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Landslide vulnerability mapping using frequency ratio model: a geospatial approach in Bodi-Bodimettu Ghat section, Theni district, Tamil Nadu, India

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Abstract

This research paper assesses the vulnerability of landslide for the Bodi-Bodimettu Ghat section, Theni district, Tamil Nadu, India, using remotely sensed data and geographic information system (GIS). Landslide database was generated using IRS-1C satellite LISS III data and aerial photographs accompanied by field investigations using differential global positioning system to generate a landslide inventory map. Topographical, spatial, and field data were processed to construct the spatial thematic layers using image processing and GIS environment. Twelve landslide-inducing factors were used for landslide vulnerability analysis: elevation, slope, aspect, plan curvature, profile curvature, proximity to road, drainage and lineament, land use/land cover, geology, geomorphology, and run-off. The first five factors were derived from digital elevation model, and other thematic layers were prepared from spatial database. Frequency ratio of each factor was computed using the above thematic factors with past landslide locations. Landslide vulnerability map was produced using raster analysis. The landslide vulnerability map was classified into five zones: very low, low, moderate, high, and very high. The model is validated using the relative landslide density index (R-index method). The consistency of R-index indicates good performance of the vulnerability map.

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References

  • Akgun A, Dag S, Bulut F (2008) Landslide susceptibility mapping for a landslide-prone area (Findikli, NE of Turkey) by likelihood frequency ratio and weighted linear combination models. Environ Geol 54:1127–1143

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Anbalagan R (1996) An overview of landslide hazards in Himalaya, available knowledge base, gaps, and recommendation for future research. Himal Geol 17:165–167

    Google Scholar 

  • Anon (1973) A method for estimating volume and rate of run-off in small watershed. US Department of Agriculture, Soil Conservation Service, Washington, DC, USA

  • Anon (1998) Bureau of Indian Standard, preparation of landslide hazard zonation maps in mountainous terrains—guidelines, part 2 macro-zonation, IS 14496, Bureau of Indian Standard, New Delhi, India

  • Anon (2005) District Resource map, Geology and minerals—Theni District, Geological Survey of India

  • Anon (2006) Manual of national land use and land cover mapping using multi-temporal satellite data. National Remote Sensing Centre, Hyderabad

  • Anon (2008) Manual of groundwater prospect mapping using remote sensing and geographic information system. Rajiv Gandhi National Drinking Water Mission Project, National Remote Sensing Centre, Hyderabad

  • Anon (2009) Specifications of NovCom DGPS, NovCom technology. John Deere Company, Torrance, USA

    Google Scholar 

  • Arora MK, Das Gupta AS, Gupta RP (2004) An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 25(3):559–572

    Article  Google Scholar 

  • Baeza C, Corominas J (2001) Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Proc Land 26:251–1263

    Article  Google Scholar 

  • Barredo JI, Benavidesz A, Hervhl J, van Westen CJ (2000) Comparing heuristic landslide hazard assessment techniques using GIS in the Tirajana basin, Gran Canaria Island, Spain. Appl Earth Obs Geoinf 2(1):9–23

    Article  Google Scholar 

  • Binaghi E, Brivio PA, Ghezzi P, Rampini A (1999) A fuzzy set-based accuracy assessment of soft classification. Pattern Recogn Lett 20:935–948

    Article  Google Scholar 

  • Brunsden D (1996) Mass movement, the research frontier and beyond: a geomorphological approach. Geomorphology 7:85–128

    Article  Google Scholar 

  • Carrara A, Guzzetti F, Cardinali M, Reichenbach P (1999) Use of GIS technology in the prediction and monitoring of landslide hazard. Nat Hazards 20:117–135

    Article  Google Scholar 

  • Chen Z, Wang J (2007) Landslide hazard mapping using logistic regression model in Mackenzie Valley, Canada. Nat Hazards 42(1):75–89

    Article  Google Scholar 

  • Chi KH, Park NW, Chung CJ (2002) Fuzzy logic integration for landslide hazard mapping using spatial data from Boeun, Korea. Symposium on Geospatial Theory, Processing and Applications, Ottawa

  • Cruden DM, Varnes DJ (1996) Landslide types and processes. In: A. K. Turner and R. L. Schuster (eds) Landslides investigation and mitigation. National Research Council, Transportation Research Board, Special Report, 247, pp. 36–75

  • Ercanoglu M, Gokceoglu C (2004) Use of fuzzy relations to produce landslide susceptibility map of a landslide prone area (West Black Sea Region, Turkey). Eng Geol 75(229–250):2004

    Google Scholar 

  • Fernandez Merodo JA, Pastor M, Mira P (2004) Modeling of diffuse failure mechanisms of catastrophic landslides. Comput Methods Appl Mech Eng 193:2911–2939

