H3 Hierarchy and Compaction: Multi-Resolution Spatial Analysis
Master H3's parent-child cell relationships and compaction algorithm for efficient spatial data representation
Every H3 hexagon at any resolution is the parent of exactly seven children at the next finer resolution. This seven-to-one relationship makes H3 uniquely powerful for multi-scale analysis — and its compaction algorithm exploits it to compress spatial datasets dramatically.
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H3 Catchment Analysis: Modelling Service Areas with Hexagonal Grids
Use H3's k-ring and grid distance functions to build precise spatial buffers and accessibility zones
Traditional circular buffers distort space and ignore real-world geometry. H3's hexagonal rings give you scale-consistent spatial catchments that work the same way across the entire Earth's surface.
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H3 Density Mapping: Visualising Urban Point Data as Hexagonal Heatmaps
Transform scattered coordinates into meaningful density patterns using H3's spatial aggregation
Raw GPS coordinates are noisy, overwhelming, and hard to interpret at scale. H3's hexagonal grid transforms thousands of points into clear, legible density maps — and the core aggregation logic fits in under ten lines.
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PlaceAgents: Modelling Multi-Stop Pedestrian Itineraries as Platial Flows
An itinerary-centred agent-based framework for simulating pedestrian movement on urban networks
Urban life is made by the places that people merge together into formal routines. PlaceAgents is a framework for modelling multi-stop pedestrian itineraries on city networks using open and reproducible data—treating the city as linked places rather than abstract space.
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Getting Started with H3: The Hexagonal Grid System for Spatial Analysis
A practical tutorial for understanding and implementing Uber's H3 hexagonal grid system
Why are Uber, Foursquare, and every major location intelligence company switching to hexagonal grids? This tutorial will teach you H3 fundamentals with interactive examples you can run in your browser.
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