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Fuzzy gamma operator model for preparing landslide susceptibility zonation mapping in parts of Kohima Town, Nagaland, India

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Abstract

Growing population and expansion of settlements over hilly areas have largely increased the impact of landslide. This paper deals with the use of Geoinformatics technology and Fuzzy Gamma Operator model to map the landslide susceptibility zones in part of Kohima Town, Nagaland. For this study, eight landslide inducing parameters such as slope gradient, slope aspect, curvature, elevation, land use and land cover, drainage density, lineament density, and topographical wetness index were considered and prepared with the help of toposheet, high resolution satellite imagery such as World View II, LISS IV, DEM data and field data. Landslide inventory was the first step for the geospatial database generation which involves the mapping of past landslide details. Landslide susceptibility maps were generated by calculating relationship between the landslide inducing factors with past landslide locations using frequency ratio and fuzzy gamma operator model. The ratios were normalized between the range of 0 and 1 to obtain fuzzy membership values. The landslide susceptibility zonation (LSZ) map were prepared by integrating all the causative factors with fuzzy membership values and classified into five different susceptibility classes based on Jenks natural breaks classification viz. very high (37.51%), high (32.21%), moderate (20.97%), low (7.97%), and very low (1.34%). The LSZ map were compared with the landslide inventory map and validated with best prediction accuracy using area under curve (AUC) with the accuracy level and R-Index.

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References

  • Aier I (2005) Landslides along the Kohima-Dimapur Road: Their Causes and Possible Remedial Measures. Unpublished Ph. D. Thesis, Department of Geology, Nagaland University, Kohima

  • Akgün A, Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environ Geol 51(8):1377–1387

    Article  Google Scholar 

  • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44. doi:10.1007/s100640050066

    Article  Google Scholar 

  • Alexander D (1993) Natural disasters. Kluwer Academic Publishers, Dordrecht. pp. 242–264, 374–390

    Google Scholar 

  • Anbazhagan S, Ramesh V (2014) Landslide hazard zonation mapping in ghat road section of Kolli hills, India. J Mt Sci 11(5):1308–1325. doi:10.1007/s11629-012-2618-9

    Article  Google Scholar 

  • Ayalew L, Yamagishi H, Marui H et al (2005) Landslides in Sado Island of Japan: part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications. Eng Geol 81(4):432–445. doi:10.1016/j.enggeo.2005.08.004

    Article  Google Scholar 

  • Balamurugan G, Ramasamy SM (2006) Tectonic grains and slope with special reference to landslide in Palani to Kodaikanal Ghat road using remote sensing and GIS techniques. In: Basavaraiappa et al (ed) Remote sensing and GIS applications, Bellur Prakashana, Mysore, pp 96–102.

  • Balamurugan G, Ramesh V, Touthang M (2016) Landslide susceptibility zonation mapping using frequency ratio and fuzzy gamma operator models in part of NH-39, Manipur, India. Nat Hazards. doi:10.1007/s11069-016-2434-6

    Google Scholar 

  • Barredo JI, Benavidesz A, Herhl J et al (2000) Comparing heuristic landslide hazard assessment tech-niques using GIS in the Tirajana basin, Gran Canaria Is-land, Spain. Int J Appl Earth Obs Geoinf 2(1):9–23

    Article  Google Scholar 

  • Begueria S (2006) Validation and evaluation of predictive models in hazard assessment and risk management. Nat Hazards 37:315–329. doi:10.1007/s11069-005-5182-6

    Article  Google Scholar 

  • Beven K, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Process 15:1993–2011

    Article  Google Scholar 

  • Bonham-Carter GF (1994) Geographic information systems for geoscientists: modelling with GIS. Elsevier Butterworth-Heine-mann, Oxford, pp 292–302

    Google Scholar 

  • Carrara A (1988) Landslide hazard mapping by statistical methods:a black box model approach. In: Proc of the Work-shop on Natural Disaster in European Mediterranean Countries. Perugia, Italy. Consiglio Nazionale delle Ricerche.

