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Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China

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Abstract

The main purpose of this paper is to present the use of multi-resource remote sensing data, an incomplete landslide inventory, GIS technique and logistic regression model for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Landslide location polygons were delineated from visual interpretation of aerial photographs, satellite images in high resolutions, and verified by selecting field investigations. Eight factors, including slope angle, slope aspect, elevation, distance from drainages, distance from roads, distance from main faults, seismic intensity and lithology were selected as controlling factors for earthquake-triggered landslide susceptibility mapping. Qualitative susceptibility analyses were carried out using the map overlaying techniques in GIS platform. The validation result showed a success rate of 82.751 % between the susceptibility probability index map and the location of the initial landslide inventory. The predictive rate of 86.930 % was obtained by comparing the additional landslide polygons and the landslide susceptibility probability index map. Both the success rate and the predictive rate show sufficient agreement between the landslide susceptibility map and the existing landslide data, and good predictive power for spatial prediction of the earthquake-triggered landslides.

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References

  • Althuwaynee OF, Pradhan B, Lee S (2012) Application of an evidential belief function model in landslide susceptibility mapping. Comput Geosci 44:120–135. doi:10.1016/j.cageo.2012.3

    Article  Google Scholar 

  • Arora MK, Das Gupta AS, Gupta RP (2004) An artificial neural networks approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley Himalayas. Int J Remote Sens 25(3):559–572. doi:10.1080/0143116031000156819

    Article  Google Scholar 

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65(1–2):15–31. doi:10.1016/j.geomorph.2004.06.010

    Article  Google Scholar 

  • Bednarik M, Magulová B, Matys M, Marschalko M (2010) Landslide susceptibility assessment of the Kraľovany–Liptovský Mikuláš railway case study. Phys Chem Earth Parts A B C 35(3–5):162–171. doi:10.1016/j.pce.2009.12.002

    Article  Google Scholar 

  • Binaghi E, Luzi L, Madella P, Pergalani F, Rampini A (1998) Slope instability zonation: a comparison between certainty factor and fuzzy Dempster–Shafer approaches. Nat Hazards 17(1):77–97. doi:10.1023/A:1008001724538

    Article  Google Scholar 

  • Binaghi E, Boschetti M, Brivio PA, Gallo I, Pergalani F, Rampini A (2004) Prediction of displacements in unstable areas using a neural model. Nat Hazards 32(1):135–154. doi:10.1023/B:NHAZ.0000026796.59079.1a

    Article  Google Scholar 

  • Brenning A (2005) Spatial prediction models for landslide hazards: review, comparison and evaluation. Nat Hazards Earth Syst Sci 5(6):853–862. doi:10.5194/nhess-5-853-2005

    Article  Google Scholar 

  • Bui DT, Pradhan B, Lofman O, Revhaug I, Dick OB (2012) Landslide susceptibility assessment in the Hoa Binh province of Vietnam: a comparison of the Levenberg–Marquardt and Bayesian regularized neural networks. Geomorphology 171–172:12–29. doi:10.1016/j.geomorph.2012.04.023

    Google Scholar 

  • Bui DT, Pradhan B, Lofman O, Revhaug I, Dick ØB (2013) Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province. Vietnam Nat Hazards 66(2):707–730

    Article  Google Scholar 

  • Caniani D, Pascale S, Sdao F, Sole A (2008) Neural networks and landslide susceptibility: a case study of the urban area of Potenza. Nat Hazards 45(1):55–72. doi:10.1007/s11069-007-9169-3

    Article  Google Scholar 

  • Chauhan S, Sharma M, Arora MK, Gupta NK (2010) Landslide susceptibility zonation through ratings derived from artificial neural networks. Int J Appl Earth Obs Geoinf 12(5):340–350. doi:10.1016/j.jag.2010.04.006

    Article  Google Scholar 

  • Chen ZH, Wang JF (2007) Landslide hazard mapping using logistic regression model in Mackenzie Valley. Can Nat Hazards 42(1):75–89. doi:10.1007/s11069-006-9061-6

    Article  Google Scholar 

  • Chung CF, Fabbri AG (2003) Validation of spatial prediction models for landslide hazard mapping. Nat Hazards 30(3):451–472. doi:10.1023/B:NHAZ.0000007172.62651.2b

