Mapping Your Own World: Open Drones and Localized AI

What if communities could map their own worlds using low-cost drones and open AI models instead of waiting for expensive satellite imagery? In this episode with Leen from HOT ( Humanitarian OpenStreetMap Team) , we explore how they're putting open mapping tools directly into communities' hands—from $500 drones that fly in parallel to create high-resolution imagery across massive areas, to predictive models that speed up feature extraction without replacing human judgment. Key topics: Why local knowledge beats perfect accuracy The drone tasking system: how multiple pilots map 80+ square kilometers simultaneously AI-assisted mapping with humans in the loop at every step Localizing AI models so they actually understand what buildings in Chad or Papua New Guinea look like The platform approach: plugging in models for trees, roads, rooftop material, waste detection, whatever communities need The tension between speed and OpenStreetMap's principles Why mapping is ultimately a power game—and who decides what's on the map

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Mapping Your Own World: Open Drones and Localized AI is an episode from The MapScaping Podcast - GIS, Geospatial, Remote Sensing, earth observation and digital geography by MapScaping.

This episode is 32:43 long.

This episode was published on Dec 18, 2025.

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