The aim of the
mapspamc R package is to facilitate the creation of country level crop distribution maps. The model builds on the global version of the Spatial Production Allocation model (SPAM) (You and Wood 2006; You, Wood, and Wood-Sichra 2009; You et al. 2014; Yu et al. 2020), which uses a cross-entropy optimization approach to ‘pixelate’ national and subnational crop statistics on a spatial grid at a resolution of 5 arc minutes (~ 10 x 10 km).
mapspamc provides the necessary infrastructure to run SPAM at the country level and makes it possible to incorporate national sources of information and potentially create maps at a higher resolution of 30 arc seconds (~ 1 x 1 km)(Dijk et al. 2022).
The articles in the Background section provide general information on approaches to create crop distribution maps, the model, input data, country examples and an appendix with additional information on specific topics.
mapspamc requires the installation of several other pieces of software, which are described in the Installation section.
It takes some preparation before the crop distribution maps can be generated. Most important and probably most time consuming is the collection of input data.
mapspamc requires a large variety of input data, which can be grouped under three headers: (1) national crop statistics, (2) data to construct the priors/fitness scores and (3) data to determine the spatial constraints. The availability of data strongly affects the structure of the model, how it will be solved and how long it takes to solve. We highly recommend to start collecting input data before running the model. The articles in the Background section give an overview of the input data that are required by the package and show were to download several country examples.
mapspamc can be divided into six major steps which are split into nine smaller steps in the Run mapspamc section.