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Landslides susceptibility mapping based on geographical information system, GuiZhou, south-west China

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Environmental Geology

Abstract

The purpose of this study is to assess the susceptibility of landslides around the area of Guizhou province, in south-west of China, using a geographical information system (GIS). The base map is prepared by visiting the field area and mapping individual landslide at a scale of 1:500,000 topographic maps. In the study, slope, lithology, landslide inventory, tectonic activity, drainage distribution and annual precipitation were taken as independent causal factors. Therefore, six causal factors maps are prepared by collecting information from various authorized sources and converting them in to GIS maps. The susceptibility assessment is based on the qualitative map combination model and trapezoidal fuzzy number weighting (TFNW) approach. Using a predicted map of probability, the study area was classified into four categories of landslide susceptibility: low, moderate, high and very high. In addition, the weighting procedure showed that the TFNW is an efficient method for landslide causal factors weighting.

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References

  • Akgün A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Geol 51:1377–1387

    Article  Google Scholar 

  • Aronoff S (1989) Geographic Information Systems: a management perspective. WDL Publications, Ottawa, p 294

  • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko mountains, Central Japan. Geomorphology 65:15–31

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Marui H, Kanno T (2005) Landslide in Sado Island of Japan: part II. GIS-based susceptibility mapping with comparison of results from two methods and verifications. Eng Geol 81:432–445

    Article  Google Scholar 

  • Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Proc Land 26(12):1251–1263

    Article  Google Scholar 

  • Brabb EE (1984) Innovative approaches to landslide hazard mapping. In: Proceed. IV Int. Symp. Landslides, Toronto, pp 307–324

  • Carro M, De Amicis M, Luzi L, Marzorati S (2003) The application of predictive modeling techniques to landslides induced by earthquakes: the case study of the 26 September 1997 Umbria-Marche earthquake (Italy). Eng Geol 69(1–2):139–159

    Article  Google Scholar 

  • Çevik E, Topal T (2003) GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environ Geol 44:949–962

    Article  Google Scholar 

  • Chou SY, Chang YH, Shen CY (2008) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective-subjective attributes. Eur J Oper Res 189:132–145

    Article  Google Scholar 

  • Clerici A, Perego S, Tellini C, Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48(4):349–364

    Article  Google Scholar 

  • Coppock J (1995) GIS and natural hazards: an overview from a GIS perspective. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. pp 21–34

  • 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

    Article  Google Scholar 

  • Donati L, Turrini MC (2002) An objective method to rank the importance of the factors predisposing to landslides with the GIS Methodology: application to an area of the Apennines (Valnerina; Perugia, Italy). Eng Geol 63(3–4):277–289

    Article  Google Scholar 

  • Eastman R (1999) Multi-criteria evaluation and GIS. Chap. 35 In: Longley PA, Goodchild MF, Maguire DJ, Rhind DW (eds) Geographical information systems, Wiley, New York, pp 493–502

  • Galli M, Ardizzone F, Cardinali M, Guzzetti F, Reichenbach P (2008) Comparing landslide inventory maps. Geomorphology 94(3–4):268–289

    Article  Google Scholar 

  • Galang JS (2004) A comparison of GIS approaches to slope instability zonation in the central blue ridge mountains of virginia. Master, Virginia Polytechnic Institute and State University, Unite State

  • Guzzetti F, Cardinali M, Reichenbach P, Carrara A (2000) Comparing landslide maps: a case study in the upper Tiber River Basin, Central Italy. Environ Manage 25(3):247–363

    Article  Google Scholar 

  • Hansen A (1984) Landslide hazard analysis. In: Brunsden D, Prior DB (eds) Slope instability. Wiley, New York, pp 523–602

    Google Scholar 

  • Jiang H, Eastman JR (2000) Application of fuzzy measures in multicriteria evaluation in GIS. Int J Geogr Inf Sci 14:173–184

    Article  Google Scholar 

  • Keufmann A, Gupta MM (1991) Introduction to fuzzy arithmetic: theory and application. Van Nostrand Reinhold, New York

    Google Scholar 

  • Lee S, Choi U (2003) Development of GIS-based geological hazard information system and its application for landslide analysis in Korea. Geosci J 7(3):243–252

