Geodatabase and Automation Code Used for Past and Real-Time Dynamic Landslide Hazard Maps in Eastern Kentucky

We developed spatiotemporal landslide hazard maps (LHMs) using soil, hydrologic, and geomorphic parameters from the subaerial infinite slope factor of safety (FS) equation under unsaturated conditions. Soil properties were sourced from the NRCS WSS, while geomorphic variables were derived from a 1.5 m LiDAR-based DEM and ArcGIS Online. Soil moisture from Hydrus-1D, driven by precipitation and evapotranspiration (ET) data from Irrigation Manager, introduced temporal variability. Validation against known landslide sites demonstrated FS accuracy both spatially and temporally, despite some false positives. To reduce false positives and enhance slope stability representation, novel depth-to-bedrock (DTB) and soil root cohesion maps were incorporated into the FS equation. The workflow was automated using Python, leveraging 72-hour National Weather Service (NWS) forecast data to enable real-time landslide hazard prediction.