Earthquake-Landslide Susceptibility is a geospatial assessment methodology that quantifies and maps the likelihood of landslide occurrence triggered by seismic activity across a defined geographic area. This GIS use case integrates multiple layers of geospatial data — including slope gradient, lithology, fault proximity, land cover, soil type, and historical seismic records — to produce probabilistic susceptibility models that identify high-risk zones before disaster events occur.

Using spatial analysis tools within GIS platforms such as ArcGIS or QGIS, analysts apply techniques including weighted overlay analysis, logistic regression, and machine learning algorithms to correlate terrain characteristics with documented earthquake-induced landslide inventories. Remote sensing data from satellite imagery and LiDAR-derived digital elevation models further enhance the accuracy of these geospatial workflows.

The practical benefits are substantial. Emergency management agencies leverage susceptibility mapping for land-use planning, infrastructure siting, and evacuation route optimization. Engineers use the outputs to inform slope stabilization decisions, while disaster risk reduction professionals integrate the results into early warning systems. Ultimately, earthquake-landslide susceptibility mapping transforms complex multi-variable geospatial data into actionable intelligence that protects lives, assets, and critical infrastructure in seismically active regions.