Areal interpolation is the process making estimates from a source set of polygons to an overlapping but incongruent set of target polygons. One challenge with areal interpolation is that, while the processes themselves are well documented in the academic literature, implementing them often involves "reinventing the wheel." While the R package sf does offer a basic interface for areal weighted interpolation (st_interpolate_aw), it lacks some features that we use in our work. The areal package contains a suite tools for validation and estimation, providing a full-featured workflow that fits into both modern data management (e.g. tidyverse) and spatial data (e.g. sf) frameworks.
An article describing areal's approach to areal weighted interpolation has been published in the The Journal of Open Source Software. The article includes benchmarking of areal performance on several data sets. Please cite the paper if you use areal in your work!
The easiest way to get areal is to install it from CRAN:
install.packages("areal")Alternatively, the development version of areal can be accessed from GitHub with remotes:
# install.packages("remotes")
remotes::install_github("chris-prener/areal")Additional details, including some tips for installing sf, can be found in the Get started article.
In addition to instructions for installation, the main Get started article has:
- a quick overview of areal interpolation,
- some notes on preparing data for interpolation,
- a brief introduction to the
aw_interpolate()function, - tips for getting help and submitting feedback,
- and the
arealpackage's development roadmap!
This site also offers dedicated articles on data preparation and using areal for areal weighted interpolation.