scispace - formally typeset
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.

read more

Citations
More filters
Journal ArticleDOI

The influence of the inventory on the determination of the rainfall-induced shallow landslides susceptibility using generalized additive models

TL;DR: In this paper, the authors performed a deep analysis of the role of different landslide inventories on the definition of shallow landslide susceptibility of a particular area, modeled through a data-driven technique (generalized additive model).
Journal ArticleDOI

National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data

TL;DR: The authors investigated the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China and concluded that ignoring landslide inventory-based incompleteness can entail misleading modelling results and that the application of non-linear mixed-effect models can reduce the propagation of such biases into the final results for very large areas.
Journal ArticleDOI

Rainfall and earthquake-induced landslide susceptibility assessment using GIS and Artificial Neural Network

TL;DR: In this article, a GIS-based method for the assessment of landslide susceptibility in a selected area of Qingchuan County in China is proposed by using the back-propagation Artificial Neural Network model (ANN).
Journal ArticleDOI

Detecting and monitoring long-term landslides in urbanized areas with nighttime light data and multi-seasonal Landsat imagery across Taiwan from 1998 to 2017

TL;DR: In this paper, a non-parametric machine-learning classifier, random forest, was used to classify the satellite imagery from the Defense Meteorological Satellite Program (DMSP) and Visible Infrared Imaging Radiometer Suite (VIIRS), with multi-seasonal daytime optical Landsat time-series, and digital elevation data from the Advanced Spaceborne Thermal Emission and Reflection Radiometry (ASTER).
Journal ArticleDOI

Improving sinkhole hazard models incorporating magnitude–frequency relationships and nearest neighbor analysis

TL;DR: In this article, a methodology for elaborating sinkhole hazard models that incorporate the magnitude and frequency relationships of the subsidence process is presented, which can be applied to predict the spatial-temporal probability of events with different magnitudes related to other geomorphic processes (e.g. landslides).
References
More filters
Journal ArticleDOI

Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy

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.
Journal ArticleDOI

The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar

TL;DR: For 11 days in February 2000, the Shuttle Radar Topography Mission (SRTM) successfully recorded by interferometric synthetic aperture radar (InSAR) data of the entire land mass of the earth between 60°N and 57°S.
Book

Geographic Information Systems for Geoscientists: Modelling with GIS

TL;DR: An introduction to GIS and tools for map analysis: map pairs, spatial data models, and more.
Journal ArticleDOI

The Rainfall Intensity - Duration Control of Shallow Landslides and Debris Flows

TL;DR: In this article, rainfall intensities and durations associated with shallow landsliding and debris flow activity suggests a limiting threshold for this type of slope instability, and the limit is defined based on the rainfall intensity and duration.
Book

Landslide hazard zonation: A review of principles and practice

TL;DR: In this paper, the authors give the definitions and principles of landslides, and identify causative conditions and processes (inherent or basic conditions, geology, geomorphology, hydrologic conditions and climate, vegetation, factors that change stress conditions and strength of materials).
Related Papers (5)