Skip to main content
Log in

Comparative evaluation of landslide susceptibility in Minamata area, Japan

  • Original Article
  • Published:
Environmental Geology

Abstract

Landslides are unpredictable; however, the susceptibility of landslide occurrence can be assessed using qualitative and quantitative methods based on the technology of the Geographic Information Systems (GIS). A map of landslide inventory was obtained from the previous work in the Minamata area, the interpretation from aerial photographs taken in 1999 and 2002. A total of 160 landslides was identified in four periods. Following the construction of geospatial databases, including lithology, topography, soil deposits, land use, etc., the study documents the relationship between landslide hazard and the factors that affect the occurrence of landslides. Different methods, namely the logistic regression analysis and the information value model, were then adopted to produce susceptibility maps of landslide occurrence. After the application of each method, two resultant maps categorize the four classes of susceptibility as high, medium, low and very low. Both of them generated acceptable results as both classify the majority of the cells with landslide occurrence in high or medium susceptibility classes, which could be believed to be a success. By combining the hazard maps generated from both methods, the susceptibility was classified as high–medium and low–very low levels, in which the classification of high susceptibility level covers 6.5% of the area, while the areas predicted to be unstable, which are 50.5% of the total area, are classified as the low susceptibility level. However, comparing the results from both the approaches, 43% of the areas were misclassified, either from high–medium to low–very low or low–very low to high–medium classes. Due to the misclassification, 8% and 3.28% of all the areas, which should be stable or free of landsliding, were evaluated as high–medium susceptibility using the logistic regression analysis and the information value model, respectively. Moreover, in the case of the class rank change from high–medium susceptibility to low–very low, 35% and 39.72% of all mapping areas were predicted as stable using both the approaches, respectively, but in these areas landslides were likely to occur or were actually recognized.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Alcantara-Ayala I (2004) Hazard assessment of rainfall-induced landsliding in Mexico. Geomorphology 61(1–2):19–40

    Article  Google Scholar 

  • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44

    Article  Google Scholar 

  • Carrara A, Cardinali M, Detti R, Guzzetti F, Pasqui V, Reichenbach P (1991) GIS techniques and statistical models in evaluating landslide hazard. Earth Surface Process Landform 16:427–445

    Google Scholar 

  • Carrara A, Cardinali M, Guzzetti F (1992) Uncertainty in assessing landslide hazard and risk. ITC 2:172–183

    Google Scholar 

  • Chau KT, Sze YL, Fung MK, Wong WY, Fong EL, Chan LCP (2004) Landslide hazard analysis for Hong Kong using landslide inventory and GIS. Comput Geosci 30(4):429–443

    Article  Google Scholar 

  • Chung CF, Fabbri AG (1995) Multivariate regression analysis for landslide hazard zonation. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer, Dordrecht, pp 107–133

    Google Scholar 

  • Cruden DM, Fell R (1997) Landslide risk assessment. In: Proceedings of International Workshop on Landslide Risk Assessment, Honolulu. AA Balkema, Rotterdam

  • Dai FC, Lee CF (2001) Terrain-based mapping of landslide susceptibility using a geographical information system: a case study. Can Geotech J 38(5):911–923

    Article  Google Scholar 

  • Gupta P, Anbalagan R (1997) Slope stability of Tehri Dam reservoir area, India, using landslide hazard zonation (LHZ) mapping. Q J Eng Geol 30(1):27–36

    Google Scholar 

  • Guzzetti F, Carrara A, Cardinalli M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-case study, central Italy. Geomorphology 31:181–216

    Article  Google Scholar 

  • Hansen A, Brimicombe AJ, Franks C, Kirk P, Tung F (1995) Application of GIS to hazard assessment, with particular reference to landslides in Hong Kong. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer, The Netherlands, pp 273–298

    Google Scholar 

  • Hutchinson JN (1995) Keynote paper—landslide hazard assessment. Proceedings of 6th symposium on landslides. In: Bell DH (ed) Landslides, vol 3. A.A. Balkema, Rotterdam, pp 1805–1841

  • Lee S, Chwae U, Min KD (2002) Landslide susceptibility mapping by correlation between topography and geological structure: the Janghung area. Korea Geomorphol 46(3–4):149–162

    Article  Google Scholar 

  • Turner AK, Schuster RL (eds) (1996) Landslides: investigation and mitigation. Washington, DC, National Research Council, Transportation Research Board Special Report 247, pp 675

  • Varnes DJ (1984) Hazard zonation: a review of principal and practice. Commission of Landslide of IAEG, UNESCO, Natural Hazards, No 3, p 61

    Google Scholar 

  • van Westen CJ (1993) Application of Geographical Information System to landslide hazard zonation. ITC Publication 15:245

    Google Scholar 

  • Wu SR, Shi L, Wang RJ, Tan CX, Hu DG, Mei YT, Xu RC (2001) Zonation of the landslide hazards in the fore reservoir region of the three Gorges project on the Yangtze river. Eng Geol 59:51–58

    Article  Google Scholar 

  • Yan TZ (1988) Advances on quantitative prediction of landslide researches (in Chinese). Hydrogeol Eng Geol 6:8–14

    Google Scholar 

  • Yin KL, Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Bonnard C (ed) Proceedings of 5th international symposium landslides, Lausanne, vol 2. AA Balkema, Rotterdam, pp 1269–1272

Download references

Acknowledgements

This work was performed under the Grant-In-Aid for scientific research from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. The first author was indebted to the Postdoctoral Fellowship for foreign researchers provided by the Japanese Society for the Promotion of Science (JSPS). Also, the first author would like to gratefully acknowledge the additional support from the China Postdoctoral Science Foundation. They would like to express their sincere appreciation to an anonymous reviewer for his insightful comments and valuable work to both the language and the research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. B. Wang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, H.B., Sassa, K. Comparative evaluation of landslide susceptibility in Minamata area, Japan. Environ Geol 47, 956–966 (2005). https://doi.org/10.1007/s00254-005-1225-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00254-005-1225-2

Keywords

Navigation