Open-source DGGS comparison data supplement

A DGGS is a type of spatial reference system that partitions the globe into many individual, evenly spaced, and well-aligned cells to encode location. We calculated normalized area and compactness of cell geometries for 5 open-source DGGS implementations - Uber H3, Google S2, RiskAware OpenEAGGR, rHEALPix by Landcare Research New Zealand, HEALPix by NASA Jet Propulsion Labs, and DGGRID by Southern Oregon University - to evaluate their suitability for a global-level statistical data cube.

This repository contains all generated data and statistics.

EAGGR doesn't seem to have a predefined logic of hierarchical cell resolutions for ISEA3H

EAGGR doesn't seem to have a region filling algorithm available, neither for ISEA4T nor ISEA3H

rHEALPix is pure Python (with Numpy/Scipy support), but cell generation/conversion is slower than the other C/C++ based implementations

DGGRID is a commandline tool and can predominantly only be used to generate a grid and fill with sampling data, the Python API is only a wrapper

healpy is a Python package to handle pixelated data on the sphere. It is based on the Hierarchical Equal Area isoLatitude Pixelization (HEALPix) scheme and bundles the HEALPix C++ library.

Kmoch et. al (2022). Area and Shape Distortions in Open-Source Discrete Global Grid Systems. Big Earth Data