Improving Spatial Landslide Prediction with 3D Slope Stability Analysis and Genetic Algorithm Optimization: Application to the Oltrepò Pavese

Towards a National-Scale Dataset of Geotechnical and Hydrological Soil Parameters for Shallow Landslide Modeling

One of the main constraints in assessing shallow landslide hazards through physically based models is the need to characterize the geotechnical parameters of the involved materials. Indeed, the quantity and quality of input data are closely related to the reliability of the results of every model used, therefore data acquisition is a critical and time-consuming step in every research activity. In this perspective, we reviewed all official certificates of tests performed through 30 years at the Geotechnics Laboratory of the Earth Science Department (University of Firenze, Firenze, Italy), compiling a dataset in which 380 points are accurately geolocated and provide information about one or more geotechnical parameters used in slope stability modeling. All tests performed in the past (in the framework of previous research programs, agreements of cooperation, or to support didactic activities) were gathered, homogenized, digitalized, and geotagged. The dataset is based on both on-site tests and laboratory tests, it accounts for 40 attributes, among which 13 are descriptive (e.g., lithology or location) and 27 may be of direct interest in slope stability modeling as input parameters. The dataset is made openly available and can be useful for scientists or practitioners committed to landslide modeling.