In his dissertation, "From Efficient Geomorphological Mapping to Semi-Automated Landslide Detection," Ikram Zangana investigates how high-resolution LiDAR-derived digital terrain models (DTMs) can improve geomorphological mapping and landslide detection in complex middle-mountain landscapes in Germany.
Using study areas in the Jena region and the Swabian Alb, the research combines expert-based GIS mapping, remote sensing, and Geographic Object-Based Image Analysis (GEOBIA) to develop a reproducible workflow that progresses from detailed geomorphological mapping to the semi-automated detection of forest-covered landslides. The workflow is further evaluated for its transferability across different regions.
The findings demonstrate that integrating high-resolution DTM data, geomorphological expertise, and object-based image analysis significantly improves the efficiency, consistency, and practical applicability of geomorphological mapping and landslide inventory generation. The developed workflow provides valuable support for hazard assessment and landscape analysis while contributing to more standardized and reproducible mapping approaches.
The Department of Geography warmly congratulates Ikram Zangana on his successful defense and wishes him all the best for his future academic and professional career!
