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Identifying Gaps in OpenStreetMap Coverage Through Machine Learning

November 6, 2019·NLT Staff
Identifying Gaps in OpenStreetMap Coverage Through Machine Learning

"Having found our model to work sufficiently well, we apply it to predict OSM building footprint for all of Haiti, and flag cells that are predicted to be fully mapped but are actually not covered by OSM."

This post is by NLT's Chief Scientist and a colleague from GFDRR Labs/World Bank, with contributions from the NLT team.

Map screenshots showing predicted versus actual OpenStreetMap building-footprint coverage in Haiti

Read the full article on Towards Data Science.

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