Landslides are among the most prevalent geohazards worldwide, leading to significant loss of human lives and extensive property damage. Italy stands out as one of the European countries most frequently affected by landslides, resulting in significant consequences for its community. Despite numerous studies on landslides across Italy, including efforts in susceptibility modeling and forecasting, a comprehensive national-scale q...

Regional- and national-scale landslide warning systems are usually based on rainfall thresholds that forecast the possibility of landslide occurrence over wide spatial units called alert zones (AZs). This work proposes a substantial improvement of the state-of-the-art by combining the rainfall threshold outcomes with a set of spatially explicit risk indicators aggregated at the municipality level. The combination of these two...

The use of machine learning models for landslide susceptibility mapping is widespread but limited to spatial prediction. The potential of employing these techniques in spatiotemporal landslide forecasting remains largely unexplored. To address this gap, this study introduces an innovative dynamic (i.e., space–time-dependent) application of the random forest algorithm for evaluating landslide hazard (i.e., spatiotemporal probab...

This study proposes an innovative approach to develop a regional-scale landslide forecasting model based on rainfall thresholds optimized for operational early warning. In particular, it addresses two main issues that usually hinder the operational implementation of this kind of models: (i) the excessive number of false alarms, resulting in civil protection system activation without any real need, and (ii) the validation proce...

Landslides represent a serious worldwide hazard, especially in Italy, where exposure to hydrogeological risk is very high; for this reason, a landslide quantitative risk assessment (QRA) is crucial for risk management and for planning mitigation measures. In this study, we present and describe a novel methodological approach of QRA for slow-moving landslides, aiming at national replicability. This procedure has been applied at...

Intensity–duration rainfall thresholds are commonly used in regional-scale landslide warning systems. In this manuscript, 3D thresholds are defined also considering the mean rainfall amount fallen in each alert zone (MeAR, mean areal rainfall) in Emilia Romagna region (Northern Italy). In the proposed 3D approach, thresholds are represented by a plane instead of a line, and the third dimension allows to indirectly account for...

The literature about landslide susceptibility mapping is rich of works focusing on improving or comparing the algorithms used for the modeling, but to our knowledge, a sensitivity analysis on the use of geological information has never been performed, and a standard method to input geological maps into susceptibility assessments has never been established. This point is crucial, especially when working on wide and complex area...

Landslide susceptibility assessment is vital for landslide risk management and urban planning, and the scientific community is continuously proposing new approaches to map landslide susceptibility, especially by hybridizing state-of-the-art models and by proposing new ones. A common practice in landslide susceptibility studies is to compare (two or more) different models in terms of AUC (area under ROC curve) to assess which o...