Landslide susceptibility mapping of the Sea to Sky transportation corridor, British Columbia, Canada: comparison of two methods

Blais-Stevens, A; Behnia, Pouran; Kremer, Marian; Page, A; Kung, R; Bonham-Carter, Graeme

doi:10.1007/s10064-012-0421-z

Cited by 27 publications

(16 citation statements)

References 33 publications

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“…When comparing results from this study with the other fuzzy logic approaches from literature showed that knowledge-based approaches (Champati ray et al 2007;Blais-Stevens et al 2012) determined fuzzy membership values simply based on subjective judgement (Bonham-Carter 1994), and therefore the quality of the landslide models is strongly dependent on those experts and is very subjective. In the case of data-driven approaches, fuzzy membership values were obtained by normalizing the frequency-ratio values for each conditioning factor (Lee 2007;Pradhan 2010;Pradhan 2011b).…”

Section: Discussionmentioning

confidence: 99%

“…Good overview of these methods with their disadvantages and advantages can be seen in Guzzetti et al (1999), Dai et al (2002), Chacon et al (2006), and Corominas and Moya (2008). In recent years, new methods such as fuzzy logic (Lee 2007;Wan et al 2008;Kanungo et al 2009;Tangestani 2009;Biswajeet & Saied 2010;Srivastava et al 2010;Pradhan 2011aPradhan , 2011bBlais-Stevens et al 2012;Kayastha 2012;Pourghasemi et al 2012a;Tien Bui et al 2012e;Tien Bui, Ho, et al 2013;Zare et al 2013), neurofuzzy (Pradhan et al 2010b;Vahidnia et al 2010;Oh & Pradhan 2011;Sezer et al 2011;Tien Bui et al 2011), and data mining approaches methods (Melchiorre et al 2008;Nefeslioglu et al 2008;Yao et al 2008;Saito et al 2009;Yilmaz 2009;Pradhan & Lee 2010;Yeon et al 2010;Marjanovic et al 2011;Melchiorre et al 2011;Yilmaz & Kaynar 2011;Ballabio & Sterlacchini 2012;Pradhan 2013;Tien Bui et al 2012a, 2012cWan et al 2012;Xu et al 2012) have been widely used in landslide mapping. In general, the prediction capability of the new models possesses better than those obtained from...…”

Section: Introductionmentioning

confidence: 99%

“…Since fuzzy set theory does not provide the functions for generating fuzzy membership values of landslide conditioning factors and theirs classes, therefore various methods have been proposed to address this issue. Champati ray et al (2007) and Blais-Stevens et al (2012) used expert knowledge; Lee (2007), Pradhan (2010Pradhan ( , 2011aPradhan ( , 2011b, and Pourghasemi et al (2012a) used the frequency ratio; Ercanoglu and Gokceoglu (2004) and Kanungo et al (2008Kanungo et al ( , 2009) used the Cosine amplitude; Chung and Fabbri (2008) and Dewitte et al (2010) used the likelihood ratio function. Similarly, Pradhan et al (2010b), Sezer et al (2011), and Tien Bui et al (2012d) used the neural network method.…”

Section: Introductionmentioning

confidence: 99%

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A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam)

Bui

Pradhan

Revhaug

et al. 2013

Geomatics, Natural Hazards and Risk

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(2015) A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam), Geomatics, Natural Hazards and Risk, 6:3, 243-271, DOI: 10.1080/19475705.2013 The main objective of this study is to investigate potential application of an integrated evidential belief function (EBF)-based fuzzy logic model for spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam). First, a landslide inventory map was constructed from various sources. Then the landslide inventory map was randomly partitioned as a ratio of 70/30 for training and validation of the models, respectively. Second, six landslide conditioning factors (slope angle, slope aspect, lithology, distance to faults, soil type, land use) were prepared and fuzzy membership values for these factors classes were estimated using the EBF. Subsequently, fuzzy operators were used to generate landslide susceptibility maps. Finally, the susceptibility maps were validated and compared using the validation dataset. The results show that the lowest prediction capability is the fuzzy SUM (76.6%). The prediction capability is almost the same for the fuzzy PRODUCT and fuzzy GAMMA models (79.6%). Compared to the frequency-ratio based fuzzy logic models, the EBF-based fuzzy logic models showed better result in both the success rate and prediction rate. The results from this study may be useful for local planner in areas prone to landslides. The modelling approach can be applied for other areas.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam)