  • Champati Ray PK, Dimri S, Lakhera RC et al (2007) Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya. Landslides 4:101–111. doi:10.1007/s10346-006-0068-6

    Article  Google Scholar 

  • Corominas J, Moya J (2008) A review of assessing landslide frequency for hazard zoning purposes. Eng Geol 102:193–213. doi:10.1016/j.enggeo.2008.03.018

    Article  Google Scholar 

  • Dai FC, Lee CF (2001) Frequency–volume relation and prediction of rainfall-induced landslides. Eng Geol 59:253–266

    Article  Google Scholar 

  • Dai FC, Lee CF, Ngai YY (2002) Landslide risk assessment and management: an overview. Eng Geol 64(1):65–87. doi:10.1016/S0013-7952(01)00093-X

    Article  Google Scholar 

  • Das I, Stein A, Kerle N et al (2012) Landslide susceptibility mapping along road corridors in the Indian Himalayas using Bayesian logistic regression models. Geomorphology 179:116–125

    Article  Google Scholar 

  • Devoli G, Morales A, Hoeg K (2007) Historical landslides in Nicaragua—collection and analysis of data. Landslides 4(1):518. doi:10.1007/s10346-006-0048-x.

    Article  Google Scholar 

  • Directorate of Geology Mining (DGM) (2009) Geological Hazard Studies of Six District Headquarter Townships—Dimapur, Kohima, Wokha, Mokokchung, Zunheboto and Phek. Project Report on Zunheboto Town, Order No. /Geo-Hazards/Studies/2008/832–25, Dated- 28/03/09. Dimapur, pp 117–121

  • Duman TY, Can T, Gokceoglu C et al (2006) Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul. Turkey. Environ Geol 51:241–256

    Article  Google Scholar 

  • Dussauge C, Helmstetter A, Grasso J-R et al (2002) Probabilistic approach to rock fall hazard assessment: potential of historical data analysis. Natural Hazards Earth Syst Sci 2:1–13

    Article  Google Scholar 

  • Dussauge C, Grasso J-R, Helmstetter A (2003) Statistical analysis of rockfall volume distributions: implications for rockfall dynamics. J Geophys Res 108(B6):2286. doi:10.1029/2001JB000650

    Article  Google Scholar 

  • Ehret D, Rohn J, Dumperth C et al (2010) Frequency ratio analysis of mass movements in the Xiangxi catchment, Three Gorges reservoir area, China. J Earth Sci 21(6):824–834. doi:10.1007/s12583-010-0134-9

    Article  Google Scholar 

  • 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. doi:10.1016/j.enggeo2004.06.001

    Article  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. doi:10.1016/j.cma.2003.09.016

    Article  Google Scholar 

  • Geological Survey of India (GSI) (2001) Geology and mineral map of Manipur. Ministry of Mines, Government of India

  • Guzetti F, Carrara A, Andcardinali M et al (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, central Italy. Geomorphology 31:181–216. doi:10.1016/S0169-555X(99)00078-1

    Article  Google Scholar 

  • Guzzetti F, Malamud BD, Turcotte DL et al (2002) Power-law correlations of landslide areas in central Italy. Earth Planet Sci Lett 195:169–183

    Article  Google Scholar 

  • Guzzetti F, Mondini AC, Cardinali M et al (2012) Landslide inventory maps: new tools for an old problem. Earth Sci Rev 112:42–66

    Article  Google Scholar 

  • Husain Z (2008) Landslides hazards in the Sikkim Himalaya. In: Singh S et.al (eds) Environmental changes and geomorphic hazards, Bookwell, New Delhi. pp 113–120

    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(8):2271–2285. doi:10.1007/s12665-011-1055-3

    Article  Google Scholar 

  • Jade S, Sarkar S (1993) Statistical Models for Slope Instability Classification. Eng Geol 36:91–98

    Article  Google Scholar 

  • Jenks GF (1967) The data model concept in statistical mapping. Int Year Book Cartogr 7:186–190

    Google Scholar 

  • Kannan M, Saranathan E, Anabalagan R (2013) Landslide vulnerability mapping using frequency ratio model: a geospatial approach in Bodi-Bodimettu Ghat section, Theni district, Tamil Nadu, India. Arab J Geosci 6(8):2901–2913. doi:10.1007/s12517-012-0587-5

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Sarkar S et al (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. doi:10.1016/j.enggeo.2006.03.004

    Article  Google Scholar 

  • Kanungo DP, Arora MK, Sarkar S et al (2009) A fuzzy set based approach for integration of thematic maps for landslide susceptibility zonation. Georisk 3(1):30–43. doi:10.1080/17499510802541417

    Google Scholar 

  • Lee S (2007) Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environ Geol 52:615–623. doi:10.1007/s00254-006-0491-y

