Crown fire damage is a mixture of three principal fire-related components:charred material,scorched foliage,and unaltered green canopy.This study estimated the abundance of these physical alterations in two immediate ...Crown fire damage is a mixture of three principal fire-related components:charred material,scorched foliage,and unaltered green canopy.This study estimated the abundance of these physical alterations in two immediate post-fire Mediterranean forest contexts(Portugal and Italy)by applying linear spectral mixture analysis(LSMA)on Sentinel-2 imagery.The tree crowns fire damage was subsequently mapped,integrating fractional abundance information in a random forest(RF)algorithm,comparing the accuracy resulting from the adoption of generic or image spectral libraries as the primary investigative goal.Although image-derived endmembers resulted in more effectiveness in terms of fire-related components abundance quantification(LMSAderived RMSE<0.1),the F-scores always were≥90%whether generic endmembers or image endmembers derived information was employed.The environmental heterogeneity of the two study areas affected the fire severity gradients,with a prevalence of the charred(PT)(45–46%)and green class(IT)(44–53%).Post-fire temporal monitoring was initialized by applying the proposed strategies,and the preliminary results showed a positive recovery trend in forest vegetation from the first year following the fire event,with a reduced charcoal predominance and an increasing proportion of green components.展开更多
基金funded by the European Commission and the Regione Calabria with the POR Calabria FESR FSE 2014-2020source[CUP C39B18000070002]Joao M.N.Silva was funded by the Forest Research Centre,a research unit funded by Fundacao para a Ciência e a Tecnologia IP(FCT),Portugal(UIDB/00239/2020)by the project FireCast–Forecasting fire probability and characteristics for a habitable pyro environment,funded by FCT(PCIF/GRF/0204/2017).
文摘Crown fire damage is a mixture of three principal fire-related components:charred material,scorched foliage,and unaltered green canopy.This study estimated the abundance of these physical alterations in two immediate post-fire Mediterranean forest contexts(Portugal and Italy)by applying linear spectral mixture analysis(LSMA)on Sentinel-2 imagery.The tree crowns fire damage was subsequently mapped,integrating fractional abundance information in a random forest(RF)algorithm,comparing the accuracy resulting from the adoption of generic or image spectral libraries as the primary investigative goal.Although image-derived endmembers resulted in more effectiveness in terms of fire-related components abundance quantification(LMSAderived RMSE<0.1),the F-scores always were≥90%whether generic endmembers or image endmembers derived information was employed.The environmental heterogeneity of the two study areas affected the fire severity gradients,with a prevalence of the charred(PT)(45–46%)and green class(IT)(44–53%).Post-fire temporal monitoring was initialized by applying the proposed strategies,and the preliminary results showed a positive recovery trend in forest vegetation from the first year following the fire event,with a reduced charcoal predominance and an increasing proportion of green components.
