Description
Timely spatial data is critical to addressing Africa’s most pressing challenges, yet much of it remains fragmented and inaccessible. This fragmentation drains research resources and forces a reliance on external models that overlook local vulnerabilities. uGAP directly solves this problem: by unifying 100+ African datasets with a Python SDK, it fuses data discovery, processing, and model training into a single, seamless workflow. By eliminating these technical bottlenecks, uGAP empowers local researchers to turn raw data into targeted, community-relevant resilience policies.
Speaker: Ian Ocholla, University of Cape Town
Host: Stephanie Nyairo, Microsoft
See more:
https://www.microsoft.com/en-us/research/video/ugap-a-unified-geospatial-ai-platform-for-african-geographic-data/
https://www.microsoft.com/en-us/research/lab/microsoft-research-lab-africa-nairobi/seminars/