    Article  Google Scholar 

  • Lee S, Pradhan B (2006) Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. J Earth Syst Sci 115(6):661–672. doi:10.1007/s12040-006-0004-0

    Article  Google Scholar 

  • Lee S, Choi J, Min K (2002) Landslide susceptibility analysis and verification using the Bayesian probability model. Environ Geol 43:120–131. doi:10.1007/s00254-002-0616-x

    Article  Google Scholar 

  • MWR Ministry of Water Resources (2013) Ground Water Information Booklet Kohima District, Nagaland. Guwahati

  • Nagarajan R, Roy A, Kumar RV et al (2000) Landslide hazard susceptibility mapping based on terrain and climatic factors for tropical monsoon regions. Bull Eng Geol Environ 58:275–287. doi:10.1007/s002540050348

    Article  Google Scholar 

  • Nandi A, Shakoor A (2008) Application of logistic regression model for slope instability prediction in Cuyahoga River Watershed, Ohio, USA. Georisk 2(1):16–27. doi:10.1080/17499510701842221.

    Google Scholar 

  • Nandi A, Shakoor A (2010) A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses. Eng Geol 110(1–2):11–20

    Article  Google Scholar 

  • Naveen Raj T, Ram Mohan V, Backiaraj S et al (2011) Landslide Hazard Zonation Using the Relative Effect method In South Eastern Part Of Nilgiris, Tamilnadu, India. Int J Eng Sci Technol (IJEST) 3(4):3260–3265

    Google Scholar 

  • Pachauri AK, Gupta PV, Chander R (1998) Landslide zoning in a part of the Garhwal Himalayas. Environ Geol 36:325–334. doi:10.1007/s100649900032

    Article  Google Scholar 

  • Parise M (2001) Landslide mapping techniques and their use in the assessment of the landslide hazard. Phys Chem Earth (C) 26:697–703

    Google Scholar 

  • Pattusamy S, Purusothaman BM (2014) Disaster management and mapping using remote sensing and GIS. J Comput Biosci Eng 1(3)

  • 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 60:1037–1054. doi:10.1007/s12665-009-0245-8

    Article  Google Scholar 

  • Pradhan B, Lee S, Buchroithner MF (2009) Use of geospatial data and fuzzy algebraic operators to landslide-hazard mapping. Appl Geomat 1:3–15. doi:10.1007/s12518-009-0001-5

    Article  Google Scholar 

  • Ramesh V, Anbazhagan S (2015) Landslide susceptibility mapping along Kolli hills Ghat road section (India) using frequency ratio, relative effect and fuzzy logic models. Environ Earth Sci 73(12):8009–8021. doi:10.1007/s12665-014-3954-6

    Article  Google Scholar 

  • Ray Champati PK, Dimri S, Lakhera RC et al (2007) Fuzzy-based method for landslide hazard assessment in active seismic zone of Himalaya. Landslides 4:101–111

    Article  Google Scholar 

  • Regmi NR, Giardino JR, McDonald EV et al (2014) A comparison of logistic regression-based models of susceptibility to landslides in western Colorado, USA. Landslides 11:247–262. doi:10.1007/s10346012-0380-2.

    Article  Google Scholar 

  • Kumar R, Anbalagan R (2015) Landslide susceptibility zonation in part of Tehri reservoir region using frequency ratio, fuzzy logic and GIS. J Earth Syst Sci 124(2):431–448

    Article  Google Scholar 

  • Saha AK, Gupta RP, Sarkar I et al (2005) An Approach for GIS-based statistical landslide susceptibility zonation—with a case Study in the Himalayas. Landslides 2:61–69

    Article  Google Scholar 

  • Sasaki Y, Abe M, Hirano I (1991) Fractals of slope failure size-number distribution. J Jpn Soc Eng Geol 32:1–11

    Article  Google Scholar 

  • Shirzadi A, Saro L, Joo OH et al (2012) A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: salavat Abad case study, Kurdistan, Iran. Nat Hazards 64:1639–1656

    Article  Google Scholar 

  • Srivastava V, Srivastava H, Lakhera RC (2010) Fuzzy gamma based geomatic modeling for landslide hazard susceptibility in a part of Tons river valley, northwest Himalaya, India. Geomat Nat Hazards Risk 1(3):225–242

    Article  Google Scholar 

  • Sujatha ER, Kumaravel P, Rajamanickam GV (2011) GIS based landslide susceptibility mapping of Tevankarai Ar sub-watershed, Kodaikkanal, India using binary logistic regression analysis. J Mt Sci 8:505–517. doi:10.1007/s11629-011-2157-9

