CODEWITHSUNDEEP
rgisramrastershapefile
Nathan
Nathan

Reputation: 686

How can I clip large shapefiles in program R without the computer crashing?

I am wanting to clip a large shapefile (67MB) in program R and derive a much smaller raster from around ~5% of it. Once loaded the shapefile has 221388 features and 5 fields - and explodes to 746 MB.

My difficulty comes when trying to clip the file to a workable size - the program crashes after a few minutes. I have tried both crop (from raster) and gIntersection (from rgeos) without success. I have 8GB of RAM - clearly there is a memory issue.

I am guessing there maybe a work around. I know that there are some big memory packages out there - but can any of them help in my kind of situation? My current code is below:

# dataset can be found at 
# http://data.fao.org/map?entryId=271096b2-8a12-4050-9ff2-27c0fec16c8f

# location of files
ogrListLayers("C:/Users/Me/Documents/PNG Glob")

# import shapefile
ogrDrivers()[10,]

# shapefiles
Glob<-readOGR("C:/Users/Me/Documents/PNG Glob", layer="png_gc_adg_1")

# assign projection
Glob@proj4string<- CRS("+proj=longlat")

#object size
object.size(Glob) 

# clipping
crop(Glob, extent(c(144,146,-7,-5)))

Upvotes: 3

Views: 1546

Answers (1)

jbaums
jbaums

Reputation: 27388

As suggested by @Pascal, GDAL's ogr2ogr is useful for this. You can call it from R with system as follows (including on Windows), though this assumes that (1) you have a working GDAL installation and (2) the path to the GDAL binaries exists in your PATH environment variable:

  1. Download and unzip the PNG shapefile:

    download.file('http://www.fao.org/geonetwork/srv/en/resources.get?id=37162&fname=png_gc_adg.zip&access=private', 
              f <- tempfile(fileext='.zip'))
unzip(f, exdir=tempdir())

  2. Call ogr2ogr with system from R to clip the PNG shapefile and save the resulting .shp to the working directory:

    system(sprintf('ogr2ogr -clipsrc 144 -7 146 -5 png_clip.shp %s', 
               file.path(tempdir(), 'png_gc_adg_1.shp')))

    On my system this took around 70 seconds, and memory usage didn't seem to increase by more than about 100MB. (I did get a lot of warnings of the likes of Warning 1: Value 138717513240 of field AREA of feature 0 not successfully written. Possibly due to too larger number with respect to field width - not sure what that's about.)

  3. Load the clipped shapefile: 

    library(rgdal)
p <- readOGR('.', 'png_clip')
plot(p)

    png clip

Upvotes: 1

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