In the RiCoLa project we analyze satellite imagery and digital elevation models (DEMs) to detect past and present river course changes and lake formation caused by the interaction of landslides and the drainage system. DEMs are used to extract a reference drainage network and to mark flow path sections indicating possible past interference of landslides with the drainage system (e.g. very low channel gradients and/or wide valley floors, high spatial heterogeneity of channel metrics). This information is used to analyze the long-term adjustment of the drainage network to landslides, identify past landslide hotspots and to fill data gaps in the subsequent detection of recent landslide-river interference on satellite imagery. Landslides, landslide-dammed lakes and river courses are semi-automatically extracted by applying object-based image analysis (OBIA) to optical satellite imagery (e.g. Landsat, Sentinel-2). River course changes and lake formation are detected and quantified by performing object-based change detection and time-series analysis. Eventually, the data will be combined, evaluated and incorporated into the RiCoLa database on the interaction of landslides with the drainage system.
Major outcomes of the project will be (1) a semi-automated and transferable technique for detection of landslide-induced river course changes and lake formation; (2) an inventory of semi-automatically detected landslide-induced river course changes and lakes; (3) statistics of the occurrence of landslide-induced river course changes and lakes dependent on (a) triggers such as earthquakes and large storm events, (b) causes such as structural weaknesses of valley flanks, and (c) consequential natural hazards.