Abstract
A GIS-based statistical methodology for landslide susceptibility zonation is described and its application to a study area in the Western Ghats of Kerala (India) is presented. The study area was approximately 218.44 km2 and 129 landslides were identified in this area. The environmental attributes used for the landslide susceptibility analysis include geomorphology, slope, aspect, slope length, plan curvature, profile curvature, elevation, drainage density, distance from drainages, lineament density, distance from lineaments and land use. The quantitative relationship between landslides and factors affecting landslides are established by the data driven-Information Value (InfoVal) — method. By applying and integrating the InfoVal weights using ArcGIS software, a continuous scale of numerical indices (susceptibility index) is obtained with which the study area is divided into five classes of landslide susceptibility. In order to validate the results of the susceptibility analysis, a success rate curve was prepared. The map obtained shows that a great majority of the landslides (74.42%) identified in the field were located in susceptible and highly susceptible zones (27.29%). The area ratio calculated by the area under curve (AUC) method shows a prediction accuracy of 80.45%. The area having a high scale of susceptibility lies on side slope plateaus and denudational hills with high slopes where drainage density is relatively low and terrain modification is relatively intense.
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References
Akgün A and Bulut F (2007) GIS-based landslide susceptibility for Arsin-Yomra (Trabzon, North Turkey) region. Environmental Geology 51(8): 1377–1387
Aleotti P and Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bulletin of Engineering Geology and the Environment 58: 21–44
Ayalew L, Yamagishi H and Ugawa N (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano river, Niigata Prefecture, Japan. Landslides 1: 73–81
Brenning A (2005) Spatial prediction models for landslide hazards: review, comparison and evaluation. Natural Hazards and Earth System Sciences 5: 853–862
Carrara A, Guzzetti F, Cardinali M and Reichenbach P (1999) Use of GIS technology in the prediction and monitoring of landslide hazard. Natural Hazards 20: 117–135
Chung C F and Fabbri A G (1999) Probabilistic prediction models for landslide hazard mapping. Photogrammetric Engineering & Remote Sensing 65(12): 1389–1399
Chung C F and Fabbri A G (2003) Validation of spatial prediction models for landslide hazard mapping. Natural Hazards 30: 451–472
Clerici A, Perego S, Tellini C and Vescovi P (2002) A procedure for landslide susceptibility zonation by the conditional analysis method. Geomorphology 48: 349–364
Dai F C and Lee C F (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Geomorphology 42: 213–228
Ercanoglu M, Gokceoglu C and Van Asch ThW J (2004) Landslide susceptibility zoning north of Yenice (NW Turkey) by multivariate statistical techniques. Natural Hazards 32: 1–23
Fall M, Azzam R and Noubactep C (2006) A multimethod approach to study the stability of natural slopes and landslide susceptibility mapping. Engineering Geology 82: 241–263
Guzzetti F, Carrara A, Cardinali M and 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
Jeganathan C and Chauniyal D D (2000) An evidential weighted approach for landslide hazard zonation from geo-environmental characterization: A case study of Kelani area. Current Science 79(2): 238–243
Lana H X, Zhoua C H, Wang L J, Zhang H Y and Li RH (2004) Landslide hazard spatial analysis and prediction using GIS in the Xiaojiang watershed, Yunnan, China. Engineering Geology 76: 109–128
Lee S and Biswajeet P (2006) Landslide hazard assessment at Cameron highland Malaysia using frequency ratio and logistic regression models. Geophysical Research Abstracts 8 Sref-ID:1607-7962/Gra/EGU06-A-03241
Lee S and Min K (2001) Statistical analysis of landslide susceptibility at Yongin, Korea. Environmental Geology 40: 1095–1113