    Article  Google Scholar 

  • Sujatha ER, Rajamanickam V, Kumaravel P et al (2013) Landslide susceptibility analysis using probabilistic likelihood ratio model—a geospatial-based study. Arab J Geosci 6:429–440. doi:10.1007/s12517-011-0356-x

    Article  Google Scholar 

  • Supongtemjen (2006) Geological investigation of land instability between Kohima and Zhadima. Unpublished Ph. D. Thesis, Department of Geology, Nagaland University, Kohima

  • Tangestani MH (2004) Landslide susceptibility mapping using the fuzzy gamma approach in a GIS, Kakan catchment area, southwest Iran. Aust J Earth Sci 51(3):439–450

    Article  Google Scholar 

  • Thong GT, Thingo V, Walling T (2006). Geotechnical Investigations of Land Instability in Kohima Town and along NH 39, between Chumukedima and Kohima. Project Report of ISRO Project. No. 10/4/415, 2002, Kohima

  • Tunusluoglu MC, Gokceoglu C, Nefeslioglu HA, Sonmez H (2008) Extraction of potential debris source areas by logistic regression technique: a case study from Barla, Besparmak and Kapi mountains (NW Taurids, Turkey). Environ Geol 54(1):9–22

    Article  Google Scholar 

  • Van Westen CJ (1997) Statistical Landslide Hazard Analysis. In: Application Guide, ILWIS 2.1 for WindowsITC, Enschede, The Netherlands, pp 73–84

  • Van Westen CJ, Terlien MTJ (1996) An approach towards deterministic landslide hazard analysis in GIS. A case study from Manizales (Colombia). Earth Surf Processes Landf 21(9):853–868

    Article  Google Scholar 

  • Varnes DJ (1984) Landslide hazard zonation: a review of principles and practice. UNESCO, Paris, pp 1–63

    Google Scholar 

  • Walling T (2005) Geological investigation of land instability in Kohima Town, Nagaland. Unpublished PhD thesis, Nagaland University, Kohima

  • Xu C, Xu X, Dai F et al (2013) Application of an incomplete landslide inventory, logistic regression model and its validation for landslide susceptibility mapping related to the May 12, 2008 Wenchuan earthquake of China. Nat Hazards 68:883–900. doi:10.1007/s11069-0130661-7

    Article  Google Scholar 

  • Yilmaz I, Keskin I (2009) GIS based statistical and physical approaches to landslide susceptibility mapping (Sebinkarahisar, Turkey). Bull Eng Geol Environ 68:459–471. doi:10.1007/s10064-009-0188-z

    Article  Google Scholar 

  • Yilmaz I, Marschalko M, Bednarik M (2012) Comments on, Landslide susceptibility zonation study using remote sensing and GIS technology in the Ken-Betwa River Link area, India, by Avtar, R., Singh, C.K., Singh, G., Verma, R.L., Mukherjee, S., Sawada, H., in Bulletin of Engineering Geology and the Environment. pp 803–804. Bull Eng Geol Environ 71:803–805. doi:10.1007/s10064-011-0406-3

    Article  Google Scholar 

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

  • Zadeh LA (1965) Fuzzy sets information and control. Inf control 8:338–353

    Article  Google Scholar 

  • Zimmermann HJ (1996) Fuzzy set theory and it applications. Kluwer Academic Publishers, Norwell p 435

    Book  Google Scholar 

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Acknowledgements

The authors acknowledge the University Grant Commission, New Delhi for providing RGNF fellowship grant for the Ph. D research work. The authors also thank Nagaland GIS and Remote Sensing Centre for providing data for this research.

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  1. Centre for Geoinformatics, Tata Institute of Social Sciences (TISS), Malti and Jal A. D. Naoroji Campus (Annex), Post Box No: 8313, Deonar Farm Road, Deonar, Mumbai, 400088, Maharashtra, India

    Hinotoli V. Sema, Balamurugan Guru & Ramesh Veerappan

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Sema, H.V., Guru, B. & Veerappan, R. Fuzzy gamma operator model for preparing landslide susceptibility zonation mapping in parts of Kohima Town, Nagaland, India. Model. Earth Syst. Environ. 3, 499–514 (2017). https://doi.org/10.1007/s40808-017-0317-9

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