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Journal ArticleDOI

Landslide hazard and risk zonation—why is it still so difficult?

TLDR
In this paper, the authors review the problem of attempting to quantify landslide risk over larger areas, discussing a number of difficulties related to the generation of landslide inventory maps including information on date, type and volume of the landslide, the determination of its spatial and temporal probability, the modelling of runout and the assessment of landslide vulnerability.
Abstract
The quantification of risk has gained importance in many disciplines, including landslide studies. The literature on landslide risk assessment illustrates the developments which have taken place in the last decade and that quantitative risk assessment is feasible for geotechnical engineering on a site investigation scale and the evaluation of linear features (e.g., pipelines, roads). However, the generation of quantitative risk zonation maps for regulatory and development planning by local authorities still seems a step too far, especially at medium scales (1:10,000–1:50,000). This paper reviews the problem of attempting to quantify landslide risk over larger areas, discussing a number of difficulties related to the generation of landslide inventory maps including information on date, type and volume of the landslide, the determination of its spatial and temporal probability, the modelling of runout and the assessment of landslide vulnerability. An overview of recent developments in the different approaches to landslide hazard and risk zonation at medium scales is given. The paper concludes with a number of new advances and challenges for the future, such as the use of very detailed topographic data, the generation of event-based landslide inventory maps, the use of these maps in spatial-temporal probabilistic modelling and the use of land use and climatic change scenarios in deterministic modelling.

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Citations
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Journal ArticleDOI

Landslide inventory maps: New tools for an old problem

TL;DR: In this article, the authors outline the principles for landslide mapping, and review the conventional methods for the preparation of landslide maps, including geomorphological, event, seasonal, and multi-temporal inventories.
Journal ArticleDOI

Guidelines for landslide susceptibility, hazard and risk zoning for land-use planning

TL;DR: In this article, the authors presented a study of the relationship between geotechnical engineering and geosciences and geophysics at the University of New South Wales and U.S. Geological Survey.
Journal ArticleDOI

Spatial data for landslide susceptibility, hazard, and vulnerability assessment: An overview

TL;DR: In this article, a review of the trends in collecting spatial information on environmental factors with a focus on Digital Elevation Models, geology and soils, geomorphology, land use and elements at risk is given.
Journal ArticleDOI

Use of LIDAR in landslide investigations: a review

TL;DR: A short history of the appraisal of laser scanner technologies in geosciences used for imaging relief by high-resolution digital elevation models (HRDEMs) or 3D models is presented in this paper.
References
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Book ChapterDOI

Multivariate Regression Analysis for Landslide Hazard Zonation

TL;DR: In this paper, the authors use multivariate regression techniques for delineating landslide hazard areas, assuming that future landslides can be predicted by the statistical relationships established between the past landslides and the spatial data set of map patterns.
Journal ArticleDOI

Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain

TL;DR: In this paper, a GIS database was compiled and used to generate mass movement hazard maps at a medium scale (1:25,000) in a high-relief area in central Gran Canaria Island, Spain.
Journal ArticleDOI

Observation and modelling of the Saint-Étienne-de-Tinée landslide using SAR interferometry

TL;DR: In this paper, six different interferograms of the La Clapiere landslide were derived from ERS-1 SAR images during the period Aug. 20-Sept. 4, 1991.
Journal ArticleDOI

Landslide susceptibility analysis using GIS and artificial neural network

TL;DR: In this article, the authors developed landslide susceptibility analysis techniques using an artificial neural network and applied the newly developed techniques to the study area of Yongin in Korea.
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