Land use classification using a discrete global grid system

A general-purpose, land use classification of an area is a valuable geospatial dataset. Making one requires assembling a wide variety of geospatial input data. This can become computationally difficult as the number or type of datasets increases, the spatial precision increases, or the combinatorial classification logic becomes more convoluted. We present as a solution a common analytical framework based on a discrete global grid system (DGGS). This provides a spatial data structure that improves geospatial data interoperability and the efficiency of producing classified land use data.