Discover how machine learning is used to identify gaps in OpenStreetMap coverage, specifically in Haiti.
“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 Ran Goldblatt, New Light Technologies, and Nick Jones, GFDRR Labs/World Bank.
Acknowledgments: Thanks to Jenny Mannix and Brad Bottoms at New Light Technologies who contributed to this project.
Contact our team if you are interested in learning more about services like this through a free consultation.
Full Article at TowardsDataScience.com: https://towardsdatascience.com/identifying-gaps-in-openstreetmap-coverage-through-machine-learning-257545c04330
New Light Technologies' groundbreaking study reveals how urban features impact children's mental health and cognition through remote sensing and data...
Explore insights on urban homogenization and heat islands from a collaborative study, shaping cooler cities.
Discover how satellite data innovations are revolutionizing development efforts by providing valuable insights.