GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region

Kamp, Ulrich; Growley, Benjamin J.; Khattak, Ghazanfar A.; Owen, Lewis A.

doi:10.1016/j.geomorph.2008.03.003

Cited by 383 publications

(269 citation statements)

References 58 publications

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“…AUC indicates the area between the horizontal axis and the curve, which can be used to evaluate the performance of models, and its value ranges between 0.5 and 1 (Song et al 2012). The higher the percentage of the area below the curve, the better is the prediction (Kamp et al 2008). The AUC in Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, the weight of the importance degree of various factors can be obtained, which provide basis for the choice of the best available solutions (Saaty 1997). So far, the AHP method has been widely used to landslide study (Tang et al 2011a;Yoshimatsu and Abe 2006;Kamp et al 2008). In our study, the AHP method was used to determine the factor weights, which indicate the importance degree of causative factors to landslide occurrence.…”

Section: Factor-weighted Overlaymentioning

confidence: 99%

“…In our study, the AHP method was used to determine the factor weights, which indicate the importance degree of causative factors to landslide occurrence. AHP method applies a one-level weighting system developed by collecting expert opinions (Kamp et al 2008), in this case, our experience during the urgent field survey after the Lushan earthquake. The results of the judgment matrix and optimized factor weights are listed in Table 2.…”

Section: Factor-weighted Overlaymentioning

confidence: 99%

“…Qualitative methods mainly refer to site analysis and overlay analysis of thematic maps (for example, geomorphological and geological characteristics) based on expert experience (Anbalagan and Singh 1996;Ayalew et al 2004). Quantitative methods mainly refer to various statistical analyses (Carrara et al 1991;Tang et al 2011a;Yoshimatsu and Abe 2006;Kamp et al 2008), such as artificial neural network (ANN) (Lee and Evangelista 2006;Yilmaz 2010), support vector machine (SVM) (Yao et al 2008;Yilmaz 2010;Xu et al 2012), Bayesian Network (Song et al 2012) and Logistic Regression (Dong et al 2011;Nefeslioglu et al 2006;Xu et al 2013a, b). These methods have different characteristics and adaptability for various environmental conditions of different regions (Tangestani 2009;Mohammady et al 2012;Ozdemir and Altural 2013).…”

Section: Introductionmentioning

confidence: 99%

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Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

et al. 2014

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The Lushan earthquake with magnitude M s 7.0 (M w 6.6, USGS) in Sichuan Province, China, triggered a large number of landslides, which seriously aggravated the earthquake's destructive consequences. This paper mainly focuses on the methodology of the urgent landslide susceptibility assessment right after the earthquake. The detailed landslide inventory (including 5,688 landslides) is prepared by means of urgent postearthquake landslide field survey, landslide remote sensing interpretation of multi-source remote sensing images including high-resolution unmanned aerial vehicle images and historical landslide archives. Ten remarkable causative factors for landslide occurrence have been selected to conduct the landslide susceptibility assessment, including earthquake intensity, landslide density and slope gradient. An integration assessment approach is developed to facilitate the effective urgent post-earthquake landslide susceptibility assessment using three methods: factor sensitivity analysis, analytical hierarchy process and factor-weighted overlay. Such integration can effectively reduce the subjectivity and uncertainty resulting from using single method. The validation evaluation using the area under curve suggests the landslide susceptibility assessment results have satisfactory accuracy, and the suggested methodology is effective for the urgent post-earthquake landslide susceptibility assessment. The study results reveal that earthquake intensity and slope gradient are the two most important causative factors for post-earthquake landslide occurrence in the Lushan earthquake-impacted area. The dominant slope gradient and slope aspect with relatively higher landslide frequency are 45°-50°and south-east direction, respectively. The intense earthquake impact increased the dominant slope gradient of 123Nat Hazards (2015) 75:2467-2487 DOI 10.1007/s11069-014-1441 landslide spatial distribution, and the thrust campaign of seismogenic fault with strike NE-SW made south-east direction as the dominant slope aspect of the landslide spatial distribution. The locations with very high and high landslide susceptibility are mainly distributed in the regions with higher earthquake intensity and adverse terrain conditions, such as Shuangshi town and Longmen town of Lushan county and Muping town of Baoxing county. The study results are expected to provide a beneficial reference for the landslide prevention and infrastructure reconstruction after the Lushan earthquake.

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Section: Resultsmentioning

confidence: 99%

Section: Factor-weighted Overlaymentioning

confidence: 99%

Section: Factor-weighted Overlaymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

et al. 2014

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“…), allows susceptibility maps to be produced quite quickly (e.g. Parise, 2001;Moreias, 2005;Fall et al, 2006;Kamp et al, 2008). Most of the research on susceptibility mapping of debris flows has been developed at a small scale (e.g.…”

Section: Scientific Backgroundmentioning

confidence: 99%

The contribution of geomorphological mapping to sediment transfer evaluation in small alpine catchments

et al. 2010

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The assessment of sediment transfer processes is necessary to understand the hydro-geomorphological functioning of small alpine watersheds prone to channelised debris flows because their occurrence often depends on the amount of debris available in the gully systems. Therefore, sediment budgets should be studied through the identification of erosion, transport and deposition processes. Sediment transfer processes were investigated in a small catchment by field measurements and, more specifically, through the application of a process-based geomorphological mapping method. The proposed methodology is based on data directly derived from GIS analysis using high-resolution DEM, field measurements and aerial photograph interpretations. It has been conceived to estimate sediment transfer dynamics, taking into account the role of different sediment stores in the torrential system. The proposed geomorphological mapping methodology is quite innovative in comparison with most legend systems that are not adequate for mapping comprehensively active and complex geomorphological systems such as debris-flow catchments. Maps representing the various sediment storages and their relationships can be used for hydro-geomorphological hazard mitigation.

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A GIS Anchored Technique for Social Utility Hotspot Detection

Chakraborty¹,

Mandal

Patra³

et al. 2017

Hybrid Intelligence for Image Analysis and Understanding

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GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region

Cited by 383 publications

References 58 publications

Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

Urgent landslide susceptibility assessment in the 2013 Lushan earthquake-impacted area, Sichuan Province, China

The contribution of geomorphological mapping to sediment transfer evaluation in small alpine catchments

A GIS Anchored Technique for Social Utility Hotspot Detection

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