    Article  Google Scholar 

  • Goetz JN, Guthrie RH, Brenning A (2011) Integrating physical and empirical landslide susceptibility models using generalized additive models. Geomorphology 129:376–386

    Article  Google Scholar 

  • Gupta V, Sah MP, Virdi NS, Bartarya SK (1993) Landslide hazard zonation in the Upper Satlej Valley, District Kinnaur, Himachal Pradesh. J Himal Geol 4:81–93

    Google Scholar 

  • 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 31:181–216

    Article  Google Scholar 

  • Guzzetti F, Reichenbach P, Cardinali M, Galli M, Ardizzone F (2005) Probabilistic landslide hazard assessment at the basin scale. Geomorphology 72:272–299

    Article  Google Scholar 

  • Hansen A (1984) Landslide hazard analysis. In: Brunsden D, Prior DB (eds) Slope instability. Wiley & Sons, New York

    Google Scholar 

  • Hartlen J, Viberg L (1988) Evaluation of landslide hazard, 5th International Symposium on Landslides, Lausanne, 2

  • Hawkins RH (1973) Improved prediction of storm runoff in mountain watersheds, J. Irrig. Drain, Div.-ASCE, 99, No. IR4, Proc. Paper, 10188, pp. 519–523

  • Hawkins RH (1979) Runoff curve numbers for partial area watersheds. J Irrig Drain Div ASCE 105(4):375–389

    Google Scholar 

  • Hawkins RH (1993) Asymptotic determination of runoff curve numbers from data. J Irrig Drain E-ASCE 119(2):334–345

    Article  Google Scholar 

  • Intarawichian N, Dasananda S (2011) Frequency ratio model based landslide susceptibility mapping in lower Mae Chaem watershed, Northern Thailand. Environ Earth Sci 64:2271-2285

    Google Scholar 

  • Jadda M, Shafri HZM, Mansor SB (2011) PFR model and GiT for landslide susceptibility mapping: a case study from Central Alborz. Iran Nat Hazards 57(2):395–412

    Article  Google Scholar 

  • Kannan M, Saranathan E, Anbazhagan R (2011a) Macro landslide hazard zonation mapping—case study from Bodi-Bodimettu Ghat section, Theni District, Tamil Nadu—India. J Indian Soc Remote Sens 39(4):485–496

    Article  Google Scholar 

  • Kannan M, Saranathan E, Anbazhagan R (2011b) Evaluation of vulnerable zones in Bodi-Bodimettu Ghat section, Bodinayakkanur Taluk, Theni District, Tamil Nadu. Indian Landslides 4(1):39–44

    Google Scholar 

  • Karim S, Jalileddin S, Ali MT (2011) Zoning landslide by use of frequency ratio method (case study: Deylaman Region). Middle-East J Sci Res 9(5):578–583

    Google Scholar 

  • Knapen A, Kitutu MG, Poesen J, Breugelmans W, Deckers J, Muwanga A (2006) Landslides in a densely populated county at the foot slopes of Mount Elgon (Uganda): characteristics and causal factors. Geomorphology 73:149–165

    Article  Google Scholar 

  • Lee S (2007) Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environ Geol 52:615–623

    Article  Google Scholar 

  • Lee S, Dan NT (2005) Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Environ Geol 48:778–787

    Article  Google Scholar 

  • Lee S, Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environ Geol 40:1095–1113

    Article  Google Scholar 

  • Lee S, Pradhan B (2006) Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. Earth Syst Sci 115(6):661–672

    Article  Google Scholar 

  • Lee S, Talib JA (2005) Probabilistic landslide susceptibility and factor effect analysis. Environ Geol 47:982–990

    Article  Google Scholar 

  • Lee S, Choi J, Min K (2004) Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea. Int J Remote Sens 125(11):2037–2052

    Article  Google Scholar 

  • Lepore C, Kamal SA, Shanahan P, Bras RL (2011) Rainfall-induced landslide susceptibility zonation of Puerto Rico Environmental Earth Sciences, pp. 1–15 (in press)

  • Luzi L, Pergalani F, Terlien MTJ (2000) Slope vulnerability to earthquakes at sub regional scale, using probabilistic techniques and geographic information systems. Eng Geol 58:313–336

    Article  Google Scholar 

  • Mantovani F, Soeters R, van Western CJ (1996) Remote sensing techniques for landslides and hazard zonation in Europe. Geomorphology 15:213–225

    Article  Google Scholar 

  • Nagarajan R, Mukherjee A, Roy A, Khire MV (1998) Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western Ghat, India. Int J Remote Sens 19(4):573–585

