We have been using the H3 DGGS with various OS GIS tools and standards (GDAL/OGR, PostgreSQL/PostGIS, GeoParquet, Dask, GeoPandas) to efficiently compute high-resolution land-use maps of parts of New Zealand against a variety of classification systems, most recently the Australian Land Use and Management Classification Version 8 (ALUM).

You will learn about our automated workflow, which can efficiently combine a large number of raster and vector datasets through the use of a DGGS. You will get an introduction to DGGS, which we think is best thought about as a third-way between the vector and raster data models. You will see how a DGGS approach to geospatial computation lends itself well to parallel computation, because of the nested hierarchical nature of DGGS cells—which is a compelling advantage over existing methods that work within either the raster or vector data models.