    Article  Google Scholar 

  • Lee S, Evangelista DG (2006) Earthquake-induced landslide-susceptibility mapping using an artificial neural network. Nat Hazard Earth Syst Sci 6:687–695

    Article  Google Scholar 

  • Lee S, Choi J, Woo I (2004a) The effect of spatial resolution on the accuracy of landslide susceptibility mapping: a case study in Boun, Korea. Geosci J 8(1):51–60

    Article  Google Scholar 

  • Lee S, Ryu JH, Won JS, Park HJ (2004b) Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Eng Geol 71(3–4):289–302

    Article  Google Scholar 

  • Ohlmacher GC, Davis JC (2003) Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansa, USA. Eng Geol 69(3–4):331–343

    Article  Google Scholar 

  • Öztekin B, Topal T (2005) GIS-based detachment susceptibility analyses of a cut slope in limestone, Ankara, Turkey. Environ Geol 49:124–132

    Article  Google Scholar 

  • Parise M, Jibson RW (2000) A seismic landslide susceptibility rating of geologic units based on analysis of characteristics of landslides triggered by the 17 January, 1994 Northridge, California earthquake. Eng Geol 58(3–4):251–270

    Article  Google Scholar 

  • Pistocchi A, Luzi L, Napolitano P (2002) The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods. Environ Geol 41(7):765–775

    Article  Google Scholar 

  • Refice A, Capolongo D (2002) Probabilistic modeling of uncertainties in earthquake-induced landslide hazard assessment. Comput Geosci 28(6):735–749

    Article  Google Scholar 

  • Saaty TL (1983) Axiomatic foundations of the analytic hierarchy process. Manage Sci 32:841–855

    Article  Google Scholar 

  • Saaty TL, Vargas GL (2001) Models, methods, concepts and applications of the analytic hierarchy process. Kluwer, Boston, pp 333

  • 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

    Article  Google Scholar 

  • Sarkar S, Kanungo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogramm Eng Remote Sens 70(5):617–625

    Article  Google Scholar 

  • Şener B, Süzen ML, Doyuran V (2006) Landfill site selection by using geographic information systems. Environ Geol 49:376–388

    Article  Google Scholar 

  • Stevenson PC (1977) An empirical method for the evaluation of relative landslide risk. Bull Int Assoc Eng Geol 16:69–72

    Article  Google Scholar 

  • The Ministry of Land and Resource of China (2008) http://www.mlr.gov.cn/. Cited 2 Feb 2008

  • Varnes DJ (1978) Slope movement types and processes. Landslides: analysis and control. Transportation research board special report. Natl Acad Sci 176:11–33

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. UNESCO, Paris, 63 pp

  • Van Westen CJ (1994) GIS in landslide hazard zonation: a review, with examples from the Colombian Andes. In: Heywood DI (ed) Mountain environments and geographic information systems, vol 1. Taylor and Francis, London, pp 135–165

  • Van Westen CJ (1997) Statistical landslide analysis. ILWIS 2.1. for windows application quide. ITC Publication, Enschede, pp 73–84

    Google Scholar 

  • Zhou CH, Lee CF, Li J, Xu ZW (2002) On the spatial relationship between landslides and causative factors on Lantau Island, Hong Kong. Geomorphology 43(3–4):197–207

    Article  Google Scholar 

  • Zhou G, Esaki T, Mitani Y, Xie M, Mori J (2003) Spatial probabilistic modeling of slope failure using an integrated GIS Monte Carlo simulation approach. Eng Geol 68(3–4):373–386

    Article  Google Scholar 

Download references

Acknowledgments

The research work was supported by West Project of Ministry Communication, China. The authors appreciate Dr. Hesham Rakha, the professor of Virginia Polytechnic Institute and State University, for providing good research condition. Also, we are grateful to anonymous referees for their useful comments and careful manuscript reviewing.

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Correspondence to Wei Dong Wang.

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Wang, W.D., Xie, C.M. & Du, X.G. Landslides susceptibility mapping based on geographical information system, GuiZhou, south-west China. Environ Geol 58, 33–43 (2009). https://doi.org/10.1007/s00254-008-1488-5

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  • DOI: https://doi.org/10.1007/s00254-008-1488-5

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