    Article  Google Scholar 

  • Dahal RK, Hasegawa S, Nonomura A, Yamanaka M, Masuda T, Nishino K (2008a) GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping. Environ Geol 54(2):311–324. doi:10.1007/s00254-007-0818-3

    Article  Google Scholar 

  • Dahal RK, Hasegawa S, Nonoumra A, Yamanaka M, Dhakal S, Paudyal P (2008b) Predictive modelling of rainfall-induced landslide hazard in the Lesser Himalaya of Nepal based on weights-of-evidence. Geomorphology 102(3–4):496–510. doi:10.1016/j.geomorph.2008.05.041

    Article  Google Scholar 

  • Dai FC, Lee CF (2003) A spatiotemporal probabilistic modelling of storm-induced shallow landsliding using aerial photographs and logistic regression. Earth Surf Proc Land 28(5):527–545. doi:10.1002/esp.456

    Article  Google Scholar 

  • Dai FC, Lee CF, Li J, Xu ZW (2001) Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong. Environ Geol 40(3):381–391. doi:10.1007/s002540000163

    Article  Google Scholar 

  • Dai FC, Lee CF, Tham LG, Ng KC, Shum WL (2004) Logistic regression modelling of storm-induced shallow landsliding in time and space on natural terrain of Lantau Island, Hong Kong. Bull Eng Geol Environ 63(4):315–327. doi:10.1007/s10064-004-0245-6

    Article  Google Scholar 

  • Gallus D, Abecker A, Richter D (2008) Classification of Landslide susceptibility in the development of early warning systems. Headway in spatial data handling, In: Lecture notes in geoinformation and cartography 55–75. doi:10.1007/978-3-540-68566-1_4

  • Garcia-Rodriguez MJ, Malpica JA, Benito B, Diaz M (2008) Susceptibility assessment of earthquake-triggered landslides in El Salvador using logistic regression. Geomorphology 95(3–4):172–191. doi:10.1016/j.geomorph.2007.06.001

    Article  Google Scholar 

  • Godt JW, Baum RL, Savage WZ, Salciarini D, Schulz WH, Harp EL (2008) Transient deterministic shallow landslide modeling: requirements for susceptibility and hazard assessments in a GIS framework. Eng Geol 102(3–4):214–226. doi:10.1016/j.enggeo.2008.03.019

    Article  Google Scholar 

  • Gorum T, Gonencgil B, Gokceoglu C, Nefeslioglu HA (2008) Implementation of reconstructed geomorphologic units in landslide susceptibility mapping: the Melen Gorge (NW Turkey). Nat Hazards 46(3):323–351. doi:10.1007/s11069-007-9190-6

    Article  Google Scholar 

  • Gunther A, Thiel C (2009) Combined rock slope stability and shallow landslide susceptibility assessment of the Jasmund Cliff area (Rügen Island, Germany). Nat Hazards Earth Syst Sci 9(3):687–698. doi:10.5194/nhess-10-2197-2010

    Article  Google Scholar 

  • Harp EL, Keefer DK, Sato HP, Yagi H (2011) Landslide inventories: the essential part of seismic landslide hazard analyses. Eng Geol 122(1–2):9–21. doi:10.1016/j.enggeo.2010.06.013

    Article  Google Scholar 

  • Hasegawa S, Dahal RK, Nishimura T, Nonomura A, Yamanaka M (2009) DEM-based analysis of earthquake-induced shallow landslide susceptibility. Geotech Geol Eng 27(3):419–430. doi:10.1007/s10706-008-9242-z

    Article  Google Scholar 

  • Havenith HB, Strom A, Caceres F, Pirard E (2006) Analysis of landslide susceptibility in the Suusamyr region, Tien Shan: statistical and geotechnical Approach. Landslides 3(1):39–50. doi:10.1007/s10346-005-0005-0

    Article  Google Scholar 

  • He YP, Beighley RE (2008) GIS-based regional landslide susceptibility mapping: a case study in southern California. Earth Surf Proc Land 33(3):380–393. doi:10.1002/esp.1562

