22. Development of a methodology for landslip potential mapping in the Rhondda Valley

Siddle, H. J.; Jones, D.; Payne, H. R.

doi:10.1680/ssedaa.16606.0023

Cited by 23 publications

(12 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to Varnes (1984), landslide hazard in a given area can be assessed in terms of probability of occurrence of a potentially damaging landslide event within a specified period. Both intrinsic and extrinsic variables affect landslide hazards (Siddle et al, 1991;Wu and Sidle, 1995;Atkinson and Massari, 1998;Dai et al, 2001;Çevik and Topal, 2003). Intrinsic variables determining hazards include bedrock geology, topography, soil depth, soil type, slope gradient, slope aspect, slope curvature, elevation, engineering properties of the slope material, land use pattern, and drainage patterns.…”

Section: Introductionmentioning

confidence: 99%

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

et al. 2008

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 99%

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

et al. 2008

View full text Add to dashboard Cite

“…Mainly based on field geomorphological evidence, some maps are either simple inventories of past events (Highland, 1997;Soldati, 1999), often developed in isopleth maps (Wright et al, 1974;DeGraff, 1985;Guzzetti et al, 1994), or are direct geomorphological maps of landslide-prone areas whose quality strongly depends on the investigator's ability to identify potential slope failures (Humbert, 1977;Dumas et al, 1984;Kienholz et al, 1984;Zimmerman et al, 1986). In order to overcome partly the problem of subjectivity inherent in geomorphological mapping, semi-quantitative hazard maps use a more systematic frame where spatial units of varying nature (catchment and slope unit) are ranked into classes of relative landslide susceptibility on the basis of their environmental characteristics (Hutchinson and Chandler, 1991;Siddle et al, 1991;Moon et al, 1992;Fell et al, 1996) and where GIS and statistical analysis may already be invoked (Carrara et al, 1977(Carrara et al, , 1991Irigaray et al, 1999). Such a statistics-oriented approach finally leads to fully quantitative maps that locate future landslide occurrence as a result of a GIS-based multivariate statistical analysis (Rezig et al, 1996;Leroi, 1997).…”

Section: Introductionmentioning

confidence: 99%

Mapping landslide susceptibility from small datasets: A case study in the Pays de Herve (E Belgium)

Demoulin

Chung

2007

Geomorphology

View full text Add to dashboard Cite

A landslide susceptibility map is proposed for the Pays de Herve (E Belgium), where large landslides affect Cretaceous clay outcrop areas. Based on a Bayesian approach, this GIS-supported probabilistic map identifies the areas most susceptible to deep landslides. The database is comprised of the source areas of ten pre-existing landslides (i.e. a sample of 154 grid cells) and of six environmental data layers, namely lithology, proximity to active faults, slope angle and aspect, elevation and distance to the nearest valley-floor. A 30-m-resolution DEM from the Belgian National Geographical Institute is used for the analysis. Owing to the small size of the sample, a special cross-validation procedure of the susceptibility map is performed, which uses in an iterative way each of the landslides to test the predictive power of the map derived from the other landslides. Four different sets of variables are used to produce four susceptibility maps, whose prediction curves are compared. While the prediction rates associated with the models not involving the "proximity to active fault" criterion are comparable to those of the models considering this variable, strong weaknesses inherent in the fault data on which the latter rely suggest that the final susceptibility map should be based on a model that excludes any reference to fault. This highlights the difference between a triggering factor and determining factors, and in the same time broadens the scope of the produced map. A single reactivated slide is also used to test the possibility of predicting future reactivation of existing landslides in the area. Finally, the need for geomorphological control over the mathematical treatment is underlined in order to obtain realistic prediction maps.

show abstract

“…The basic types of qualitative methods use landslide index to identify areas with similar geological and geomorphologic characteristics that are susceptible to landslides. Moreover, there are qualitative methodologies which use weighting and rating procedures and these are known as semi-quantitative methods (Hutchinson and Chandler 1991;Siddle et al 1991;Moon et al 1992;Fell et al 1996;Ayalew and Yamagishi 2005). Such kinds of methodologies are the analytic hierarchy process (AHP) (Saaty 1980;Barredo et al 2000;Yalcin 2008) and the weighted linear combination (WLC) (Ayalew et al 2004a, b;Ayalew and Yamagishi 2005).…”

mentioning

confidence: 99%

Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece

Kouli¹,

Loupasakis

Soupios³

et al. 2009

Nat Hazards

102

View full text Add to dashboard Cite

The central part of Rethymnon Prefecture, Crete Island, suffers from severe landslide phenomena because of its geological and geomorphological settings alternated by the human activities. The main landslide preparatory and triggering causal factors are considered to be the ground conditions (lithology), geomorphological processes (fluvial erosion, etc.), and the man-made actions (excavations, loading etc.). The purpose of this study is to develop a decision support and continuous monitoring system of the area by composing landslide hazard and risk maps. For that reason, several approaches of the weighted linear combination (WLC), a semi-quantitative hazard analysis method, were adopted in a Geographic Information Systems (GIS) environment. The results were validated using a pre-existing landslide database enriched with new landslide locations mapped through image interpretation of a processed IKONOS satellite image. The validation results showed that the WLC method coupled with remote sensing (RS) and GIS techniques can support engineering geological studies concerning landslide vulnerability of hazardous areas.

show abstract

22. Development of a methodology for landslip potential mapping in the Rhondda Valley

Cited by 23 publications

References 0 publications

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence

Mapping landslide susceptibility from small datasets: A case study in the Pays de Herve (E Belgium)

Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece

Contact Info

Product

Resources

About