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A Comparative Evaluation of Weight-Rating and Analytical Hierarchical (AHP) for Landslide Susceptibility Mapping in Dhalai District, Tripura

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Book cover Environment and Earth Observation

Part of the book series: Springer Remote Sensing/Photogrammetry ((SPRINGERREMO))

Abstract

The landslide susceptibility map delineates the potential areas of landslide occurrence which is considered to be the first step for landslide hazard management. The present study focuses on the spatial analysis of landslide susceptibility in the Dhalai district using the Geographical Information System (GIS). For this purpose, landslide susceptibility maps are prepared using weight-rating and Analytical Hierarchical Processes (AHP). To analyze landslide manifestation in the present study area, different causative factors (lithology, road buffer, slope, relative relief, rainfall, fault buffer, land-use/land-cover, and drainage density) are derived as layers. The final susceptibility zonation map of weight-rating method shows that about 1.64 and 16.68 % of the total study area falls under very high and high susceptibility zones respectively. In the AHP method, the five landslide susceptibility zones are very low which accounted 14.8 % (354.35 km2) is, low 38.91 % (932.01 km2), moderate 34.75 % (832.37 km2), high 6.03 % (144.39 km2), and very high 5.51 % (131.87 km2). Both susceptibility maps show that the high susceptibility zone is restricted within the structural hilly areas and the low susceptibility zone is in the flood plain areas of the district. Both of the susceptibility maps are validated using the existing landslide distribution in the area.

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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

    Article  Google Scholar 

  • Anbalagan R (1992) Landslide hazard evaluation and zonation mapping in mountainous terrain. Eng Geol 32:269–277

    Article  Google Scholar 

  • Belton V, Stewart T (2002) Multi criteria decision analysis: an integrated approach. Kluwaer Academic Publishers, Bostan

    Book  Google Scholar 

  • BIS (1998) Guideline for preparation of landslide hazard zonation maps in mountains terrains; draft proposal of the Bureau of Indian Standards 2:1–15

    Google Scholar 

  • Brabb EE, Pampeyan, EH (1972) Preliminary map of landslide deposits in San Mateo County, California. US Geological Survey Miscellaneous Field Studies, Map MF-360, scale 1:62.500. (Reprinted in 1978)

    Google Scholar 

  • Devi D, Das K (2013) Landslide hazard zonation along NH-39 from Kangpokpi to Mao, Manipur, India. Int J Econ Environ Geol 2(1):30–35

    Google Scholar 

  • Dutta PJ, Sarma S (2013) Landslide susceptibility zoning of the Kala-Pahar Hill, Guwahati Assam state (India), using a GIS based heuristic technique. Int J Remote Sens Geosci 2(2):49–55

    Google Scholar 

  • EM-DAT (2009) Emergency management disaster database. www.emdat.be/maps-disaster-types

  • Ermini L, Catani F, Casagli N (2005) Artificial neural networks applied to landslide susceptibility assessment. Geomorphology 66:327–343

    Article  Google Scholar 

  • GSI (2009) Geological survey of India report. www.portal.gsi.gov.in

  • Guzzetti F, Cardinali M, Reichenbach P, Carrara A (1999) Comparing landslide maps: a case study in the upper Tiber River Basin, central Italy. Environ Manag 25:247–363

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Gupta RP, Sarkar S (2008) Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas. Landslides 5:407–416

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Sarkar S, Gupta RP (2006) A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Eng Geol 85:347–366

    Article  Google Scholar 

  • Lallianthanga RK, Lalbiakmawia F (2013) Landslide hazard zonation of Mamit town, Mizoram, India using remote sensing and GIS techniques. Int J Geol Earth Environ Sci 3(1):184–194

    Google Scholar 

  • Lee S (2005) Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. Int J Remote Sens 26:1477–1491

    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 54:1517–1529

    Google Scholar 

  • Phukon P, Chetia D, Das P (2012) Landslide susceptibility assessment in the Guwahati city, Assam using analytic hierarchy process (AHP) and geographic information system (GIS). Int J Comput Appl Eng Sci 2(1):1–6

    Google Scholar 

  • Punia M, Raman R (2012) The application of GIS-based bivariate statistical methods for landslide hazards assessment in the upper Tons river valley, Western Himalaya, India. Georisk: Assess Manag Risk Eng Syst Geo Hazards 6(3):145–161

    Google Scholar 

  • Radbruch DH (1970) Map of relative amounts of landslides in California, US Geological Survey Open-File Report 70-1485, pp 36, map scale 1:500.000. US Geological Survey Open-File Report, 85-585

    Google Scholar 

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:234–281

    Article  Google Scholar 

  • Saaty TL (1980) The analytical hierarchy process. McGraw Hill, NY, p 350

    Google Scholar 

  • Saaty TL (2000) Models, methods, concepts and application of the analytical hierarchy process. Kluwer Academic Publishers, Boston

    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 38:8208–8219

    Article  Google Scholar 

  • Singh CD, Behera KK, Rochy WS (2011) Landslide Susceptibility along NH-39 between Karong and Mao, Senapati District, Manipur. J Geol Soc India 78:559–570

    Article  Google Scholar 

  • Singh CD, Singh J (2013) Landslides caused due to ignorance—case studies from northeast India. J Geol Soc India 82(1):91–94

    Article  Google Scholar 

  • Soeters R, Van Westen CJ (1996) Slope instability recognition, analysis, and zonation. In: Urner AK, Schuster RL (eds) Landslides: investigation and mitigation, vol 247. National Academy Press, Washington, D.C, pp 129–177

    Google Scholar 

  • Van Westen CJ, Rengers N, Soeters R (2003) Use of geomorphological information in indirect landslide susceptibility assessment. Nat Hazard 30:399–419

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Geography and Disaster Management, Tripura University, Agartala, 799022, India

    Kapil Ghosh & Shreya Bandyopadhyay

  2. Department of Geography, North Eastern Hill University, Shillong, 793022, India

    Sunil Kumar De

Authors
  1. Kapil Ghosh
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  2. Shreya Bandyopadhyay
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  3. Sunil Kumar De
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Corresponding author

Correspondence to Sunil Kumar De .

Editor information

Editors and Affiliations

  1. School of Oceanographic Studies, Jadavpur University , Kolkata, India

    S. Hazra

  2. School of Oceanographic Studies, Jadavpur University, Kolkata, West Bengal, India

    A. Mukhopadhyay

  3. Department of Science and Technology , Kolkata, West Bengal, India

    A. R. Ghosh

  4. Marine and Atmospheric Studies, Indian Space Research Organisation, Dehradun, India

    D. Mitra

  5. Indian Space Research Organisation, National Remote Sensing Centre, Hyderabad, India

    V. K. Dadhwal

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Ghosh, K., Bandyopadhyay, S., De, S.K. (2017). A Comparative Evaluation of Weight-Rating and Analytical Hierarchical (AHP) for Landslide Susceptibility Mapping in Dhalai District, Tripura. In: Hazra, S., Mukhopadhyay, A., Ghosh, A., Mitra, D., Dadhwal, V. (eds) Environment and Earth Observation. Springer Remote Sensing/Photogrammetry. Springer, Cham. https://doi.org/10.1007/978-3-319-46010-9_12

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