    Article  Google Scholar 

  • Naithani AK (2007) Macro landslide hazard zonation mapping using univariate statistical analysis in a part of Garhwal Himalaya. J Geol Soc India 70(2):353–368

    Google Scholar 

  • Nichol JE, Wong MS (2005) Satellite remote sensing for detailed landslide inventories using change detection and image fusion. Int J Remote Sens 26:1913–1926

    Article  Google Scholar 

  • Poudyal CP, Chang C, Oh H-J, Lee S (2010) Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya. Environ Earth Sci 61(5):1049–1064

    Article  Google Scholar 

  • Pradhan B (2010) Manifestation of an advanced fuzzy logic model coupled with geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modeling. Environ Ecol Stat. doi:10.1007/s10651-010-0147-7

  • Pradhan B, Lee S (2010) Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models. Environ Earth Sci 60(5):1037–1054

    Article  Google Scholar 

  • Pradhan B, Lee S, Buchroithner MF (2009) GIS application on spatial landslide analysis using statistical based models. Proceedings of SPIE—The International Society for Optical Engineering, 7478, art. no. 74781B

  • Ramani SE, Pitchaimani K, Gnanamanickam VR (2011) GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis. J Mt Sci 8(4):505–551

    Article  Google Scholar 

  • Saranathan E, Rajesh Kumar V, Kannan M (2010) Landslide macro hazard zonation of the Yercaud Hill slope ghat section—km 10/4 to 29/6. Indian Landslides 3(1):9–16

    Google Scholar 

  • Saranathan E, Ravindar S, Chandrasekaran R, Gopinath K, Kannan M (2011) Landslide susceptibility zonation for Kumuli Ghat section, Theni District, Tamil Nadu. Indian Landslides,4(1): 45–50

    Google Scholar 

  • Sarkar S, Gupta PK (2005) Techniques for landslide hazard zonation—application to Srinagar-Rudraprayag area of Garhwal Himalaya. J Geol Soc India 70(2):217–230

    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

    Google Scholar 

  • Sujatha ER, Rajamanickam V (2011) Landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal taluk, India, using weighted similar choice fuzzy model. Nat Hazards. doi:10.1007/s11069-011-9763-2

  • Sujatha ER, Rajamanickam V, Kumaravel P, Saranathan E (2011) Landslide susceptibility analysis using probabilistic likelihood ratio model-a geospatial-based study. Arab J Geosci 1–12. doi:10.1007/s12517-011-0356-x

  • Thornes JB, Ayala IA (1998) Modelling mass failure in a Mediterranean mountain environment: climatic, geological, topographical and erosional controls. Geomorphology 24:87–100

    Article  Google Scholar 

  • Van Westen CJ (2000) The modeling of landslide hazards using GIS. Surv Geophys 21(2–3):241–255

    Article  Google Scholar 

  • Van Westen CJ (2004) Geo-information tools for landslide risk assessment: an overview of recent developments In Landslides evaluation and stabilization. In proceedings of the 9th international Symposium on Landslides, Rio de Janeiro, Brazil, London: Balkema, June 28–July 2, pp. 39–56

  • Varnes DJ (1978) Slope movement types and process. In: Landslides, analysis and control. Transportation Research Board Special Report, 176, pp. 11–33

  • Vijith H, Madhu G (2008) Estimating potential landslide sites of an upland sub-watershed in Western Ghat’s of Kerala (India) through frequency ratio and GIS. Environ Geol 55(7):1397–1405

    Article  Google Scholar 

  • Wasowski J (1998) Research articles understanding rainfall–landslide relationships in man-modified environments: a case-history from Caramanico Terme, Italy. Environ Geol 35(2–3):197–209

    Article  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 43:197–207

    Article  Google Scholar 

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Acknowledgments

The TNSCST (Tamil Nadu State Council for Science and Technology) has financially supported this work. The Highways Department, Theni district, has provided the critical locations and cooperates with us. We are grateful to Prof. R. Sethuraman, Vice Chancellor, SASTRA University, provided facilities and encouragement in carrying out this project.

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Authors and Affiliations

  1. School of Civil Engineering, SASTRA University, Thanjavur, 613 401, Tamil Nadu, India

    M. Kannan & E. Saranathan

  2. Department of Earth Science, Indian Institute of Technology-Roorkee, Roorkee, 247 667, India

    R. Anabalagan

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  1. M. Kannan
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Correspondence to M. Kannan.

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Kannan, M., Saranathan, E. & Anabalagan, R. Landslide vulnerability mapping using frequency ratio model: a geospatial approach in Bodi-Bodimettu Ghat section, Theni district, Tamil Nadu, India. Arab J Geosci 6, 2901–2913 (2013). https://doi.org/10.1007/s12517-012-0587-5

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