Bui

Pradhan

Revhaug

et al. 2013

Geomatics, Natural Hazards and Risk

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show abstract

“…Landslide susceptibility is defined as the likelihood of a landslide occurring in an area on the basis of the local terrain and environmental conditions (Brabb, 1984;Guzzetti et al, 2005). Landslide susceptibility zonation (LSZ) is important for landslide mitigation plans, since it supplies planners and decision makers with essential information (Van Den Eeckhaut et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Effective surveyed area and its role in statistical landslide susceptibility assessments

Bornaetxea

Rossi

Marchesini

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. Geomorphological field mapping is a conventional method used to prepare landslide inventories. The approach is typically hampered by the accessibility and visibility, during field campaigns for landslide mapping, of the different portions of the study area. Statistical significance of landslide susceptibility maps can be significantly reduced if the classification algorithm is trained in unsurveyed regions of the study area, for which landslide absence is typically assumed, while ignorance about landslide presence should actually be acknowledged. We compare different landslide susceptibility zonations obtained by training the classification model either in the entire study area or in the only portion of the area that was actually surveyed, which we name effective surveyed area. The latter was delineated by an automatic procedure specifically devised for the purpose, which uses information gathered during surveys, along with landslide locations. The method was tested in Gipuzkoa Province (Basque Country), north of the Iberian Peninsula, where digital thematic maps were available and a landslide survey was performed. We prepared the landslide susceptibility maps and the associated uncertainty within a logistic regression model, using both slope units and regular grid cells as the reference mapping unit. Results indicate that the use of effective surveyed area for landslide susceptibility zonation is a valid approach that minimises the limitations stemming from unsurveyed regions at landslide mapping time. Use of slope units as mapping units, instead of grid cells, mitigates the uncertainties introduced by training the automatic classifier within the entire study area. Our method pertains to data preparation and, as such, the relevance of our conclusions is not limited to the logistic regression but are valid for virtually all the existing multivariate landslide susceptibility models.

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“…In common with dam break floods produced by failure of other types of natural impoundment, such break‐outs produce characteristic V‐shaped breaches in the rim, with low width/depth ratios, typically in the range of 3–5 (MacDonald and Langridge‐Monopolis, ). Such hydrologically open caldera lakes are candidates for producing further break‐out floods due to either temporary blocking of their outlets by volcanic activity (Belousov and Belousov, ), volcano‐tectonic uplift of the lake floor (including subaqueous dome growth) (Mann et al ., ), explosive displacement of water through the outlet (Cronin et al ., ; Egorov, ; Kilgour et al ., ; Watts and Waythomas, ), or landslide‐induced tsunami waves (Walder et al ., ; Blais‐Stevens et al ., ). The sudden release of huge volume of water stored in temporarily elevated caldera lakes are a recurrent feature of volcanic environments due to the case with which outlet channels are blocked by and re‐cut through unwelded pyroclastic deposits (Waythomas et al ., ; Manville et al ., ; Hogdson and Nairn, ; Manville and Wilson, ; Manville, ).…”

Section: Introductionmentioning

confidence: 99%

Simulating floods triggered by volcanic activities in the Cheon‐ji caldera lake for hazards and risk analysis

Lee

Kim²,

Kim³

2016

J Flood Risk Management

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Many volcanic craters and calderas are filled with large amounts of water that can pose significant flood hazards to downstream communities due to their high elevation and the potential for catastrophic releases of water. Explosive volcanic activity, uplift of the lake floor and landslides directed into the lake are some of the possible scenarios that can cause the release of water through a breach. In this paper, we derive a physically based model that uses the mass balance equation to simulate the hydrograph through a breached rim due to water displacement by lake floor uplift or landsliding. The model was applied to the Baekdusan volcano to examine its performance. Then, the hydrograph at the breach of a caldera lake serves as an upstream boundary condition for the subsequent flood‐routing model, FLO‐2D. The FLO‐2D simulation shows that three populated towns are at risk, showing maximum depth up to 10–30 m. The flow converges to the Baishan dam that has a volume capacity of 6.5 km3. The simulation shows the probable inundation zones and maximum depth, and these are to be used for risk assessment.

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Landslide susceptibility mapping of the Sea to Sky transportation corridor, British Columbia, Canada: comparison of two methods

Cited by 27 publications

References 33 publications

A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam)

A novel hybrid evidential belief function-based fuzzy logic model in spatial prediction of rainfall-induced shallow landslides in the Lang Son city area (Vietnam)

Effective surveyed area and its role in statistical landslide susceptibility assessments

Simulating floods triggered by volcanic activities in the Cheon‐ji caldera lake for hazards and risk analysis

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