Damage assessments are widely used in the humanitarian sector for response planning and aid allocation following natural disasters.

The Damage Assessment solution uses AI models to help identify damaged buildings from high-resolution satellite imagery. The use of assistive AI technology enables human analysts to assess damages significantly faster and cover a much broader impacted area than would be feasible with a manual-only approach. 

This product is built in partnership with Google Research and the United Nations Satellite Center (UNOSAT). It is based on Google’s SKAI model originally developed as a collaborative project of Google Research, the United Nations World Food Program (WFP) Innovation Accelerator,  and InstaDeep‘s AI for Social Good (AI4SG) team.

The solution is live in beta. To learn more, please read our blog post or email disha@unglobalpulse.org.

The Socio-economic Mapping product uses mobile phone data to estimate poverty levels by region. Known as “nowcasting”, this technique helps humanitarian organizations predict areas where people might need food or cash assistance. 

Additionally, by analyzing mobile phone data, such as call patterns and top-up information, DISHA detects major population movements into or out of specific regions. This real-time information assists in quickly locating affected populations during emergencies.

This product is live in beta in the Philippines and being scaled to Indonesia. 

To request a demo of the product, please email disha@unglobalpulse.org.