Early Response of Post-Fire Forest Treatments Across Four Iberian Ecoregions: Indicators to Maximize Its Effectiveness by Remote Sensing

[EN] Remote sensing techniques that use spectral indices (SIs) are essential for monitoring vegetation recovery after wildfires. However, there is a critical gap in the comparability of SI responses across ecoregions due to ecological variability. In this study, a meta-analysis was conducted to eval...

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Detalles Bibliográficos
Autores: Pérez-Romero, Javier|||0000-0002-3105-8956, Blanco-Cano, Laura|||0000-0003-1794-8087, Campo García, Antonio Dámaso Del|||0000-0002-5279-4215, Lucas-Borja, Manuel Esteban, Zema, Demetrio A., Soria, Rocío, Miralles, Isabel, Fernández, Cristina
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/226256
Acceso en línea:https://riunet.upv.es/handle/10251/226256
Access Level:acceso abierto
Palabra clave:Wildfires
Post-fire management
Vegetation indices
Restoration strategies
Fire severity
Descripción
Sumario:[EN] Remote sensing techniques that use spectral indices (SIs) are essential for monitoring vegetation recovery after wildfires. However, there is a critical gap in the comparability of SI responses across ecoregions due to ecological variability. In this study, a meta-analysis was conducted to evaluate the capacity of different SIs (GCI, MSI, NBR, NDVI, NDII, and EVI2) to reflect the effect of post-wildfire emergency works on early recovery of vegetation in four Spanish ecoregions. It compared vegetation regrowth between treated and untreated sites, identifying the most sensitive SI for monitoring this recovery. All indices except EVI2 detected significantly better recovery in treated areas; among these, GCI was the most sensitive and NDII the least. The effect of treatment on recovery measured through SI is influenced by site covariates (fire severity, physiography, post-fire action period, post-fire climate, and edaphic characteristics). Finally, random mixed models showed that annual precipitation lower than 700 mm, diurnal temperature over 21 degrees C, soils with finer texture, and water content under 33% are quantitative limits of the treatment effectiveness on vegetation recovery. Overall, the study highlighted the importance of immediate interventions after fires, especially in the first six months, and advocated context-specific management strategies based on fire severity, ecoregion, soil properties, and climate to optimize vegetation recovery.