Open Cities AI Challenge Dataset

This dataset was developed as part of a challenge to segment building footprints from aerial imagery. The goal of the challenge was to accelerate the development of more accurate, relevant, and usable open-source AI models to support mapping for disaster risk management in African cities [Read more about the challenge]. The data consists of drone imagery from 10 different cities and regions across Africa

Documentation

• Link

Tutorials

• Segmenting Buildings for Disaster Resilience - Benchmark by Azavea

Tools & Applications

• Open Cities AI Challenge benchmark model
• Open Cities AI Challenge Winning Models

Publications

• The Open Cities AI Challenge by Dave Luo
• Meet the Winner of the Open Cities AI Challenge by Greg Lipstein

Creator & Contact

• Global Facility for Disaster Reduction and Recovery (GFDRR)
• njones@worldbankgroup.org

License

• ODbL-1.0

Citation & DOI

GFDRR Labs (2020). "Open Cities AI Challenge Dataset", Version 1.0, Radiant MLHub. [Date Accessed] https://doi.org/10.34911/rdnt.f94cxb