2022
DOI: 10.1007/s11629-022-7487-2
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Disaster risk reduction in mountain areas: a research overview

Abstract: This paper gives an account of the diverse dimensions of research on disaster risk reduction in mountain regions derived from an open call of the Journal of Mountain Science that brought 21 contributions. This special issue includes topics as diverse as landslide dynamics and mechanisms, landslide inventories and landslide susceptibility models, insights to landslide hazards and disasters and mitigation measures, disaster response and disaster risk reduction. The overall structure of the… Show more

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Cited by 6 publications
(2 citation statements)
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“…Mountainscapes face multiple challenges, not only for their propensity to disaster risk and increased rate of geological hazards occurring in the mountain en-vironment-i.e., mass wasting, snow avalanche, flash flooding-induced glacial ablation, rock fall, 0 °C isotherm rise to high altitude, fires, volcanic eruptions, and forest dieback (Alcántara-Ayala et al, 2022b) but also for their intrinsic contentious community's dynamics (Debarbieux & Rudaz, 2010).…”
Section: Transdisciplinary Implications and Theoretical Approachesmentioning
confidence: 99%
“…Mountainscapes face multiple challenges, not only for their propensity to disaster risk and increased rate of geological hazards occurring in the mountain en-vironment-i.e., mass wasting, snow avalanche, flash flooding-induced glacial ablation, rock fall, 0 °C isotherm rise to high altitude, fires, volcanic eruptions, and forest dieback (Alcántara-Ayala et al, 2022b) but also for their intrinsic contentious community's dynamics (Debarbieux & Rudaz, 2010).…”
Section: Transdisciplinary Implications and Theoretical Approachesmentioning
confidence: 99%
“…This method focuses on building the functional relationship between landslide environmental variables and existing landslide inventories, and further realize the quantitative or qualitative assessment of the spatial possibility of landslide occurrence under a set of geological/ geographical environmental conditions (Guzzetti et al, 2005;2006a;2006b;Reichenbach et al, 2018). SLSM can be used to effectively predict and identify locations prone to landslides on the regional scale (Alcántara-Ayala et al, 2022), and its results can provide indispensable information for various tasks, such as landslide risk assessment, formulation of disaster reduction measures, and land use planning (van Westen et al, 2008;Erener et al, 2016;Huang et al, 2019;Zhang et al, 2022). In recent years, it has gradually become a hot topic of geological hazard research on a global scale Huang et al, 2021a).…”
Section: Introductionmentioning
confidence: 99%