For developers and data scientists, the shift from traditional map projections to Discrete Global Grid Systems (DGGS) is more than just a coordinate change—it’s a move toward “Indexing the Earth.” Instead of wrestling with complex spherical trigonometry and the “Greenland problem” (projection distortion), a DGGS treats the planet as a hierarchical database. Every point on Earth is assigned a unique integer ID (like a cell phone’s SIM ID) that inherently contains its location, resolution, and neighborhood relationships. This makes spatial joins, multi-resolution aggregations, and global-scale data analysis as fast as a simple key-value lookup.
The newly released IGEO7 system is a massive leap forward for this ecosystem. While popular systems like Uber’s H3 are excellent for logistics, they can suffer from cell-area variance of up to 50%, which skews scientific statistical models. IGEO7 provides a “pure aperture 7” hexagonal grid that is truly equal-area, ensuring that every cell represents the exact same amount of physical space anywhere on the globe. With the integration of XDGGS and its new plugins, you can now swap between these high-performance backends—including H3, HEALPix, and the DGGRID-powered IGEO7—using a single, unified Xarray API that is cloud-native and Dask-ready.
Ready to build the next generation of planetary-scale applications? Dive into these essential resources to get started:
- DGGS Info Hub: The ultimate primer for the “Why” and “How” of global grids, including the OGC standards.
- Awesome-DGGS: A curated developer portal featuring the best libraries (H3, S2, DGGAL), tools (QGIS plugins), and research papers.
Watch the Youtube DGGS teaser
Watch the DGGS Teaser on our YouTube channel.
We also have a collection DGGS-related presenation around the web on our YouTube channel.