    Article  Google Scholar 

  • Hong Y, Adler R, Huffman G (2007) Use of satellite remote sensing data in the mapping of global landslide susceptibility. Nat Hazards 43(2):245–256. doi:10.1007/s11069-006-9104-z

    Article  Google Scholar 

  • Irigaray C, Fernandez T, Chacon J (2003) Preliminary rock-slope-susceptibility assessment using GIS and the SMR classification. Nat Hazards 30(3):309–324. doi:10.1023/B:NHAZ.0000007178.44617.c6

    Article  Google Scholar 

  • Keefer DK (1984) Landslides caused by earthquakes. Geol Soc Am Bull 95(4):406–421. doi:10.1130/0016-7606(1984)95<406:LCBE>2.0.CO;2

    Article  Google Scholar 

  • Kouli M, Loupasakis C, Soupios P, Vallianatos F (2010) Landslide hazard zonation in high risk areas of Rethymno Prefecture, Crete Island, Greece. Nat Hazards 52(3):599–621. doi:10.1007/s11069-009-9403-2

    Article  Google Scholar 

  • Lee S (2004) Application of likelihood ratio and logistic regression models to landslide susceptibility mapping using GIS. Environ Manage 34(2):223–232. doi:10.1007/s00267-003-0077-3

    Article  Google Scholar 

  • Liu JG, Mason PJ, Clerici N, Chen S, Davis AM, Miao F, Deng H, Liang L (2003) Landslide hazard assessment in the three Gorges area of the Yangtze River using ASTER imagery. Geoscience and remote sensing symposium, IGARSS ‘03. Proc 2003 IEEE Int 2:1302–1304. doi:10.1109/IGARSS.2003.1294090

    Google Scholar 

  • Lu P, Rosenbaum MS (2003) Artificial neural networks and grey systems for the prediction of slope stability. Nat Hazards 30(3):383–398. doi:10.1023/B:NHAZ.0000007168.00673.27

    Article  Google Scholar 

  • Luzi L, Pergalani F (1999) Slope instability in static and dynamic conditions for urban planning: the ‘Oltre Po Pavese’ case history (Regione Lombardia-Italy). Nat Hazards 20(1):57–82. doi:10.1023/A:1008162814578

    Article  Google Scholar 

  • Magliulo P, Lisio AD, Russo F, Zelano A (2008) Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: a case study in southern Italy. Nat Hazards 47(3):411–435. doi:10.1007/s11069-008-9230-x

    Article  Google Scholar 

  • Marquinez J, Duarte RM, Farias P, Sanchez MJ (2003) Predictive GIS-based model of rockfall activity in mountain cliffs. Nat Hazards 30(3):341–360. doi:10.1023/B:NHAZ.0000007170.21649.e1

    Article  Google Scholar 

  • Marzorati S, Luzi L, Amicis MD (2002) Rock falls induced by earthquakes: a statistical approach. Soil Dyn Earthq Eng 22(7):565–577. doi:10.1016/S0267-7261(02)00036-2

    Article  Google Scholar 

  • Mavrouli O, Corominas J, Wartman J (2009) Methodology to evaluate rock slope stability under seismic conditions at Solà de Santa Coloma, Andorra. Nat Hazards Earth Syst Sci 9(6):1763–1773. doi:10.5194/nhess-9-1763-2009

    Article  Google Scholar 

  • Miles SB, Ho CL (1999) Rigorous landslide hazard zonation using newmark’s method and stochastic ground motion simulation. Soil Dyn Earthq Eng 18(4):305–323. doi:10.1016/S0267-7261(98)00048-7

    Article  Google Scholar 

  • Moon V, Blackstock H (2004) A methodology for assessing landslide hazard using deterministic stability models. Nat Hazards 32(1):111–134. doi:10.1023/B:NHAZ.0000026793.49052.87

    Article  Google Scholar 

  • Msilimba GG, Holmes PJ (2005) A landslide hazard assessment and vulnerability appraisal procedure: Vunguvungu/Banga Catchment, North Malawi. Nat Hazards 34(2):199–216. doi:10.1007/s11069-004-1513-2

    Article  Google Scholar 

  • Nefeslioglu HA, Gokceoglu C, Sonmez H (2008) An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Eng Geol 97(3–4):171–191. doi:10.1016/j.enggeo.2008.01.004

