, 4:101 | Cite as

Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya

  • P. K. Champati ray
  • Suvarna Dimri
  • R. C. Lakhera
  • Santosh Sati
Original Article


Landslides in Himalaya cause widespread damage in terms of property and human lives. It the present study, an attempt is made to derive information on causative parameters and preparation of landslide-susceptible map using fuzzy data integration in one of the seismically active region of Garhwal Himalaya that was recently devastated by a huge landslide. High-resolution remotely sensed data products acquired from Indian Remote Sensing Satellite before and after the landslide event were processed to improve interpretability and derivation of causative parameters. Spatial data sets such as lithology, rock weathering, geomorphology, lineaments, drainage, land use, anthropogenic factor, soil type and depth, slope gradient, and slope aspect were integrated using fuzzy gamma operator. The final map was reclassified in to five classes such as highly to lowly susceptible classes based on cumulative cutoff. The result shows around 72% of known landslide areas including the large Uttarkashi landslide in the high and very high susceptibility classes comprising of only 37% of the total area. The precipitation data from ground- and satellite-based observations were compared; the precipitation threshold and the role of seismic activity were analyzed for initiation of landslide.


Himalaya Seismic zone Landslide hazard assesment Fuzzy Remote sensing 



The authors are thankful to Dr. R.R. Navalgund, Director, NRSA and Dr. V.K. Dadhwal, Dean, IIRS for their support to the study and to Dr. Rajat Chatterjee and Ms. Yamini Sharma for helping in satellite data analysis and database generation. Authors are grateful to Central Water Commission and CPC, NOAA (USA) for rainfall data and Uttaranchal administration for logistic support during field investigation. Authors are extremely grateful to an anonymous reviewer, Dr. C.J. van Westen, and Prof. O. Maquaire, co-editor, for their very critical comments to improve the manuscript.


