How can landslide risk maps be validated? Potential solutions with open-source databases

Abstract

Landslides are a worldwide natural hazard that cause more damage and casualties than other hazards. Therefore, social and economic losses can be reduced through a landslide quantitative risk assessment (QRA). In the last two decades, many attempts of quantitative analysis on various scales have been performed; nevertheless, the major difficulty of QRA lies in how precise and reliable the assessment should have to be useful. For this reason, in this paper, we analyzed different freely available datasets and some products of previous research to assess the soundness of the outcomes performed by a recent QRA of slow-moving landslides in the Arno River basin (Central Italy). The validation process was carried out by comparing the abovementioned datasets and two components of the selected QRA (hazard and risk). The obtained results showed a robust correlation between most of the testing dataset and risk components, highlighting the accuracy of the selected QRA.

Tracking a Decade of Hydrogeological Emergencies in Italian Municipalities

“…However, the public release of this dataset may also provide benefits to other fields of research. For instance, [31,32] discussed the lack of standards and comprehensive datasets to validate risk maps; [22,[32][33][34][35] highlighted the need for updated and homogeneous datasets to calibrate hazard models; [36] stressed the complexity of acquiring detailed information combining sufficient detail with wide temporal and spatial coverage at the same time; and [37,38] identified some spatiotemporal patterns in societal risk that could be compared with the information contained in this dataset. Finally, the dataset and derived research products could be useful to raise awareness and engagement of the general public toward the hydrogeological risks affecting Italy [39].…”

Integrated Approach for Landslide Risk Assessment Using Geoinformation Tools and Field Data in Hindukush Mountain Ranges, Northern Pakistan

“…Similarly, Phander and Teru (Figure 12) are the other populated areas that lie in the high-risk class. The quantitative validation of a risk index is often ignored due to the lack of high-quality data [111] and, therefore, could not be included in this study; however, it shall be accomplished in future quantitative landslide risk assessment studies in the region. This study is an intermediate methodology between purely qualitative and quantitative approaches, including quanitative data, and providing relative risk levels.…”

The Impact of Hydrogeological Events on Firms: Evidence from Italy

“…In recent regional-and national-scale studies, the datasets derived by SECAGN have proven to be in accordance with observed reality (Segoni and Caleca 2021;Caleca et al, 2022;Franceschini et al, 2022). However, SECAGN suffers from some setbacks, which need to be properly accounted for during research development.…”