Live fuel moisture Content mapping in the Mediterranean basin using random forests and combining MODIS spectral and thermal data

Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limit...

Descripción completa

Detalles Bibliográficos
Autores: Cunill Camprubí, Àngel, González-Moreno, Pablo, Resco de Dios, Víctor
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/83606
Acceso en línea:https://doi.org/10.3390/rs14133162
http://hdl.handle.net/10459.1/83606
Access Level:acceso abierto
Palabra clave:Wildfire
MODIS
Spectral indices
Land surface temperature
Random forests
Live fuel moisture content
Boscos i silvicultura
Boscos i silvicultura -- Humitat
Descripción
Sumario:Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in vegetation structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored the potential of random forests (RF) to estimate LFMC at the subcontinental scale in the Mediterranean basin wildland. We built RF models (LFMCRF) using a combination of MODIS spectral bands, vegetation indices, surface temperature, and the day of year as predictors. We used the Globe-LFMC and the Catalan LFMC monitoring program databases as ground-truth samples (10,374 samples). LFMCRF was calibrated with samples collected between 2000 and 2014 and validated with samples from 2015 to 2019, with overall root mean square errors (RMSE) of 19.9% and 16.4%, respectively, which were lower than current approaches based on radiative transfer models (RMSE ~74–78%). We used our approach to generate a public database with weekly LFMC maps across the Mediterranean basin.