Habitaq visualises 2.3 billion buildings around the world and colours each one by environmental, social, and economic datasets — heights, density, mixed-use intensity, AirBnB prices, and more.
How it works
Building geometries come from Overture Maps. Per-building metrics are computed within a 500 m radius (density, height diversity, mixed-use). Regional datasets (e.g. AirBnB) are layered in from public sources.
Datasets
Building Height — vertical extent in metres, from Overture/Google 2.5D.
Building Density — number of buildings within a 500 m radius.
Footprint Ratio — share of ground covered by building footprints.
Height Diversity — standard deviation of neighbour heights (σ).
Mixed-Use Index — variety of building classes nearby (0–1).
Eco Index — composite proxy favouring low footprint coverage.
AirBnB Price — nightly price from Inside Airbnb. avg = mean of listings within 500 m; real = snapped to nearest building only.
POI Density (300m) — count of points-of-interest within 300 m, from Overture Maps places.
Transit Distance — metres to the nearest train/metro/bus stop, from OpenStreetMap (lower is better).
Population Density — residents within ~100 m of each building, from WorldPop 2020 (constrained 100 m grid).
Green Space Distance — metres to the nearest park, garden, forest or wood from OpenStreetMap (lower is greener).
Traffic Noise Proxy — weighted score from nearby OSM road segments × highway-class weight (motorway=10 → residential=1) within 200 m. Lower is quieter.
Building Age — year built, from the Spanish cadastre (INSPIRE Buildings) joined onto Overture buildings via H3 cell.
Built by Konstantin Varik. Currently covers Lisbon, Berlin, New York City, all of Spain, all of France, and all of the United Kingdom (~99 million buildings) — global rollout in progress.