How can data be translated into decisions in crisis contexts?

Since 2023, the National Council for Scientific Research – Lebanon (CNRS-L) has been leading advanced national efforts in war damage monitoring, leveraging AI and Earth Observation to generate timely, reliable, and actionable geospatial intelligence.

This example from Bint Jbeil illustrates the integration of 10 m optical imagery and SAR data to assess damage across urban areas, with clear classification of destruction levels:

🔴 Total destruction

🟡 Partial damage

These outputs are further validated and calibrated using high-resolution imagery, ensuring a high level of accuracy and consistency, and enabling their integration into national Damage and Needs Assessments (RDNA).

This approach supports the production of evidence-based spatial data to inform rapid assessments, prioritization, and recovery planning, aligning with international frameworks on disaster risk reduction and resilience building.

Disclaimer: The analysis relies on a CORINE-derived urban mask, excluding certain land-use classes from the estimates.