[GIS] Creating a map of population density using shapefiles in R

This would be a pretty simple task for me in ArcGIS, but I'm trying to start using R and I'm stumped. I have census data in the form of a shapefile that contains the population of each shape in the shapefile. I would like to divide the population by the area of each shape in order to create a density map. But I can't figure out how to calculate the area of each shape in the shapefile, and I can't figure out how to take the area once I've calculated it and divide the population by the area.

Best Answer

library(rgdal)
library(raster)

areashp<-readOGR("C:/","Census")
areashp$Totalarea<-area(areashp)
areashp$density<- areashp$population / areashp$Totalarea

Also make sure you are in UTM or another projection for calculating area

Using rgeos:

library(rgeos)
areashp$Totalarea<-gArea(areashp, byid=TRUE)
areashp$density<- areashp$population / areashp$Totalarea

Alternatively, as per Jeffrey's comment you could use: areashp$density<- areashp$population / rgeos::gArea(areashp, byid=TRUE) if you don't want area in your attribute table.

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[GIS] Using R to calculate the area of multiple polygons on a map that intersect with another overlaid polygon

Spacedman's answer and hints above were useful, but do not in themselves constitute a full answer. After some detective work on my part I have got closer to an answer although I have not yet managed to get gIntersection in the way I want (see original question above). Still, I have managed to get my new polygon into the SpatialPolygonsDataFrame.

UPDATE 2012-11-11: I seem to have found a workable solution (see below). The key was to wrap the polygons in a SpatialPolygons call when using gIntersection from the rgeos package. The output looks like this:

[1] "Haverfordwest: Portfield ED (poly 2) area = 1202564.3, intersect = 143019.3, intersect % = 11.9%"
[1] "Haverfordwest: Prendergast ED (poly 3) area = 1766933.7, intersect = 100870.4, intersect % = 5.7%"
[1] "Haverfordwest: Castle ED (poly 4) area = 683977.7, intersect = 338606.7, intersect % = 49.5%"
[1] "Haverfordwest: Garth ED (poly 5) area = 1861675.1, intersect = 417503.7, intersect % = 22.4%"

Inserting the polygon was harder than I thought because, surprisingly, there doesn't seem to be an easy-to-follow example of inserting a new shape in an existing Ordnance Survey-derived shapefile. I have reproduced my steps here in the hope that it will be useful to somebody else. The result is a map like this.

map showing new polygon overlaid

If/when I solve the intersection issue I will edit this answer and add the final steps, unless, of course, somebody beats me to it and provides a full answer. In the meantime, comments/advice on my solution so far are all welcome.

Code follows.

require(sp) # the classes and methods that make up spatial ops in R
require(maptools) # tools for reading and manipulating spatial objects
require(mapdata) # includes good vector maps of world political boundaries.
require(rgeos)
require(rgdal)
require(gpclib)
require(ggplot2)
require(scales)
gpclibPermit()

## Download the Ordnance Survey Boundary-Line data (large!) from this URL:
## https://www.ordnancesurvey.co.uk/opendatadownload/products.html
## then extract all the files to a local folder.
## Read the electoral division (ward) boundaries from the shapefile
shp1 <- readOGR("C:/test", layer = "unitary_electoral_division_region")
## First subset down to the electoral divisions for the county of Pembrokeshire...
shp2 <- shp1[shp1$FILE_NAME == "SIR BENFRO - PEMBROKESHIRE" | shp1$FILE_NAME == "SIR_BENFRO_-_PEMBROKESHIRE", ]
## ... then the electoral divisions for the town of Haverfordwest (this could be done in one step)
shp3 <- shp2[grep("haverford", shp2$NAME, ignore.case = TRUE),]

## Create a matrix holding the long/lat coordinates of the desired new shape;
## one coordinate pair per line makes it easier to visualise the coordinates
my.coord.pairs <- c(
                    194500,215500,
                    194500,216500,
                    195500,216500,
                    195500,215500,
                    194500,215500)

my.rows <- length(my.coord.pairs)/2
my.coords <- matrix(my.coord.pairs, nrow = my.rows, ncol = 2, byrow = TRUE)

## The Ordnance Survey-derived SpatialPolygonsDataFrame is rather complex, so
## rather than creating a new one from scratch, copy one row and use this as a
## template for the new polygon. This wouldn't be ideal for complex/multiple new
## polygons but for just one simple polygon it seems to work
newpoly <- shp3[1,]

## Replace the coords of the template polygon with our own coordinates
newpoly@polygons[[1]]@Polygons[[1]]@coords <- my.coords

## Change the name as well
newpoly@data$NAME <- "zzMyPoly" # polygons seem to be plotted in alphabetical
                                 # order so make sure it is plotted last

## The IDs must not be identical otherwise the spRbind call will not work
## so use the spCHFIDs to assign new IDs; it looks like anything sensible will do
newpoly2 <- spChFIDs(newpoly, paste("newid", 1:nrow(newpoly), sep = ""))

## Now we should be able to insert the new polygon into the existing SpatialPolygonsDataFrame
shp4 <- spRbind(shp3, newpoly2)

## We want a visual check of the map with the new polygon but
## ggplot requires a data frame, so use the fortify() function
mydf <- fortify(shp4, region = "NAME")

## Make a distinction between the underlying shapes and the new polygon
## so that we can manually set the colours
mydf$filltype <- ifelse(mydf$id == 'zzMyPoly', "colour1", "colour2")

## Now plot
ggplot(mydf, aes(x = long, y = lat, group = group)) +
    geom_polygon(colour = "black", size = 1, aes(fill = mydf$filltype)) +
    scale_fill_manual("Test", values = c(alpha("Red", 0.4), "white"), labels = c("a", "b"))

## Visual check, successful, so back to the original problem of finding intersections
overlaid.poly <- 6 # This is the index of the polygon we added
num.of.polys <- length(shp4@polygons)
all.polys <- 1:num.of.polys
all.polys <- all.polys[-overlaid.poly] # Remove the overlaid polygon - no point in comparing to self
all.polys <- all.polys[-1] ## In this case the visual check we did shows that the
                           ## first polygon doesn't intersect overlaid poly, so remove

## Display example intersection for a visual check - note use of SpatialPolygons()
plot(gIntersection(SpatialPolygons(shp4@polygons[3]), SpatialPolygons(shp4@polygons[6])))

## Calculate and print out intersecting area as % total area for each polygon
areas.list <- sapply(all.polys, function(x) {
    my.area <- shp4@polygons[[x]]@Polygons[[1]]@area # the OS data contains area
    intersected.area <- gArea(gIntersection(SpatialPolygons(shp4@polygons[x]), SpatialPolygons(shp4@polygons[overlaid.poly])))
    print(paste(shp4@data$NAME[x], " (poly ", x, ") area = ", round(my.area, 1), ", intersect = ", round(intersected.area, 1), ", intersect % = ", sprintf("%1.1f%%", 100*intersected.area/my.area), sep = ""))
    return(intersected.area) # return the intersected area for future use
      })

Best Answer

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[GIS] Using R to calculate the area of multiple polygons on a map that intersect with another overlaid polygon

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