Search

San Nicola Island, pertaining to the Tremiti Archipelago (Southern Adriatic Sea, Italy), is widely affected by cliff retreat and gravitational phenomena which severely threaten its monumental historical and natural value. In this study, geomorphological features of the area were derived following a stepwise approach, combining multitemporal stereoscopic aerial photo interpretations with morphometric analyses and detailed field surveys. A rockfall susceptibility map was created following a heuristic approach based on morphometric and geothematic parameters, accounting for slope, slope aspect, outcropping lithologies, structural discontinuities density, distance from landslide scarps, and presence of anthropic caves. Cliff sectors set on dolomitic limestones feature the highest susceptibility values, especially along the southeastern sector; medium values, instead, are found along the island flanks and along scarps located within the inner sectors; and the lowest values are detected on summit tabular surfaces. The achieved results were compared with historical maps and seismic data derived from local and national archives and catalogues, respectively. These analyses allowed us to define the role played by litho-structural and tectonic features on landslide occurrence and distribution, and their interplay in driving landscape evolution over centuries. Finally, this work represents a valuable scientific tool to support geomorphological studies for landslide hazard assessment and proper territorial planning in any other small insular areas, showing similar geological–geomorphological features and landscape values. [ABSTRACT FROM AUTHOR]

The paper presents a map of sediment surface distribution and bedforms in the Harle tidal inlet, German Wadden Sea. Data collection, processing, and map editing were realized within the sublittoral mapping program of Lower Saxony national waters carried out by the NLWKN – Coastal Research Station. The map is the result of the combined use of multibeam echosounder, sub-bottom profiler, and ground-truth data. The sediment characterization is achieved by an unsupervised approach using an Object-Based Image Analysis (OBIA) on a normalized backscatter mosaic, verified by nineteen sediment samples. Morphometrical parameters and sub-bottom data provided important information to identify hard substrates and bedforms. [ABSTRACT FROM AUTHOR]