Spatial Computing

Learn how H3's hierarchical structure enables multi-resolution analysis, how parent-child relationships work across resolution levels, and how the compactCells and uncompactCells functions reduce redundant spatial representations. Includes interactive browser demos and practical code examples.

Learn how to use H3's gridDisk, gridRing, and gridDistance functions to model service areas, accessibility zones, and multi-source catchment overlap. Includes interactive browser-based demos with step-by-step code.

Learn how to aggregate point data into hexagonal density maps using H3 and Leaflet. This tutorial covers spatial binning, choropleth colouring, power-scaled colour ramps, and interactive multi-resolution analysis — all running in the browser.

A reflective piece on how large language models represent place: the difference between spatial and platial knowledge, what LLMs do well (cultural associations, character, narrative), what they get wrong (boundaries, recency, under-represented places), and how to build applications that use this capability honestly.

A practical guide to using DuckDB's spatial extension for geospatial analysis. Covers installing the extension, running ST_Within and ST_Distance queries over large Parquet datasets, integrating with Python and the broader data ecosystem, and comparing the approach to traditional spatial database setups.

An introduction to the cloud-native geospatial stack: GeoParquet for vector data, Cloud Optimized GeoTIFFs (COGs) for raster data, and the SpatioTemporal Asset Catalog (STAC) specification for discovery. Covers practical Python examples using rio-cogeo, pystac-client, and geopandas with GeoParquet.

A practical guide to building spatial ETL (extract, transform, load) pipelines using GeoPandas and Shapely. Covers reading and writing spatial formats, geometry validation and repair, coordinate reference system management, spatial joins, and outputting clean data to PostGIS or GeoParquet.

Introducing Chora, the first Python library to model the human experience of place. Built on rigorous theory from GIScience, cognitive geography, and social physics, Chora provides tools for processing GPS traces, detecting routines, mapping emotions, and understanding places as lived experiences rather than coordinate pairs.

Spatial Narrative is a high-performance Rust library for modelling, indexing, and analysing events that unfold across geographic space and chronological time. Built for researchers, digital humanists, and data scientists, it provides spatial indexing, movement analysis, named entity recognition, and multi-format I/O.

An overview of our W2GIS 2025 paper analysing diabetes-related hospitalisations and deaths in Mexico from 2005–2022, using the marginalization index to understand how social inequalities shape health outcomes.

An extended reflection on the difference between the spatial and the platial, why it matters for data, design, and everyday life, and how embracing both can transform how we map the world.

This hands-on tutorial introduces H3, Uber's open-source hexagonal grid system that's transforming spatial analysis. Learn why hexagons outperform traditional grids, set up H3 in JavaScript, and build interactive mapping applications with step-by-step code examples.