Satellite-driven flood, wildfire, and vegetation risk mapping for resilience planning and intervention prioritisation.

WEO's Risk Management platform uses satellite imagery and deep learning to deliver automated, 1-metre-resolution risk assessments across three hazard categories: flood, wildfire, and vegetation (tree fall) risk. For flood risk, the STURM project fuses open Sentinel-1/Sentinel-2 data with crowdsourced street-level inputs and deep learning to achieve sub-pixel urban flood extent and depth mapping. Wildfire and vegetation outputs include fuel-load assessments, land-management prioritisation, and heat-retention mapping. All assessments are delivered without field surveys, at roughly 70% below the cost of laser scanning or aerial surveys, via an annual subscription (EUR 15,000–30,000) that covers a managed, web-based platform requiring no GIS expertise. Target customers include municipalities, regional authorities, utilities, NGOs, asset managers, and insurance/actuarial teams needing scenario-based hazard layers, intervention priority maps, and large-scale risk datasets.
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Ruimtegegevens binnen
Verwerking
Insight Generation

WEO
WEO creates environmental analytics from satellite data using AI to deliver actionable insights for cities, vegetation management and risk reduction. Their solutions support urban resilience, flood and heat risk assessment, and environmental monitoring for public and private stakeholders.
2019
Opgericht
1-10
Teamgrootte
Luxembourg
Land
Converts analysis into context-rich, actionable insights.
Geleverd als
Data Visualisation
Displays data in interactive dashboards, charts, or graphs.