Definition of Environmental Indicators for a Fast Estimation of Landslide Risk at National Scale

Abstract

The purpose of this paper is to propose a new set of environmental indicators for the fast estimation of landslide risk over very wide areas. Using Italy (301,340 km2) as a test case, landslide susceptibility maps and soil sealing/land consumption maps were combined to derive a spatially distributed indicator (LRI—landslide risk index), then an aggregation was performed using Italian municipalities as basic spatial units. Two indicators were defined, namely ALR (averaged landslide risk) and TLR (total landslide risk). All data were processed using GIS programs. Conceptually, landslide susceptibility maps account for landslide hazard while soil sealing maps account for the spatial distribution of anthropic elements exposed to risk (including buildings, infrastructure, and services). The indexes quantify how much the two issues overlap, producing a relevant risk and can be used to evaluate how each municipality has been prudent in planning sustainable urban growth to cope with landslide risk. The proposed indexes are indicators that are simple to understand, can be adapted to various contexts and at various scales, and could be periodically updated, with very low effort, making use of the products of ongoing governmental monitoring programs of Italian environment. Of course, the indicators represent an oversimplification of the complexity of landslide risk, but this is the first time that a landslide risk indicator has been defined in Italy at the national scale, starting from landslide susceptibility maps (although Italy is one of the European countries most affected by hydro-geological hazards) and, more in general, the first time that land consumption maps are integrated into a landslide risk assessment.

Impact of Urban Expansion on Rain Island Effect in Jinan City, North China

“…Rapid urbanization has led to serious urban problems, such as urban waterlogging, landslide hazard and environmental degradation, which threaten social stability, economic development and human health [19]. Land urbanization changes the regional hydrological conditions and reduces the stability of slopes, increasing the severity and frequency of natural disasters [20,21]. From 2003 to 2014, there were 288,946 places with geological disasters (including landslides, ground cracks and land subsidence) that caused economic losses of about USD 870 million and 9560 casualties in China [22].…”

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

“…Last, the risk values were compared with two different databases of national risk indicators; for this validation phase, the outcome analyzed was the risk to buildings because both risk indicators do not report information about land use risk, while they provide data about buildings; indeed, the ISPRA indicators clearly show the number of buildings for each landslide hazard zone. Likewise, the indices proposed by Segoni and Caleca. (2021) were computed on the basis of the urbanized areas, which can be undoubtedly correlated to the exposure to building risk.…”

“…The other set of indicators employed was the one proposed by Segoni and Caleca. (2021), who created indices by overlaying in a GIS environment a susceptibility map (expressing the spatial probability of landslide occurrence) and the nation-wide soil sealing monitoring data (classifying as "1" the urbanized areas and as "0" the natural and seminatural areas).…”

“…In the last two decades, many attempts have been made to quantify landslide risk on various geographic scales (Catani et al, 2005;Remondo et al, 2005;van Westen et al, 2006;Zêzere et al, 2007;Lu et al, 2014b;Uzielli et al, 2015a;Uzielli et al, 2015b;Peng et al, 2015;Guo et al, 2020;Huang et al, 2020;Caleca et al, 2022); however, due to the lack of complete data or inability to obtain them, landslide risk studies can be based on indicator definitions (Abella and Van Westen, 2007;Guillard-Gonçalves et al, 2015;de Almeida et al, 2016;Trigila et al, 2018;Pereira et al, 2020;Segoni and Caleca, 2021).…”

A methodological approach of QRA for slow-moving landslides at a regional scale

“…entire nations or regions), QRA is hampered by the difficulty of gathering complete and homogeneous datasets and the impossibility of applying refined methodologies. In such cases, landslide risk studies usually rely on the definition of simplified indicators (Guillard-Gonçalves et al 2015 ; de Almeida et al 2016 ; Pereira et al 2020 ; Iadanza et al 2021 ; Segoni and Caleca 2021 ), which have the advantage of being very easy to apply, update and disseminate, but from a scientific point of view, they represent an oversimplification of a full QRA procedure.…”