Abstract
The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.
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References
Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58(1):21–44
Alexander DE (2008) A brief survey of GIS in mass-movement studies, with reflections on theory and methods. Geomorphology 94(3–4):261–267
Bonham-Carter GF (2002) Geographic information systems for geoscientist: modeling with GIS. In: Merriam DF (ed) Computer methods in the geosciences, vol 13. New York, Elsevier, pp 302–334
Brenning A (2005) Spatial prediction models for landslide hazards: review, comparison and evaluation. Nat Hazards Earth Syst Sci 5(6):853–862
Carrara A, Pike RJ (2008) GIS technology and models for assessing landslide hazard and risk. Geomorphology 94(3–4):257–260
Carrara A, Guzzetti F, Cardinali M, Reichenbach P (1999) Use of GIS technology in the prediction and monitoring of landslide hazard. Nat Hazards 20(2–3):117–135
Chacon J, Irigaray C, Fernandez T, Hamdouni RE (2006) Engineering geology maps: landslides and geographical information systems. Bull Eng Geol Environ 65(4):341–411
Chen LC, Wang H, Ran YK, Sun XZ, Su GW, Wang J, Tan XB, Li ZM, Zhang XQ (2010) The Ms7.1 Yushu earthquake surface rupture and large historical earthquakes on the Garzê–Yushu fault. Chin Sci Bull 55(31):3504–3509
Corominas J, Moya J (2008) A review of assessing landslide frequency for hazard zoning purposes. Eng Geol 102(3–4)
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
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
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
Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87
Dikau R, Cavallin A, Jager S (1996) Databases and GIS for landslide research in Europe. Geomorphology 15(3–4):227–239
Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31(1–4):181–216
Keefer DK, Larsen MC (2007) Assessing landslide hazards. Science 316(5828):1136–1138
Oh HJ, Lee S (2011) Landslide susceptibility mapping on Panaon Island, Philippines using a geographic information system. Environ Earth Sci 62(5):935–951
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 Modell Softw 25(6):747–759
Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation—with a case study in the Himalayas. Landslides 2(1):61–69
Sassa K, Tsuchiya S, Ugai K, Wakai A, Uchimura T (2009) Landslides: a review of achievements in the first 5 years (2004–2009). Landslides 6(4):275–286
Singh LP, van Westen CJ, Champati Ray PK, Pasquali P (2005) Accuracy assessment of InSAR derived input maps for landslide susceptibility analysis: a case study from the Swiss Alps. Landslides 2(3):221–228
Sun XZ, Xu XW, Chen LC, Tan XB, Su GW, Wang J, Li ZM, Zhang XQ (2010) Characteristics of surface rupture of the Ms 7.1 Yushu, Qinghai Province earthquake at two representative places. Seismol Geol 32(2):338–344. doi:10.3969/j.issn.0253-4967.2010.02.017 (in Chinese with English abstract)
US Geological Survey (2010) Advanced national seismic system (ANSS), shake map, global region, maps of ground shaking and intensity for event 2010 years, Southern Qinghai, China. http://earthquake.usgs.gov/eqcenter/shakemap
Wang HB, Liu GJ, Xu WY, Wang GH (2005) GIS-based landslide hazard assessment: an overview. Prog Phys Geogr 29(4):548–567
Weiss AD (2006) Topographic position and landforms analysis. http://www.jennessent.com/downloads/tpi-poster-tnc_18x22.pdf
Xu C, Dai FC, Xu XW, Lee YH (2012a) GIS-based support vector machine modeling of earthquake triggered landslide susceptibility mapping in a section of Jianjiang River watershed. Geomorphology 145–156:70–80
Xu C, Dai FC, Xu XW, Saraf AK (2012b) Comparison of different models for susceptibility mapping of earthquake triggered landslides related with the 2008 Wenchuan earthquake in China. Comput Geosci (Online)
Xu C, Xu XW, Dai FC, Xiao JZ, Tan XB, Yuan RM (2012c) 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
Yin YP, Zhang YS, Ma YS, Hu DG, Zhang ZC (2010) Research on major characteristics of geohazards induced by the Yushu Ms7.1 earthquake. J Eng Geol 18(3):289–296 (in Chinese with English abstract)
Zhang PZ, Deng QD, Zhang GM, Ma J, Gan WJ, Min W, Mao FY, Wang Q (2003) Active tectonic blocks and strong earthquakes in the continent of China. Sci China Ser D Earth Sci 46(S2):13–24
Acknowledgments
This research is supported by International Scientific joint project of China (Grant 2009DFA21280), the National Science Foundation of China (Grant 40821160550), and the National Science Foundation of China (Grant 40974057).
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Xu, C., Xu, X., Lee, Y.H. et al. The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling. Environ Earth Sci 66, 1603–1616 (2012). https://doi.org/10.1007/s12665-012-1624-0
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DOI: https://doi.org/10.1007/s12665-012-1624-0