Advancing global live fuel moisture mapping through multi-sensor data assimilation

Title
Advancing global live fuel moisture mapping through multi-sensor data assimilation
Report
Date Published
07/2025
Series/Collection
ESA Contract Report
Document Number
4000144712/24/I-DT-bgh
Author
Siham El Garroussi
Patricia de Rosnay
Sebastien Garrigues
David Fairbairn
Joe McNorton
Francesca Di Giuseppe
Abstract This deliverable outlines the methodology and results of Task 2 of Fuelity project, which focused on integrating Earth Observation data into the ECMWF land data assimilation system (LDAS) to constrain live fuel moisture content (LFMC) estimates. The aim is to support a high-resolution, observation-informed global LFMC reanalysis. Enhancements to ECMWF’s ecLand system include targeted modifications to the Simplified Extended Kalman Filter to assimilate L-band Vegetation Optical Depth, Solar-Induced Fluorescence, and ASCAT backscatter data, thereby improving estimates of Leaf Area Index and soil moisture, which underpin LFMC. A machine learning-based post-assimilation bias correction further refines the LAI inputs. Evaluation shows improved seasonal vegetation dynamics and realistic LFMC spatial and temporal patterns. The system successfully captured canopy loss during the 2021 Evia wildfire, demonstrating its potential for operational fire monitoring and risk assessment.
URL https://www.ecmwf.int/en/elibrary/81671-advancing-global-live-fuel-moisture-mapping-through-multi-sensor-data
DOI 10.21957/0bb27c6524
Download citation