H3 (Uber)

H3 is an open-source geospatial indexing system created by Uber that divides the Earth's surface into a hierarchy of hexagonal cells at 16 resolution levels, from continental scale (resolution 0, ~4.3 million km²) to sub-meter precision (resolution 15, ~0.9 m²). Hexagonal grids are preferred over square grids for spatial analysis because each hexagon has the same distance to all six neighbors, eliminating directional bias in proximity calculations. H3 assigns a unique 64-bit integer index to each hexagonal cell, enabling fast lookups, parent-child traversal between resolutions, and efficient spatial joins. Core functions include point-to-cell indexing, cell boundary retrieval, neighbor (k-ring) discovery, hierarchical compaction, polyfill (polygon-to-cell coverage), and distance calculations. H3 is available as a C library with bindings for Python, JavaScript, Java, Go, and other languages, and is integrated into databases like BigQuery, Snowflake, Databricks, and ClickHouse. H3 is widely adopted for location analytics, particularly in ride-sharing, logistics, and retail site selectionSite SelectionSite selection is the analytical process of evaluating and choosing optimal physical locations for new stores, facili.... Its uniform hexagonal grid enables consistent spatial aggregation, density analysis, and isochroneIsochroneAn isochrone is a line or polygon on a map connecting all points reachable from a given location within a specified t... computation. Urban planners, data scientists, and analysts use H3 to bucket point data into spatial units for visualization and statistical analysis. The system's hierarchical nature supports multi-scale analysis and efficient data compression for large-scale geospatial datasets.