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When simplifying polygons it’s almost inevitable that you will generate some slither polygons or gaps between the correct polygons. For example, the following image shows two adjoining complex polygons, representing two adjoining administrative areas. Note there are no gaps between the polygons; they are contiguous (the border is between ... [Read more...]

I’m proud to announce the initial release of rakeR, v0.1.1, has been published on CRAN! It’s licensed under the GPLv3 so you can use it for any projects you wish. Purpose The goal behind rakeR is to make performing spatial microsimulation in R as easy as possible. R ... [Read more...]

This week I updated my Townsend Material Deprivation Score project. The update makes townsendr an interactive online map of deprivation that users can simply view in their browser, rather than having to download and run the R code or view only static maps. I think the result is much more ... [Read more...]

When writing research code I do test my code and results, but until recently I’ve only been doing this informally and not in any systematic way. I decided it was time to change my testing habits when I noticed I had recoded a variable incorrectly despite my informal tests ... [Read more...]

Dissolving polygons is another fairly elementary GIS task that I need to perform regularly. With R this is can be a bit involved, but once done is fully reproducible and the code can be re-used. This post is essentially a companion piece to Clipping polygons in R; I wrote both ... [Read more...]

Clipping polygons is a basic GIS task. It involves removing unneeded polygons outside of an area of interest. For example, you might want to study all local authorities (LADs) in the Yorkshire and the Humber region but can only obtain shapefiles that contain all the LADs in the UK. Removing ... [Read more...]

The R statistical software is my preferred statistical package for many reasons. It’s mature, well-supported by communities such as Stack Overflow, has programming abilities built right in, and, most-importantly, is completely free (in both senses) so that anyone can reproduce and check your analyses. R is extremely comprehensive in ... [Read more...]