Lee S and Sambath T (2006) Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology 50: 847–855
Lu PF and An P (1999) A metric for spatial data layers in favorability mapping for geological events. IEEE Transactions in Geoscience and Remote Sensing 37: 1194–1198
Nagarajan R, Mukherjee A, Roy A and Khire MV (1998) Temporal remote sensing data and GIS application in landslide hazard zonation of part of Western Ghat, India. International Journal of Remote Sensing 19: 573–585
Popescu M E (1994) A suggested method for reporting landslide causes. Bulletin of International Association of Engineering Geology 50: 71–74
Remondo J, González A, De Terán J R D, Cendrero A, Chung C F and Fabbri A G (2003) Validation of landslide susceptibility maps; examples and applications from a case study in northern Spain. Natural Hazards 30: 437–449
Saha AK, Gupta RP and Arora MK (2002) GIS-based landslide hazard zonation in the Bhagirathi (Ganga) valley, Himalayas. International Journal of Remote Sensing 23: 357–369
Saha AK, Gupta RP, Sarkar I, Arora MK and Csaplovics E (2005) An approach for GIS-based statistical landslide susceptibility zonation-with a case study in the Himalayas. Landslides 2: 321–328
Santacana N, Baeza B, Corominas J, De Paz A and Marturiá J (2003) A GIS-based multivariate statistical analysis for shallow landslide susceptibility mapping in La Pobla De Lillet area (Eastern Pyrenees, Spain). Natural Hazards 30: 281–295
Sarkar S and Kanungo DP (2004) An integrated approach for landslide susceptibility mapping using remote sensing and GIS. Photogrammetric Engineering and Remote Sensing 70: 617–625
Suzen ML and Doyuran V (2004) Data driven bivariate landslide susceptibility assessment using geographical information systems: a method and application to Asarsuyu catchment, Turkey. Engineering Geology 71: 303–321
Thampi PK, Mathai J, Sankar G and Sidharthan S (1997) Evaluation study in terms of landslide mitigation in parts of Western Ghats, Kerala, Technical report. Center for Earth Science Studies, Trivandrum
van Westen CJ (1997) Statistical landslide hazard analysis. In: Application guide, ILWIS 2.1 for Windows. ITC, Enschede, The Netherlands, pp 73–84
van Westen CJ (2000) The Modelling of Landslide Hazards Using GIS. Surveys in Geophysics 21: 241–255
van Westen CJ, Rengers N and Soeters R (2003) Use of Geomorphological Information in Indirect Landslide Susceptibility Assessment. Natural Hazards 30: 399–419
Vijith H and Madhu G (2007a) Estimating potential landslide sites of an upland sub-watershed in Western Ghats of Kerala (India) through frequency ratio and GIS. Environmental Geology DOI10.1007/s00254-007-1090-2
Vijith H and Madhu G (2007b) Application of GIS and frequency ratio model in mapping the potential surface failure sites in the Poonjar sub-watershed of Meenachil river in Western Ghats of Kerala. Journal of the Indian Society of Remote Sensing 35(3): 262–271
Wu Y, Yin K and Liu Y (eds.) (2000) Information analysis system for landslide hazard zonation. In: E Bromhead, N Dixon and ML Ibsen. Landslides in Research, Theory and Practice, 3, Thomas Telford, London, 1593–1598
Yin KL and Yan TZ (1988) Statistical prediction model for slope instability of metamorphosed rocks. In: Landslides-Glissements de Terrain. Proceedings V International Symposium on Landslides, Vol. 2, Lausanne, Switzerland, pp 1269–1272
Zezere J L (2002) Landslide susceptibility assessment considering landslide typology. A case study in the area north of Lisbon (Portugal). Natural Hazards and Earth System Sciences 2: 73–82
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Vijith, H., Rejith, P.G. & Madhu, G. Using InfoVal method and GIS techniques for the spatial modelling of landslide susceptibility in the upper catchment of river Meenachil in Kerala. J Indian Soc Remote Sens 37, 241–250 (2009). https://doi.org/10.1007/s12524-009-0028-4
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DOI: https://doi.org/10.1007/s12524-009-0028-4