Pre-fire aboveground biomass, estimated from LiDAR, spectral and field inventory data, as a major driver of burn severity in maritime pine (Pinus pinaster) ecosystems

• DOI: 10.1016/j.fecs.2022.100022
• Publication Date: 2022-03-03T01:59:31Z
• Authors: José Manuel Ferná...; Susana Suárez-Seoane; Paulo M. Fernandes; Víctor Fernández-...; Alfonso Fernández...; Carmen Quintano; Leonor Calvo
• Keywords: Understory; Pinus pinaster; Fire regime; Thinning

The characterization of surface and canopy fuel loadings in fire-prone pine ecosystems is critical for understanding fire behavior anticipating the most harmful ecological effects fire. Nevertheless, joint consideration both overstory understory strata burn severity assessments often dismissed. aim this work was to assess role total, pre-fire aboveground biomass (AGB), estimated by means airborne Light Detection Ranging (LiDAR) Landsat data, as drivers a megafire occurred ecosystem dominated Pinus pinaster Ait. western Mediterranean Basin. Total AGB were more accurately (R2 equal 0.72 0.68, respectively) from LiDAR spectral data than ​= ​0.26). Density height percentile metrics several found be important predictors AGB. Burn responded markedly non-linearly total ​0.60) ​0.53) AGB, whereas relationship with weaker ​0.21). plus contribution led highest ability predict (RMSE ​122.46 dNBR scale), instead ​158.41). This study novelty evaluated potential vegetation biophysical property derived LiDAR, field plot inventory predicting severity, separating loads stands. evidenced relationships between distribution stands would allow implementation threshold criteria support decision making treatments designed minimize crown hazard.