Journal ArticleDOI
Landslide prediction, monitoring and early warning: a concise review of state-of-the-art
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TLDR
In this article, the authors reviewed the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed.Abstract:
Landslide is one of the repeated geological hazards during rainy season, which causes fatalities, damage to property and economic losses in Korea. Landslides are responsible for at least 17% of all fatalities from natural hazards worldwide, and nearly 25% of annual casualties caused by natural hazards in Korea. Due to global climate change, the frequency of landslide occurrence has been increased and subsequently, the losses and damages associated with landslides also have been increased. Therefore, accurate prediction of landslide occurrence, and monitoring and early warning for ground movements are very important tasks to reduce the damages and losses caused by landslides. Various studies on landslide prediction and reduction in landslide damage have been performed and consequently, much of the recent progress has been in these areas. In particular, the application of information and geospatial technologies such as remote sensing and geographic information systems (GIS) has greatly contributed to landslide hazard assessment studies over recent years. In this paper, the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed. Especially, this paper focused on the evaluation of the landslide susceptibility using probabilistic approach and physically based method, runout evaluation using volume based model and dynamic model, in situ ground based monitoring techniques, remote sensing techniques for landslide monitoring, and landslide early warning using rainfall and physical thresholds.read more
Citations
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Monitoring Landslides and Tectonic Motions with the Permanent Scatterers Technique
TL;DR: In this paper, the evolution of the Ancona landslide (central Italy) was analyzed by processing 61 ERS images acquired in the time span between June 1992 and December 2000.
Journal ArticleDOI
Geographical landslide early warning systems
Fausto Guzzetti,Stefano Luigi Gariano,Silvia Peruccacci,Maria Teresa Brunetti,Ivan Marchesini,Mauro Rossi,Massimo Melillo +6 more
TL;DR: In this paper, a critical analysis of nine main assumptions that form the rationale for landslide forecasting and early warning is performed, and the authors conclude that operational forecast of weather-induced landslides is feasible, and it can help reduce landslide risk.
Journal ArticleDOI
Monitoring strategies for local landslide early warning systems
TL;DR: The description and the analysis of the monitoring strategies implemented within local landslide early warning systems (Lo-LEWS) operational all around the world are described and a description of the most used monitoring parameters and instruments for issuing warnings is presented.
Journal ArticleDOI
Rainfall Induced Landslide Studies in Indian Himalayan Region: A Critical Review
TL;DR: A review of landslide studies conducted in this region is therefore important to provide a general picture of the state-of-the-art, a reference point for researchers and practitioners working in the region for the first time, and a summary of the improvements most urgently needed to better address landslide hazard research and management.
Journal ArticleDOI
Landslide mapping with remote sensing: challenges and opportunities
TL;DR: It is expected that the accuracy and applicability of LMRS could be greatly improved, by exploiting big data, utilizing the deep learning technique, and modelling the surface spatial structure of the landslide.
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