Peter R. Robichaud

An interpretable remote sensing–machine learning framework for wildfire soil burn severity prediction in the northwestern United States

Background Although soil burn severity (SBS) is traditionally mapped post-fire, pre-fire predictive approaches remain limited despite their potential to identify areas at risk of soil degradation, runoff and erosion. Aim To develop a large-scale model for predicting post-fire SBS...