  1. Agarwal NC, Kumar G (1973) Geology of the upper Bhagirathi and Yamuna valleys, Uttarkashi District, Kumaun Himalaya. Himal Geol 3:1–23Google Scholar
  2. Anbalagan R (1992) Landslide hazard evaluation and zonation mapping in mountainous terrain. Eng Geol 32:269–277CrossRefGoogle Scholar
  3. Bonham-Carter GF (1994) Geographic information systems for geoscientists: modelling with GIS. Pergamon, New York, pp 292–302Google Scholar
  4. Carrara A, Cardinali M, Guzzetti F, Reichenbach P (1995) GIS technology in mapping landslide hazard. In: Carrara A, Guzzetti F (eds) Geographical information systems in assessing natural hazards. Kluwer, Dordrecht, The Netherlands, pp 135–175Google Scholar
  5. CEOS (2001) The use of earth observing satellites for hazard support: assessment and scenarios. CEOS report, NOAA, USA. Available at
  6. Champati ray PK (1996) Landslide hazard zonation using fuzzy logic and probability analysis in western Himalayas. Project report under IIRS-ITC programme, internal publication. ITC, NetherlandsGoogle Scholar
  7. Champati ray PK (2004) GIS based landslide modelling. In: Nagarajan R (ed) Landslide disaster: assessment and monitoring. Anmol Publications, New Delhi, pp 81–96Google Scholar
  8. Champati ray PK, Bhan SK (1998) Remotely sensed and ancillary data integration techniques for landslide hazard zonation. In: Tripathy NK, Bajpai VN (eds) Remote sensing in geoscience. Anmol Publisher, New Delhi, pp 245–260Google Scholar
  9. Chang KT, Liu JK (2004) Landslide features interpreted by neural network method using a high-resolution satellite image and digital topographic data, Proceedings of XXth ISPRS Congress, 12–23 July 2004 Istanbul, pp 574–579Google Scholar
  10. Choubey VD, Litoria PK (1990) Terrain classification and land hazard mapping in Kalsi-Chakrata area (Garhwal Himalaya) India. ITC J 1990–1:58–66Google Scholar
  11. Chung CF, Fabbri AG (1993) The representation of geoscientific information for data integration. Nonrenew Resour 2(2):122–139CrossRefGoogle Scholar
  12. Chung CF, Fabbri AG, van Westen CJ (1995) Multivariate regression analysis for landslide hazard zonation. In: Carrara A, Guzzety F (eds) Geographical information systems in assessing natural hazards. Kluwer, Dordrecht, The Netherlands, pp 107–133Google Scholar
  13. Gabet EJ, Burbank DW, Putkonen JK, Pratt-Sitaula BA, Ojha T (2004) Rainfall thresholds for landsliding in the Himalayas of Nepal. Geomorphology 63(3–4):131–143CrossRefGoogle Scholar
  14. Gupta RP, Joshi BC (1990) Landslide hazard zoning using the GIS approach—a case study from the Ram Ganga catchment, Himalayas. Eng Geol 28(1990):119–131CrossRefGoogle Scholar
  15. Gupta P, Anbalagan R, Bisht DS (1993a) Landslide hazard zonation mapping around Shivpuri, Garhwal Himalayas, U.P. J Himal Geol 4(1):95–102Google Scholar
  16. Gupta V, Sah MP, Virdi NS, Bartarya SK (1993b) Landslide Hazard Zonation in the upper Satluj valley, Dist. Kinnaur, Himachal Pradesh. J Himal Geol 4(1):81–93Google Scholar
  17. Gupta V, Virdi NS, Prakash S (2001) Morphometric assessment of active landslides in the Higher Himalayan crystalline, Satluj valley, Himachal Pradesh. Himal Geol 22(2):99–107Google Scholar
  18. Hervas J, Barredo JI, Rosin PL, Pasuto A, Mantovani F, Silvano S (2003) Monitoring landslides from optical remotely sensed imagery:the case history of Tessina landslide , Italy. Geomorphology 54(1–2):63–75CrossRefGoogle Scholar
  19. IDRISI (1995) The decision support ring. IDRISI user manual ver. 4Google Scholar
  20. Jain AK (1971) Stratigraphy and tectonics of lesser Himalayan Region of Uttarkashi, Garhwal Himalaya. Himal Geol 1:25–58Google Scholar
  21. Jibson RW (1993) Predicting earthquake-induced landslide displacements using Newmark’s sliding block analysis. Transp Res Rec 1411:9–17Google Scholar
  22. Jibson RW, Harp EL, Michael JA (1998) A method for producing digital probabilistic seismic landslide hazard maps: an example from the Los Angeles, California Area. Open-File Report 98–113, U.S. Department of the Interior U.S. Geological SurveyGoogle Scholar
  23. Kanungo DP, Sarkar S (2003) Landslides and terrain parameters in Darjeeling Himalaya. Himal Geol 24(2):55–62Google Scholar
  24. Mehrotra GS, Sarkar S, Dhramaraju R (1991) Landslide hazard assessment in Rishikesh Tehri area, Garhwal Himalaya, India. In: Bell DH (ed) Landslides. Balkema, Rotterdam, pp 1001–1007Google Scholar
  25. Nainwal HC, Prasad C (2001) Miro-Zonation of slope stability using SMR approach—a case study from Garhwal Himalayas, India. Himal Geol 22(2):135–146Google Scholar
  26. Naithani AK, Prasad C, Bisht MPS, Kumari G (1997) Landslide zonation and geoenvironmental appraisal along main centre thrust zone in Mandakini Valley, Garhwal Himalaya, India. Himal Geol 18:135–143Google Scholar
  27. Narula PL, Shome SK, Kumar S, Pande P (1995) Damage patterns and delineation of isoseismals of Uttarkashi earthquake of 20th October, 1991. In: Gupta HK, Gupta GD (eds) Uttarkashi earthquake. Geological survey of India, pp 1–18Google Scholar