    Article  Google Scholar 

  • Oh HJ, Lee S (2011) Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system. Environ Earth Sci 62(5):935–951. doi:10.1007/s12665-010-0579-2

    Article  Google Scholar 

  • Ozdemir A, Delikanli M (2009) A geotechnical investigation of the retrogressive Yaka Landslide and the debris flow threatening the town of Yaka (Isparta, SW Turkey). Nat Hazards 49(1):113–136. doi:10.1007/s11069-008-9282-y

    Article  Google Scholar 

  • Pandey A, Dabral PP, Chowdary VM, Yadav NK (2008) Landslide hazard zonation using remote sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India. Environ Geol 54(7):1517–1529. doi:10.1007/s00254-007-0933-1

    Article  Google Scholar 

  • Pareek N, Sharma ML, Arora MK (2010) Impact of seismic factors on landslide susceptibility zonation: a case study in part of Indian Himalayas. Landslides 7(2):191–201. doi:10.1007/s10346-009-0192-1

    Article  Google Scholar 

  • Park NW (2010) Application of Dempster-Shafer theory of evidence to GIS-based landslide susceptibility analysis. Environ Earth Sci 62(2):367–376. doi:10.1007/s12665-010-0531-5

    Article  Google Scholar 

  • Pourghasemi HR, Mohammady M, Pradhan B (2012) Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran. Catena 97:71–84. doi:10.1016/j.catena.2012.05.005

    Article  Google Scholar 

  • Pradhan B, Lee S (2007) Utilization of optical remote sensing data and GIS tools for regional landslide hazard analysis using an artificial neural network model. Earth Sci Front 14(6):143–151. doi:10.1016/S1872-5791(08)60008-1

    Article  Google Scholar 

  • Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environ Model Softw 25(6):747–759. doi:10.1016/j.envsoft.2009.10.016

    Article  Google Scholar 

  • Pradhan B, Youssef AM, Varathrajoo R (2010) Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model. Geosp Inf Sci 13(2):93–102. doi:10.1007/s11806-010-0236-7

    Article  Google Scholar 

  • Remondo J, Gonzalez A, De Teran JRD, Cendrero A (2003a) Landslide susceptibility models utilising spatial data analysis techniques. A case study from the Lower Deba Valley, Guipúzcoa (Spain). Nat Hazards 30(3):267–279

    Article  Google Scholar 

  • Remondo J, Gonzalez A, De Teran JRD, Cendrero A, Fabbri A, Chung CJF (2003b) Validation of landslide susceptibility maps; examples and applications from a case study in Northern Spain. Nat Hazards 30(3):437–449. doi:10.1023/B:NHAZ.0000007201.80743.fc

    Article  Google Scholar 

  • Rodriguez CE, Bommer JJ, Chandler RJ (1999) Earthquake-induced landslides: 1980–1997. Soil Dyn Earthq Eng 18(5):325–346. doi:10.1016/S0267-7261(99)00012-3

    Article  Google Scholar 

  • Saha AK, Gupta RP, Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 23(2):357–369. doi:10.1080/01431160010014260

    Article  Google Scholar 

  • Sassa K (2005) Landslide disasters triggered by the 2004 Mid-Niigata prefecture earthquake in Japan. Landslides 2(2):135–142. doi:10.1007/s10346-005-0054-4

    Article  Google Scholar 

  • Sezer EA, Pradhan B, Gokceoglu C (2011) Manifestation of an adaptive neuro-fuzzy model on landslide susceptibility mapping: Klang valley, Malaysia. Expert Syst Appl 38(7):8208–8219. doi:10.1016/j.eswa.2010.12.167

    Article  Google Scholar 

  • van Beek LPH, van Asch TWJ (2004) Regional assessment of the effects of land-use change on landslide hazard by means of physically based modelling. Nat Hazards 31(1):289–304. doi:10.1023/B:NHAZ.0000020267.39691.39

    Article  Google Scholar 

  • van Westen CJ, Seijmonsbergen AC, Mantovani F (1999) Comparing landslide hazard maps. Nat Hazards 20(2–3):137–158. doi:10.1023/A:1008036810401

