诸塞州、新罕布什尔州和缅因州的 .shp 文件和相关的 .dbf 和 .shx 文件.

In this case, I downloaded the .shp files and associated .dbf and .shx files for Massachusetts, New Hampshire, and Maine.

library('maptools')
library('rgdal')

setwd('c:/location.of.shp.files')

# this location has the shapefiles for zt23_d00 (Maine), zt25_d00 (Mass.), and zt33_d00 (New Hampshire).

# columns.to.keep
# allows the subsequent spRbind to work properly

columns.to.keep <- c('AREA', 'PERIMETER', 'ZCTA', 'NAME', 'LSAD', 'LSAD_TRANS')

files <- list.files(pattern="*.shp$", recursive=TRUE, full.names=TRUE) 

uid <-1 

# get polygons from first file

poly.data<- readOGR(files[1], gsub("^.*/(.*).shp$", "\\1", files[1])) 
n <- length(slot(poly.data, "polygons"))
poly.data <- spChFIDs(poly.data, as.character(uid:(uid+n-1))) 
uid <- uid + n 
poly.data <- poly.data[columns.to.keep]

# combine remaining polygons with first polygon

for (i in 2:length(files)) {
    temp.data <- readOGR(files[i], gsub("^.*/(.*).shp$", "\\1",files[i]))
    n <- length(slot(temp.data, "polygons")) 
    temp.data <- spChFIDs(temp.data, as.character(uid:(uid+n-1))) 
    temp.data <- temp.data[columns.to.keep]
    uid <- uid + n 
    poly.data <- spRbind(poly.data,temp.data) 
}

plot(poly.data)

# save new shapefile

combined.shp <- 'combined.shp'
writeOGR(poly.data, dsn=combined.shp, layer='combined1', driver='ESRI Shapefile') 

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