A Review of Scale Dependency in Landslide Hazard and Risk Analysis

Abstract

Landslides are part of the natural environment and affect economy and communities worldwide at various scales. Consequently, methods of assessing landslide risk depend heavily on specific demands. Within this frame, spatial landslide hazard and risk assessments are an important tool to support local and regional communities. These assessments include hazard and risk analysis, risk perception and a sustainable risk management. In Bíldudalur, Iceland, hazard analysis was performed at 1:5,000 scale and is build on landslide hazard determined by a combination of heuristic analysis, in particular geomorphological assessment, and process modelling. The investigation was focussed on debris flows and rock falls only. Resulting landslide maps give run-out distances of different sized landslide events. This information is assigned to hazard classes expressing through its magnitude the probability of occurrence of a given magnitude within a given region. Risk analysis in Rheinhessen, Germany is based on landslide hazard derived from multivariate statistical analysis at scale 1:25,000. Landslide types were not differentiated specifically, however, most landslides in this region are shallow, translational earth and debris slides and flows. Risk elements were mapped and categorized from aerial photographs and land use plans. Potential damage was calculated as average values based on official German statistics sources. Due to missing information, vulnerability was assigned as 1 (highly vulnerable) -thus analysis returns a worst case scenario. Resulting landslide risk map identifies high risk areas in urban settings. Within their scale of investigation, both approaches demonstrate their importance for prevention strategies, in particular for planning and mitigation purposes. The examples are linked to an overall scheme of landslide risk assessment, which has the potential to include other natural hazards and consequently might lead to a mutli-natural risk assessment.

Analysis of Slope Sensitivity to Landslides by a Transdisciplinary Approach in the Framework of Future Development: The Case of La Trinité in Martinique (French West Indies)

“…The landslide susceptibility, hazard, and risk assessment benefited from a substantial literature review [11,13,15,[57][58][59][60][61]. Landslide susceptibility assessment (LSA) expresses the spatial correlation between predisposing terrain factors (slope, land use, superficial deposits, etc.)…”

“…Landslide susceptibility assessment (LSA) expresses the spatial correlation between predisposing terrain factors (slope, land use, superficial deposits, etc.) and the distribution of observed landslides in a territory [57,62]. The goal is to produce information about the most probable initiation areas (probable failure) and the possible extension (retrogression and downslope run-out of phenomena, [11,15]).…”

Evaluating performance of simplified physically based models for shallow landslide susceptibility

“…ROCs are used to assess the performance of models which provides results assigned to one of two classes. The ROC graph is widely used in many scientific fields, such as medicine (Goodenough et al, 1974), biometrics (Pepe, 2003), and machine learning (Provost and Fawcett, 2001). The ROC graph is a Cartesian plane with the FPR on the x axis and TPR on the y axis.…”

“…Many methods for landslide susceptibility mapping have been developed and can be grouped in two main branches: qualitative and quantitative methods (Glade and Crozier, 2005;Corominas et al, 2014 and references therein).…”

Probabilistic landslide ensemble prediction systems: lessons to be learned from hydrology

“…Landslide prediction at the regional scale is a hot topic within the scientific community as the time-varying aspects of landslide susceptibilities, hazards, and even risks are crucial for emergency response planning and protecting public safety Glade and Crozier, 2015). Further, the number of landslides is assumed to increase due to global change (Crozier, 2010;Gariano et al, 2017;PapathomaKöhle and Glade, 2013).…”