In watershed mountain basins, affected in the last decades by strong rainfall events, the role of debris-flow and debris flood processes was investigated. Morphometric parameters have proven to be useful first-approximation indicators in discriminating those processes, especially in large areas of investigation. Computation of morphometric parameters in 19 watershed mountain basins of the western side valley of the Vallo di Diano intermontane basin (southern Italy) was carried out. This procedure was integrated by a semi-automatic elaboration of the potential susceptibility to debris flows, using Flow-R modelling. This software, providing an empirical model of the preliminary susceptibility assessment at a regional scale, was applied in many countries of the world. The implementation of Flow-R modelling requires a GIS application and some thematic base maps extracted using DEMs analysis. A 5-meter-resolution DEM has been used in order to produce the susceptibility maps of the whole study area, and the results are compared and discussed with the real debris flow/flood events that occurred in 1993, 2005, 2010, and 2017 in the studied area. The results have provided a good reliability of Flow-R modelling within small catchment mountain basins.

The semi-automated extraction of flat surface landforms was carried out, merging a GIS tools application and a geomorphic analysis. The study focuses on seven areas in southern Italy, characterized by different physical landscapes, using a 5 m resolution digital elevation model (DEM). The GIS application allowed the selection of polygonal areas of flat surfaces from diverse arrays of landforms and was implemented using a filtering process to minimize noises. Subsequently, the mean elevation and mean slope of the detected surfaces were extracted and visualized using scatter plots, which helped in determining the elevation ranges and average slope angles for various flat-floored and terraced surfaces. To enhance the reliability of the results, a detailed geomorphic analysis and field survey were conducted to differentiate between fluvial and marine flat surfaces across different physical landscapes. This comprehensive approach included statistical analyses and comparisons with the existing literature to validate the identified flat surfaces, ensuring the accuracy and reliability of the semi-automated extraction procedure. The integration of GIS technology with field investigations not only streamlines the detection of flat landforms but also contributes to a deeper understanding of their geomorphic characteristics, ultimately enhancing geomorphic analysis efficiency.

The semi-automated extraction of landforms using GIS analysis is one of the main topics in computer analyses. The use of digital elevation models (DEMs) in GIS applications makes the extraction and classification procedure of landforms easier and faster. In the present paper, we assess the accuracy of semi-automated landform maps by means of a comparison with hand-made landform maps realized in the Pleistocene Agri intermontane basin (southern Italy). In this study, landform maps at three different scales of 1:50,000, 1:25,000, and 1:10,000 were used to ensure a good level of detail in the spatial distribution of landforms. The semi-automated extraction and classification of landforms was performed using a GIS-related toolbox, which identified ~48 different landform types. Conversely, the hand-made landform map identified ~57 landforms pertaining to various morphogenetic groups, such as structural, fluvial, karst landforms, etc. An overlap of the two landform maps was produced using GIS applications, and a 3D block diagram visualization was realized. A visual inspection of the overlapping maps was conducted using different spatial scales of patch frames and then analyzed to provide information on the accuracy of landform extraction using the implemented tools.