Amy Whitehead's Research

the ecological musings of a conservation biologist

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Extracting raster data using a shapefile

I recently had an email from a PhD student in Austria who had a raster showing the distribution of Douglas Fir in Europe and wanted to know what proportion of each European country was covered in this species. They had a raster with presence (1) and absence (0) of Douglas-fir in Europe and wanted to calculate the number of cells with 1 and 0 within each country of the Europe. I’ve put together a dummy example below which shows how to R script to extract the number of raster cells in each country that meet a certain condition.


Douglas Fir (source: Pixabay)

Essentially the script works through the following steps:

  1. Loads the relevant shapefile and raster datasets.
  2. Identifies all of the countries within the shapefile.
  3. Within a loop, masks the presence-absence raster by each country and counts the number of cells that meet the required condition.

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Converting shapefiles to rasters in R

I’ve been doing a lot of analyses recently that need rasters representing features in the landscape. In most cases, these data have been supplied as shapefiles, so I needed to quickly extract parts of a shapefile dataset and convert them to a raster in a standardised format. Preferably with as little repetitive coding as possible. So I created a simple and relatively flexible function to do the job for me.

The function requires two main input files: the shapefile (shp) that you want to convert and a raster that represents the background area (mask.raster), with your desired extent and resolution. The value of the background raster should be set to a constant value that will represent the absence of the data in the shapefile (I typically use zero).

The function steps through the following:

  1. Optional: If shp is not in the same projection as the mask.raster, set the current projection (proj.from) and then transform the shapefile to the new projection ( using transform=TRUE.
  2. Convert shp to a raster based on the specifications of mask.raster (i.e. same extent and resolution).
  3. Set the value of the cells of the raster that represent the polygon to the desired value.
  4. Merge the raster with mask.raster, so that the background values are equal to the value of mask.raster.
  5. Export as a tiff file in the working directory with the label specified in the function call.
  6. If desired, plot the new raster using map=TRUE.
  7. Return as an object in the global R environment.

The function is relatively quick, although is somewhat dependant on how complicated your shapefile is. The more individual polygons that need to filtered through and extracted, the longer it will take. Continue reading