Codes for Probabilistic Post-Fire Shallow Landslide Susceptibility Modeling Considering Spatiotemporal Land Cover Uncertainties: A Case of January 2025 Palisades Wildfire in Southern California

Probabilistic, physics-based modeling of post-fire shallow-landslide susceptibility and its uncertainty.

Core pieces: RFHydrorealization.py — generates random fields of post-fire hydraulic conductivity RFroot.py — generates random fields of post-fire root cohesion Main_SF_para_prob_eff.m — MATLAB model for shallow-landslide susceptibility (factor of safety and failure probability)

Inputs: Place required geospatial inputs in RasterT_Palisad4_SpatialJoin6_TableToExcel.xlsx derive from ArcGIS Pro

Quick start:

1. Generate hydraulic conductivity random fields RFHydrorealization.py produces ensembles of post-fire hydraulic conductivity (or multipliers) over the study grid.
2. Generate root cohesion random fields RFroot.py produces ensembles of post-fire root cohesion (or multipliers) that evolve over time.
3. Run the physical model in MATLAB Open Main_SF_para_prob_eff.m, and set the paths.

Outputs: Fs maps per time step and ensemble member