mapbox/robosat
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
This project helps urban planners, cartographers, and environmental analysts automatically identify and map real-world features like buildings, roads, and water bodies from aerial and satellite imagery. You provide raw satellite or aerial images, and it generates clean, simplified GeoJSON polygons of the identified features. It is ideal for anyone who needs to create or update geographic data from overhead imagery efficiently.
2,052 stars. No commits in the last 6 months.
Use this if you need to extract specific geographic features from aerial or satellite images to generate precise vector data for mapping or analysis.
Not ideal if you're looking for a user-friendly, point-and-click desktop application or if you need to process highly obscure or nuanced features not typically found in open-source mapping datasets.
Stars
2,052
Forks
388
Language
Python
License
MIT
Category
Last pushed
Aug 27, 2020
Commits (30d)
0
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