Abstract
Decision-making plays a key role in reducing landslide risk and preventing natural disasters. Land management, recovery of degraded lands, urban planning, and environmental protection in general are fundamental for mitigating landslide hazard and risk. Here, we present a GIS-based multi-scale approach to highlight where and when a country is affected by a high probability of landslide occurrence. In the first step, a landslide human exposure equation is developed considering the landslide susceptibility triggered by rain as hazard, and the population density as exposed factor. The output, from this overview analysis, is a global GIS layer expressing the number of potentially affected people by month, where the monthly rain is used to weight the landslide hazard. As following step, Logistic Regression (LR) analysis was implemented at a national and local level. The Receiver Operating Characteristic indicator is used to understand the goodness of a LR model. The LR models are defined by a dependent variable, presence–absence of landslide points, versus a set of independent environmental variables. The results demonstrate the relevance of a multi-scale approach, at national level the biophysical variables are able to detect landslide hotspot areas, while at sub-regional level geomorphological aspects, like land cover, topographic wetness, and local climatic condition have greater explanatory power.
Highlights
Over the last decades, the frequency of landslides has increased (Lee et al 2021) due to increasing human use of the environment (Fell 2018) by communities with a lack of environmental knowledge or loss of cultural heritage (Harmsworth and Raynor 2005; Pradhan et al 2011; Hadji et al 2013; Pourghasemi et al 2019; Anis et al 2019)
This paper aims to highlight where and when people could be affected by a landslide, considering monthly time granularity in order to facilitate a landslide Disaster Risk Reduction (DRR) process
In the first step the output is an exposure map based on a combination of hazard and presence of people.In the second and third steps, the analysis considers landslide hazards at national and sub-national levels without crossing the result with the population
Summary
The frequency of landslides has increased (Lee et al 2021) due to increasing human use of the environment (Fell 2018) by communities with a lack of environmental knowledge or loss of cultural heritage (Harmsworth and Raynor 2005; Pradhan et al 2011; Hadji et al 2013; Pourghasemi et al 2019; Anis et al 2019). Land cover change dynamics such as deforestation and expansion of human settlements in exposed areas have defined a new risk aspect (Brander et al 2018; Karim et al 2019; Hadji et al 2013). Fast economic changes define a spread of urban and agricultural land use to support a growing population, resulting in more people being exposed to hazards (Smith 2003). Forest and landscape restoration are not often considered for supporting local communities to produce ecological benefits and avoid landside events (Paudyal et al 2017), and fast economicdemographic growth generally leads to an increase in environmental hazards such as landslides due to a no planned urbanization (Cui et al 2019). Anthropogenic influences on the environment is sometimes the primary cause of a landslide activation, dramatic land cover changes, alteration of morphological aspects, and hydrological changes are all disturbances that increase landslide risk (Jaboyedoff et al 2018)
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