  28. Newmark NM (1965) Effects of earthquakes on dams and embankments. Geotechnique 15(2):139–160CrossRefGoogle Scholar
  29. Ostir K, Veljanovski T, Podobnikar T, Stancic Z (2003) Application of satellite remote sensing in natural hazard management: the Mount Mangart landslide case study. Int J Remote Sens 24(20):3983–4002CrossRefGoogle Scholar
  30. Pachauri AK, Pant M (1992) Landslide hazard mapping based on geological attributes. Eng Geol 32:81–100CrossRefGoogle Scholar
  31. Pachauri AK, Gupta PV, Chandar R (1998) Landslide zoning in a part of the Garhwal Himalaya. Environ Geol 36(3–4):325–334CrossRefGoogle Scholar
  32. Petley DN, Crick WDO, Hart AB (2002) The use of satellite imagery in landslide studies in high mountain areas. In: The proceedings of the 23rd Asian conference on remote sensing, Kathmandu, Nov 2002, pp 25–29Google Scholar
  33. Raman VAV, Rawat DS (1993) Geology and geomorphology of Kishau dam area, U.P., India. P.G. Diploma Dissertation, IIRS, DehradunGoogle Scholar
  34. Rastogi BK, RK Chadha (1995) Intensity and isoseismals of Uttarkashi earthquake of October 20, 1991. In: Gupta HK, Gupta GD (eds) Uttarkashi earthquake. Geological survey of India, pp 19–24Google Scholar
  35. Ravindran KV, Bhan SK (1991) Mountain resources management of remote sensing. Survey Publications, Dehradun, pp 38–48Google Scholar
  36. Ravindran KV, Phillip G (2002) Mapping of 29 March 1999 Chamoli earthquake induced landslides using IRS-1C/1D data. Himal Geol 23(1&2):69–76Google Scholar
  37. Saaty TL (1978) Exploring the interface between hierarchies, multiple objectives and fuzzy sets. Fuzzy Sets Syst 1:57–68CrossRefGoogle Scholar
  38. Saha AK, Gupta RP, Arora MK (2002) GIS based landslide hazard zonation in the Bhagirathi (Ganga) valley, Himalayas. Int J Remote Sens 23(2):357–369CrossRefGoogle Scholar
  39. Saha AK, Gupta RP, Sarkar I, Arora MK, Csaplovics E (2004) An approach for GIS based statistical landslide susceptibility zonation—with a case study in the Himalayas. Landslides 2(1):61–69CrossRefGoogle Scholar
  40. Saraf AK, Sarkar I (2002) Seismotectonic and environmental aspects of the Chamoli earthquake using ground and satellite data. Himal Geol 23(1&2):77–86Google Scholar
  41. Sarkar S, Kanungo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogramm Eng Remote Sensing 70(5):617–625Google Scholar
  42. Sarkar S, DP Kanungo, Mehrotra GS (1995) Landslide hazard zonation: a case study in Garhwal Himalaya, India. Mt Res Dev 15(4):301–309CrossRefGoogle Scholar
  43. Sarkar S, Kanungo DP, Chauhan PKS (2004) Landslide disaster of 24th September 2003 in Uttarkashi. Curr Sci 87(2):134–137Google Scholar
  44. 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 Swiss Alps. Landslides 2:221–228CrossRefGoogle Scholar
  45. Soeters R, van Westen CJ (1996) Slope instability recognition, analysis, and zonation. In: Landslides investigation and mitigation, special report 247. Transportation Research Board, National Research Council, National Academy Press, pp 129–177Google Scholar
  46. Sreemal PS, Chmpati Ray PK, Srivastav SK (2003) Remote sensing and GIS based method and software customization for landslide hazard assessment along Silchar–Shillong Highway, Northeast India. Trop Agric Res 15:316–326Google Scholar
  47. van Westen CJ (1993) GISSIZ training package for geographic information systems in slope instability zonation, UNESCO-ITC Project. ITC Publication No. 15, EnschedeGoogle Scholar
  48. Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. Natural hazards, vol. 3. UNESCO, ParisGoogle Scholar
  49. Vinod Kumar K, Nair R, Lakhera RC (1993) Digital image enhancement for delineating active landslide areas. Asian Pacific Remote Sensing J 6(1):63–66Google Scholar
  50. Virdi NS, Sah MP, Bartarya, SK (1997) Mass wasting, its manifestations, causes and control: some case histories from Himachal Himalayas. In: Perspectives of mountain risks engineering in the Himalayan region. Gyanodaya Prakashan, Nainital, pp 111–129Google Scholar
  51. Wilson RC, Keefer DK (1983) Dynamic analysis of a slope failure from the 6 August 1979 Coyote Lake, California Earthquake. Bull Seismol Soc Am 73:863–877Google Scholar
  52. Yin KL, Yan TZ (1988) Statistical prediction models for slope instability of metamorphosed rocks. In: Proceedings of 5th international symposium on landslides, vol. 2. Lausanne, pp 1269–1272Google Scholar
  53. Zadeh LA (1965) Fuzzy sets. IEEE Information and Control 8:125–151Google Scholar
  54. Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 1:3–28CrossRefGoogle Scholar
  55. Zimmermann HJ (1985) Fuzzy set theory—and its applications. Kluwer-Nijhoff, DordrechtGoogle Scholar
  56. Zimmermann HJ, Zysno P (1980) Latent connectives in human decision making. Fuzzy Sets Syst 4:37–51CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • P. K. Champati ray
    • 1
  • Suvarna Dimri
    • 2
  • R. C. Lakhera
    • 1
  • Santosh Sati
    • 3
  1. 1.Indian Institute of Remote SensingDehradunIndia
  2. 2.Forest Research InstituteDehradunIndia
  3. 3.Department of GeologyH. N. B. Garhwal UniversitySrinagarIndia

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