    Article  Google Scholar 

  • van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazards 30(3):399–419. doi:10.1023/B:NHAZ.0000007097.42735.9e

    Article  Google Scholar 

  • Vaunat J, Leroueil S (2002) Analysis of post-failure slope movements within the framework of hazard and risk analysis. Nat Hazards 26(1):83–109. doi:10.1023/A:1015224914845

    Article  Google Scholar 

  • Wachal DJ, Hudak PF (2000) Mapping landslide susceptibility in Travis County, Texas, USA. GeoJournal 51(3):245–253. doi:10.1023/A:1017524604463

    Article  Google Scholar 

  • Wang WN, Wu HL, Nakamura H, Wu SC, Ouyang S, Yu MF (2003) Mass movements caused by recent tectonic activity: the 1999 Chi–Chi earthquake in central Taiwan. Isl Arc 12(4):325–334. doi:10.1046/j.1440-1738.2003.00400.x

    Article  Google Scholar 

  • Xie MW, Esaki T, Zhou GY (2004) GIS-based probabilistic mapping of landslide hazard using a three-dimensional deterministic model. Nat Hazards 33(2):265–282. doi:10.1023/B:NHAZ.0000037036.01850.0d

    Article  Google Scholar 

  • Xu C, XW Xu (2012a) Comment on “Spatial distribution analysis of landslides triggered by 2008.5.12 Wenchuan Earthquake, China” by Qi S, Xu Q, Lan H, Zhang B, Liu J [Eng Geol 116 (2010) 95–108]. Eng Geol 133–134: 40–42. doi:10.1016/j.enggeo.2012.02.017

  • Xu C, Xu XW (2012b) The 2010 Yushu earthquake triggered landslides spatial prediction models based on several kernel function types. Chin J Geophys 55(9):2994–3005. doi:10.6038/j.issn.0001-5733.2012.09.018 (In Chinese)

    Google Scholar 

  • Xu C, Xu XW (2013) Controlling parameter analyses and hazard mapping for earthquake triggered-landslides: an example from a square region in Beichuan County, Sichuan Province, China. Arab J Geosci. doi:10.1007/s12517-012-0646-y

    Google Scholar 

  • Xu ZQ, Ji SC, Li HB, Hou LW, Fu XF, Cai ZH (2008a) Uplift of the Longmen Shan range and the Wenchuan earthquake. Episodes 31(3):291–301

    Google Scholar 

  • Xu XW, Wen XZ, Ye JQ, Ma BQ, Chen J, Zhou RJ, He HL, Tian QJ, He YL, Wang ZC, Sun ZM, Feng XJ, Yu GH, Chen LC, Chen GH, Yu SE, Ran YK, Li XG, Li CX, An YF (2008b) The Ms 8.0 Wenchuan earthquake surface ruptures and its seismogenic structure. Seismol Geol 30(3):597–629 (In Chinese)

    Google Scholar 

  • Xu C, Dai FC, Chen J, Tu XB, Xu L, Li WC, Tian W, Cao YB, Yao X (2009a) Identification and analysis of secondary geological hazards triggered by a magnitude 8.0 Wenchuan Earthquake. J Remote Sens 13(4):745–762

    Google Scholar 

  • Xu XW, Wen XZ, Yu GH, Chen GH, Klinger Y, Hubbard J, Shaw J (2009b) Coseismic reverse- and oblique-slip surface faulting generated by the 2008 Mw 7.9 Wenchuan earthquake, China. Geology 37(6):515–518. doi:10.1130/G25462A.1

    Article  Google Scholar 

  • Xu XW, Yu GH, Chen GH, Ran YK, Li CX, Chen YG, Chang CP (2009c) Parameters of coseismic reverse- and oblique-slip surface ruptures of the 2008 Wenchuan Earthquake, Eastern Tibetan Plateau. Acta Geol Sin 83(4):673–684. doi:10.1111/j.1755-6724.2009.00091.x

    Article  Google Scholar 

  • Xu C, Xu XW, Dai FC, Xiao JZ, Tan XB, Yuan RM (2012a) Landslide hazard mapping using GIS and weight of evidence model in Qingshui river watershed of 2008 Wenchuan earthquake struck region. J Earth Sci 23(1):97–120. doi:10.1007/s12583-012-0236-7

