Millions of people worldwide live in poorly mapped areas. When conflict, disease, or natural disaster strikes, the humanitarian community often scrambles to generate map data as it responds. The The Missing Maps project aims to solve this problem with an ambitious effort to put the world’s most vulnerable populations on the map.
Brighter areas are more densely mapped but don’t always correspond with population size
But where to start mapping? Mapbox is applying the same analysis used by our data team to help prioritize Missing Maps work. Our code looks for areas with low feature counts in OpenStreetMap but high satellite imagery data density (a rough proxy for lots of buildings and roads) to identify under-mapped areas. We can then compare the resulting locations with various vulnerability metrics like public health data, infrastructure quality, food security, and disaster preparedness.
As an example, we identified these map tiles from Karachi, Mumbai, Surat, and Yangon as good Missing Maps tracing candidates:
Lots of roads and buildings, but not many are traced in OpenStreetMap (purple)