Deterministic Modelling in Gis-Based Landslide Hazard Assessment

Terlien, M.T.J.; Westen, C.J. van; Asch, Th.W.J. van

doi:10.1007/978-94-015-8404-3_4

Cited by 120 publications

(75 citation statements)

References 1 publication

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“…For both aspects, expert knowledge is essential in making the selection of relevant indicator maps for the index. To get a better idea of the importance of these factors, physical models for estimating slope instability (Terlien et al 1995;van Westen and Terlien 1996;Moon and Blackstock 2004) can be used to derive trends. These deterministic models require a number of input maps, related to soil depth, soil strength, soil-water conditions and slope angles.…”

Section: National Landslide Risk Assessment Model Design Issues and Omentioning

confidence: 99%

Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation

Abella

Westen²

2007

Landslides

180

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This paper explains the procedure for the generation of a landslide risk index map at national level in Cuba, using a semiquantitative model with ten indicator maps and a cell size of 90× 90 m. The model was designed and implemented using spatial multi-criteria evaluation techniques in a GIS system. Each indicator was processed, analysed and standardised according to its contribution to hazard and vulnerability. The indicators were weighted using direct, pairwise comparison and rank-ordering weighting methods, and weights were combined to obtain the final landslide risk index map. The results were analysed per physiographic region and administrative units at provincial and municipal levels. The Sierra Maestra mountain system was found to have the largest concentration of high landslide risk index values while the Nipe-Cristal-Baracoa system has the highest absolute values, although they are more dispersed. The results obtained allow designing an appropriated landslide risk mitigation plan at national level and to link the information to the national hurricane early warning system, allowing also warning and evacuation for landslide-prone areas.

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Section: National Landslide Risk Assessment Model Design Issues and Omentioning

confidence: 99%

Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation

Abella

Westen²

2007

Landslides

180

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“…Generally, geotechnical process methods are developed from slope stability analyses and are applicable for site-specific landslides or when the ground conditions are quite uniform in the study area. Also, this method requires the landslide types to be known and relatively easy to analyze (Terlien et al, 1995;Wu and Sidle, 1995), and hence it is seldom used in large-scale landslide susceptibility mapping. In qualitative methods, landslide experts select landslide controlling factors and com-bine these factors into a susceptibility map, based on their knowledge and experience of landslide investigation.…”

Section: Introductionmentioning

confidence: 99%

Landslide susceptibility mapping on a global scale using the method of logistic regression

Lin

Wang

2017

Nat. Hazards Earth Syst. Sci.

121

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Abstract. This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC) curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC) was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

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“…In the deterministic methods, on the other hand, the causal factors are expressed in algebraic terms to determine the factor of safety (Terlien et al 1995;Wu and Sidle 1995;Borga et al 1998;D'Odorico and Fagherazzi 2003;Godt et al 2008;Salciarini et al 2008;Harp et al 2009). These approaches utilize a large amount of detailed geo-mechanical and hydrological parameters derived from field and laboratory experiments, and computer tool-based modelling.…”

Section: Introductionmentioning

confidence: 99%

Deterministic slope failure hazard assessment in a model catchment and its replication in neighbourhood terrain

Acharya

Yatabe

Bhandary

et al. 2014

Geomatics, Natural Hazards and Risk

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In this work, we prepare and replicate a deterministic slope failure hazard model in small-scale catchments of tertiary sedimentary terrain of Niihama city in western Japan. It is generally difficult to replicate a deterministic model from one catchment to another due to lack of exactly similar geo-mechanical and hydrological parameters. To overcome this problem, discriminant function modelling was done with the deterministic slope failure hazard model and the DEM-based causal factors of slope failure, which yielded an empirical parametric relationship or a discriminant function equation. This parametric relationship was used to predict the slope failure hazard index in a total of 40 target catchments in the study area. From ROC plots, the prediction rate between 0.719-0.814 and 0.704-0.805 was obtained with inventories of September and October slope failures, respectively. This means September slope failures were better predicted than October slope failures by approximately 1%. The results show that the prediction of the slope failure hazard index is possible, even in a small catchment scale, in similar geophysical settings. Moreover, the replication of the deterministic model through discriminant function modelling was found to be successful in predicting typhoon rainfall-induced slope failures with moderate to good accuracy without any use of geo-mechanical and hydrological parameters.

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Deterministic Modelling in Gis-Based Landslide Hazard Assessment

Cited by 120 publications

References 1 publication

Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation

Generation of a landslide risk index map for Cuba using spatial multi-criteria evaluation

Landslide susceptibility mapping on a global scale using the method of logistic regression

Deterministic slope failure hazard assessment in a model catchment and its replication in neighbourhood terrain

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