Landslide Risk Assessment in Eastern Kentucky, USA: Developing a Regional Scale, Limited Resource Approach

Rapidly changing remote sensing technologies (lidar, aerial photography, satellites) provide opportunities to improve regional-scale landslide risk mapping. However, data limitations regarding hazard and exposure influence how is calculated. To develop assessments for a landslide-prone region of eastern Kentucky, USA, we assessed modeling applicability using variable quality data. First, used equation that incorporated the as logistic regression susceptibility model geomorphic variables derived from lidar Susceptibility calculated probability occurrence. The included population, roads, railroads, land class. Our vulnerability value was assumed equal one (worst-case scenario degree loss) consequence economic cost. Results indicate 64.1 percent study area classified moderate high socioeconomic risk. more data-limited approach, 30 m slope-angle map input simplified slope-based approach show distribution less uniform, with large areas over-and under-prediction. Changes in inputs result significant changes maps demonstrate broad range modelling approaches.