## 1 Introduction  
This section provides an overview of landslides, including their types, causes, and the importance of reliable landslide risk forecasting tools. It also highlights the roles of the IRPI and ISPRA in managing landslide risk. Following this overview, a description of the structure of the work is provided, illustrating how each part contributes to a better understanding of the research. Landslides are one of the most dramatic and, unfortunately, frequent natural disasters, capable of causing significant economic losses and casualties each year. In just a few seconds, they can mobilize large masses of soil and debris, altering the landscape and burying everything in their path. The hazards associated with landslides vary based on their mass and speed. They are categorized into different types depending on factors such as the method of occurrence, the amount of soil and rock displaced, and the resulting damage to the area [1]. To better understand the risks associated with landslides, it is essential to categorize them based on their characteristics. The main types of landslides are as follows:* Landslides of Collapse: These involve large rock masses that detach from a slope, often triggering a chain reaction of additional rock falls. * Sliding Landslides: These occur when the upper layers of soil slide down the slope due to the deeper layers' inability to support their weight and the friction of surface layers and vegetation. * Landslides from Flows: These occur in clayey, muddy, or water-saturated soils, where rocks and organic debris flow downward under the influence of gravity. * Landslips: These refer to very shallow landslides that affect small slopes or involve minimal amounts of rocky material. Understanding these types and mechanisms is essential for assessing risks and implementing effective mitigation strategies. The causes of landslides can be natural or anthropogenic, often a combination of both [2]. Factors such as the volume of water or snow; tree roots stabilizing the soil; composition and structure of rocks and soil; slope; changes in slope stability due to earthquakes or human activities like excavation and construction; and human actions such as deforestation, overbuilding, and urbanization without proper criteria can significantly escalate the risk of landslides, rendering the territory more vulnerable [3]. It is crucial to understand the role of human activities in this process and act responsibly to mitigate these risks [4]. Predicting landslide risks is complex due to the interaction of natural factors and human actions. Research is currently focused on developing models to improve the accuracy of geographical landslide risk prediction. One method to achieve this is by creating susceptibility and hazard maps, which can help predict landslides and implement preventive measures to reduce the risk of damage and human loss [5]. In the international context, an essential aspect of geographical analysis is categorizing territory based on its unique geomorphological characteristics. Geospatial analysis, particularly the creation of maps showing areas vulnerable to flooding, provides a comprehensive understanding of the territory's vulnerability. These maps enable continuous assessment of slope conditions, facilitating proactive actions to mitigate landslide risks. They are created by combining data from various sources, such as topographic maps, satellite images, and field observations. The information identifies vulnerable areas and details the extent of risks to communities, infrastructure, and ecosystems. The challenge lies in maintaining up-to-date and accurate systems based on near real-time data. The creation of these maps involves traditional mapping conducted with geographic information systems technologies [6; 7; 8], which is significantly complemented by advanced artificial intelligence techniques [9; 10; 11]. These techniques play a significant role in enhancing the accuracy and efficiency of the mapping process.