Remote Sensing and Multi-Level Data Analyses for Hum na Sutli Landslide Impact Assessment in a Changing Climate

In Northern Croatia, the stability of slopes is increasingly compromised by a combination of anthropogenic pressures, seismic activity, and climate-driven changes in precipitation patterns. This study presents an integrated, multi-level investigation of the complex, composite Hum na Sutli landslide to characterize its failure mechanism, identify cascading triggering factors, and provide a quantitative basis for impact assessment and mitigation plan development. By reviewing the existing relevant (geo) data, information on the landslide’s historical background and triggering factors was gathered. Material properties were determined in the field and confirmed via laboratory tests. With the integration of new data and multilevel methodology, including unmanned aerial vehicle (UAV) derived light detection and ranging data (LiDAR) data and Electrical Resistivity Tomography (ERT), the characterization of a landslide type was conducted, and an initial landslide map and model were created. Analyzing precipitation data from over the last 25 years provided insights into the area’s changing precipitation trends, highlighting the importance of continuous monitoring of this site. The presented research results for the Hum na Sutli landslide provide a viable basis for mitigation plan creation. Furthermore, laboratory results establish a correlation in landslide susceptibility between two regional units: the Golubovec and Vrbova formations, based on their similar clay-silt-sand compositions and observed failure mechanisms. The research presented here highlights the benefits of multi-level data analysis, emphasizing the integration of existing data with new high-resolution remote sensing data in order to develop a rapid and reliable initial landslide model.