RT info:eu-repo/semantics/article
T1 Vegetation and Soil Fire Damage Analysis Based on Species Distribution Modeling Trained with Multispectral Satellite Data
A1 Quintano Pastor, Carmen
A1 Fernández Manso, Alfonso
A1 Calvo Galván, María Leonor
A1 Roberts, Dar A.
A2 Ecologia
K1 Ecología. Medio ambiente
K1 Soil burn severity
K1 Vegetation burn severity
K1 Burned area
K1 Composite burn index (CBI)
K1 Lland surface temperature (LST)
K1 Sentinel-2
AB Forest managers demand reliable tools to evaluate post-fire vegetation and soil damage. Inthis study, we quantify wildfire damage to vegetation and soil based on the analysis of burn severity,using multitemporal and multispectral satellite data and species distribution models, particularlymaximum entropy (MaxEnt). We studied a mega-wildfire (9000 ha burned) in North-Western Spain,which occurred from 21 to 27 August 2017. Burn severity was measured in the field using thecomposite burn index (CBI). Burn severity of vegetation and soil layers (CBIveg and CBIsoil) was alsodi erentiated. MaxEnt provided the relative contribution of each pre-fire and post-fire input variableon low, moderate and high burn severity levels, as well as on all severity levels combined (burnedarea). In addition, it built continuous suitability surfaces from which the burned surface area andburn severity maps were built. The burned area map achieved a high accuracy level (  = 0.85), butslightly lower accuracy when di erentiating the three burn severity classes (  = 0.81). When the burnseverity map was validated using field CBIveg and CBIsoil values we reached lower   statistic values(0.76 and 0.63, respectively). This study revealed the e ectiveness of the proposed multi-temporalMaxEnt based method to map fire damage accurately in Mediterranean ecosystems, providing keyinformation to forest managers
PB MDPI
SN 2072-4292
LK http://hdl.handle.net/10612/11187
UL http://hdl.handle.net/10612/11187
NO Remote Sensing, 2019, vol. 11, n. 15
NO P. 1-24
DS BULERIA. Repositorio Institucional de la Universidad de León
RD 18-may-2024