    Article  Google Scholar 

  • Xu C, Xu XW, Dai FC, Saraf AK (2012b) Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China. Comput Geosci 46:317–329. doi:10.1016/j.cageo.2012.01.002

    Article  Google Scholar 

  • Xu C, Dai FC, Xu XW, Lee YH (2012c) GIS-based support vector machine modeling of earthquake-triggered landslide susceptibility in the Jianjiang River watershed, China. Geomorphology 145–146:70–80. doi:10.1016/j.geomorph.2011.12.040

    Article  Google Scholar 

  • Xu C, Xu XW, Yu GH (2012d) Earthquake triggered landslide hazard mapping and validation related with the 2010 Port-au-Prince Haiti earthquake. Disaster Adv 5(4):1297–1304

    Google Scholar 

  • Xu C, Xu XW, Lee YH, Tan XB, Yu GH, Dai FC (2012e) The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling. Environ Earth Sci 66(6):1603–1616. doi:10.1007/s12665-012-1624-0

    Article  Google Scholar 

  • Xu C, Xu XW, Yu GH (2013a) Landslides triggered by slipping-fault-generated earthquake on a plateau: an example of the 14 April 2010, Ms 7.1, Yushu, China earthquake. Landslides. doi:10.1007/s10346-012-0340-x

  • Xu C, Xu XW, Yao Q, Wang YY (2013b) GIS-based bivariate statistical modeling for earthquake-triggered landslides susceptibility mapping related to the 2008 Wenchuan earthquake, China. Q J Eng Geol Hydrogeol. doi:10.1144/qjegh2012-006

    Google Scholar 

  • Yalcin A, Bulut F (2007) Landslide susceptibility mapping using GIS and digital photogrammetric techniques: a case study from Ardesen (NE-Turkey). Nat Hazards 41(1):201–226. doi:10.1007/s11069-006-9030-0

    Article  Google Scholar 

  • Yao X, Tham LG, Dai FC (2008) Landslide susceptibility mapping based on Support Vector Machine: a case study on natural slopes of Hong Kong, China. Geomorphology 101(4):572–582. doi:10.1016/j.geomorph.2008.02.011

    Article  Google Scholar 

  • Yilmaz I (2009a) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat—Turkey). Comput Geosci 35(6):1125–1138. doi:10.1016/j.cageo.2008.08.007

    Article  Google Scholar 

  • Yilmaz I (2009b) A case study from Koyulhisar (Sivas-Turkey) for landslide susceptibility mapping by artificial neural networks. Bull Eng Geol Environ 68(3):297–306. doi:10.1007/s10064-009-0185-2

    Article  Google Scholar 

  • Yilmaz I (2010) Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine. Environ Earth Sci 61(4):821–836. doi:10.1007/s12665-009-0394-9

    Article  Google Scholar 

  • Yilmaz I, Keskin I (2009) GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey). Bull Eng Geol Environ 68(4):459–471. doi:10.1007/s10064-009-0188-z

    Article  Google Scholar 

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Acknowledgments

This research is supported by the National Science Foundation of China (grant No. 41202235). We thank Drs. Cees J. van Westen and Tolga Gorum for their help in providing ALOS and ASTER images for compiling the inventory of landslides triggered by the 2008 Wenchuan earthquake.

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  1. Key Laboratory of Active Tectonics and Volcano, Institute of Geology, China Earthquake Administration, P.O. Box 9803, Beijing, 100029, People’s Republic of China

    Chong Xu, Xiwei Xu, Honglin He, Feng Shi & Xiyan Wu

  2. Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029, People’s Republic of China

    Chong Xu & Fuchu Dai

  3. Langfang Branch of PetroChina, Research Institute of Petroleum Exploration and Development, Langfang, 065007, People’s Republic of China

    Zhide Wu

  4. China Institute of Geo-Environmental Monitoring, Beijing, 100081, People’s Republic of China

    Suning Xu

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Correspondence to Chong Xu.

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Xu, C., Xu, X., Dai, F. et al. Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Nat Hazards 68, 883–900 (2013). https://doi.org/10.1007/s11069-013-0661-7

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