## 2 Materials and Methods
### Conditioning Factors  
The flood and landslide susceptibility assessment in the Basento basin integrated multiple conditioning factors derived from high-resolution geospatial data and pro-cessed using Geographic Information Systems (GIS) and remote sensing techniques. These factors included Elevation, Slope, Aspect, Relative Elevation, Drainage Network, Land Use, Curve Number (CN), Lithology, Distance from the Drainage Network, and Drainage Density, each playing a crucial role in identifying landslide and flood-prone areas [12; 14; 15]. Slope, Aspect, Relative Elevation, Drainage Network, and Drainage Density were extracted from  
Figure 2: Validation map of historical flood events from multiple data sources. the Digital Terrain Model (DTM) with a pixel size of 20 \(\times\) 20 m using spatial analyst tools available in the ArcGIS 10.3 software. The elevation map was obtained from the official geospatial datasets of the Basilicata Region, specifically from airborne LiDAR surveys and photogrammetric processing. The dataset was resampled to a 20 m resolution, ensuring uniformity across the study area. Before analysis, preprocessing steps such as gap filling, interpolation of NoData values, and edge matching were performed to eliminate inconsistencies between adjacent tiles. The finalized DTM provides fundamental elevation data for calculating derivative topographic parameters. The slope map was derived from the DTM using standard GIS-based gradient calculations; the slope was computed for each cell using a 3 \(\times\) 3 m moving window and the planar method, which identifies the steepest rate of elevation change. The aspect map was computed using the planar method, which identifies the orientation of the maximum slope gradient. Derived from the DTM through standard GIS calculations, the aspect is classified into eight cardinal directions (N, NE, E, SE, S, SW, W, NW). The relative elevation, representing the difference in height between a given location and the nearest drainage point, was computed to assess localized susceptibility. It was determined by subtracting the base level elevation (associated with nearby river channels) from the surface elevation of each pixel. The distance to the drainage network was computed using GIS-based Euclidean distance analysis, assigning each pixel a value corresponding to its shortest distance from the nearest river or stream. In addition to standard Euclidean distance, a flow-path distance approach was also applied, simulating the actual hydraulic connectivity between terrain points and the drainage system. The drainage density was computed by dividing the total stream length within a predefined grid cell by the cell's area, using a moving window analysis in GIS. The resulting map highlights areas with high drainage density, which correspond to regions with more developed fluvial networks and higher flood risk potential. The land use map was obtained from the Regional Spatial Data Infrastructure (RSDI), which provides geospatial datasets for environmental monitoring and spatial planning. The dataset is derived from the CORINE Land Cover 2012 classification at a 1:100,000 scale, offering 44 distinct land cover classes grouped into three hierarchical levels. Figure 3: Validation map of historical landslide events. The geolithological map was implemented using both a 5 m-resolution Digital Elevation Model (DEM) derived from LiDAR data available on the geocortical of the Basilicata Regional Authority ([[http://rsdi.regione.basilicata.it/](http://rsdi.regione.basilicata.it/)]([http://rsdi.regione.basilicata.it/](http://rsdi.regione.basilicata.it/))) (accessed on 2 May 2025) and official topographic maps by the Italian 'Istituto Geografico Militare' (IGM) at a 1:25,000 scale. Geological maps at a 1:50,000 scale and, where the 1:50,000-scale maps are not yet available, geological maps at a 1:100,000 scale, were used to draw the boundaries of the lithological units, together with data from edited or unpublished geological maps at different scales [26].