TL;DR: In this paper, the authors used geomorphological information to assess areas at high landslide hazard, and help mitigate the associated risk, and found that despite the operational and conceptual limitations, landslide hazard assessment may indeed constitute a suitable, cost-effective aid to land-use planning.
TL;DR: In this paper, the authors analyze how earthquakes trigger landslides and highlight research gaps, and suggest pathways toward a more complete understanding of the seismic effects on the Earth's surface, highlighting research gaps.
Abstract: Large earthquakes initiate chains of surface processes that last much longer than the brief moments of strong shaking. Most moderate‐ and large‐magnitude earthquakes trigger landslides, ranging from small failures in the soil cover to massive, devastating rock avalanches. Some landslides dam rivers and impound lakes, which can collapse days to centuries later, and flood mountain valleys for hundreds of kilometers downstream. Landslide deposits on slopes can remobilize during heavy rainfall and evolve into debris flows. Cracks and fractures can form and widen on mountain crests and flanks, promoting increased frequency of landslides that lasts for decades. More gradual impacts involve the flushing of excess debris downstream by rivers, which can generate bank erosion and floodplain accretion as well as channel avulsions that affect flooding frequency, settlements, ecosystems, and infrastructure. Ultimately, earthquake sequences and their geomorphic consequences alter mountain landscapes over both human and geologic time scales. Two recent events have attracted intense research into earthquake‐induced landslides and their consequences: the magnitude M 7.6 Chi‐Chi, Taiwan earthquake of 1999, and the M 7.9 Wenchuan, China earthquake of 2008. Using data and insights from these and several other earthquakes, we analyze how such events initiate processes that change mountain landscapes, highlight research gaps, and suggest pathways toward a more complete understanding of the seismic effects on the Earth's surface.
TL;DR: In this article, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas, manipulated using ArcView GIS.
TL;DR: In this paper, a GIS-aid to the geo-environmental evaluation for urban land-use planning is illustrated for the urban area of Lanzhou City and its vicinity in Northwest China.
TL;DR: 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.