SEVESCAN is a research-based platform for automated wildfire severity classification from field photographs, supporting post-fire assessment and remote sensing validation.
Developed by the GEAT research group (Universidad de Leon) in collaboration with MongoDB and Vexiza.
This project has been developed under the Universidad de León Proof of Concept Programme (ULE-PoC 2026), promoted by FEGULEM.