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Título
Improving Fire Severity Analysis in Mediterranean Environments: A Comparative Study of eeMETRIC and SSEBop Landsat-Based Evapotranspiration Models
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Remote Sensing
Número de la revista
2
Cita Bibliográfica
Quintano, C., Fernández-Manso, A., Fernández-Guisuraga, J. M., & Roberts, D. A. (2024). Improving Fire Severity Analysis in Mediterranean Environments: A Comparative Study of eeMETRIC and SSEBop Landsat-Based Evapotranspiration Models. Remote Sensing, 16(2), Article e361. https://doi.org/10.3390/RS16020361
Editorial
MDPI
Fecha
2024
Resumen
[EN] Wildfires represent a significant threat to both ecosystems and human assets in Mediterranean countries, where fire occurrence is frequent and often devastating. Accurate assessments of the initial fire severity are required for management and mitigation efforts of the negative impacts of fire. Evapotranspiration (ET) is a crucial hydrological process that links vegetation health and water availability, making it a valuable indicator for understanding fire dynamics and ecosystem recovery after wildfires. This study uses the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) and Operational Simplified Surface Energy Balance (SSEBop) ET models based on Landsat imagery to estimate fire severity in five large forest fires that occurred in Spain and Portugal in 2022 from two perspectives: uni- and bi-temporal (post/pre-fire ratio). Using-fine-spatial resolution ET is particularly relevant for heterogeneous Mediterranean landscapes with different vegetation types and water availability. ET was significantly affected by fire severity according to eeMETRIC (F > 431.35; p-value < 0.001) and SSEBop (F > 373.83; p-value < 0.001) metrics, with reductions of 61.46% and 63.92%, respectively, after the wildfire event. A Random Forest machine learning algorithm was used to predict fire severity. We achieved higher accuracy (0.60 < Kappa < 0.67) when employing both ET models (eeMETRIC and SSEBop) as predictors compared to utilizing the conventional differenced Normalized Burn Ratio (dNBR) index, which resulted in a Kappa value of 0.46. We conclude that both fine resolution ET models are valid to be used as indicators of fire severity in Mediterranean countries. This research highlights the importance of Landsat-based ET models as accurate tools to improve the initial analysis of fire severity in Mediterranean countries.
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Peer review
SI
ID proyecto
- info:eu-repo/grantAgreement/AEI/Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia/PID2022-139156OB-C21/ES/Susceptibilidad y vulnerabilidad del paisaje frente a megaincendios severos en el eje atlántico-mediterráneo: soluciones basadas en la naturaleza para una gestión proactiva/LANDSUSFIRE
- info:eu-repo/grantAgreement/Junta de Castilla y León//LE005P20/ES/Vulnerabilidad de la interfaz urbano-forestal y eficacia de las medidas de restauración tras incendio en áreas propensas al fuego de castilla y león. Aplicaciones a la gestión pre y post-incendio/WUIFIRECYL
- info:eu-repo/grantAgreement/Portuguese Foundation for Science and Technology//UIDB/04033/2020/PT
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