IJEP 42(7): 849-856 : Vol. 42 Issue. 7 (July 2022)
1. University of Madras, Centre for Natural Hazards and Disaster Studies (CNHDS), Chennai-600 005, Tamil Nadu, India
2. Mizoram University, Department of Geography and Resource Management, Aizawl – 796 004, Mizoram, India
Abstract
The landslide susceptibility is the probability of occurrence of landslide in an area which is predicted based on the certain local condition of the terrain. There are number of landslide probability methodologies which have been used by researchers for last few years. The objective of this paper is to assess the landslide susceptibility in the part of the Tehri dam in the state of Uttrakhand, India. Total of 198 landslides have been recognized using world view-2 satellite image and Geological Survey of India (GSI). In this study five most important causative factors have been taken, such as slope, aspect, geology, drainage and landuse/ land cover. Remote sensing data and ancillary data have been used to prepare landslide inventory map and thematic layers for susceptibility zonation mapping. Slope, aspect and drainage maps have been derived from the ASTER DEM satellite data. Geology map has been taken from the Geological Survey of India. Landuse/ land cover map has been prepared using world view -2. Each causative factor was given weight on the basis of information value (IV) method. The IV method is statistics-based methodology which is used as a landslide probability technique. The final landslide susceptibility map was prepared by using the sum of each weighted value on the GIS platform. The result of this study was classified into five classes, such as very high, high, moderate, low and very low. The final map will be helpful for the local people, engineers and planner for mitigating the hazard and also demarcate the highly vulnerable and low vulnerable zones in the study area.
Keywords
Information value, Geographical information system, Landslide, Susceptibility, Tehri dam
References
- Varnes, D.J. 1984. Landslide hzard zonation: A review of principles and practice. Natural Hazards, UNESCO, Paris.
- Hutchinson, J.N. 1995. Landslide hazard assessment (keynote paper). In Landslides. Ed D. H. Bell. 6th International Symposium on Landslides, Christchurch (vol. 1), Balkema, Rotterdam. Proceeding, pp 1805-1841.
- Brabb, E. E. 1984. Innovative approaches to landslide hazard mapping. 4th International Symposium on Landslides, Toronto. Proceedings, 1(1) : 307–324.
- Anbalagan, R. 1992. Landslide hazard evaluation and zonation mapping in mountainous terrain. Eng. Geol., 32 : 269–277.
- Yalcin, A. 2008. GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena. 72:1-12. DOI: 10.1016/j.catena.2007.01.003.
- Althuwaynee, O.F., B. Pradhan and N. Ahmad. 2014. Landslide susceptibility mapping using decision-tree based Chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration. IOP Conference Series Earth Env. Sci., 20:12032.
- Ahmed, B. 2015. Landslide susceptibility modelling applying user-defined weighting and data-driven statistical techniques in Cox’s bazar municipality, Bangladesh. Nat. Hazards. 79:1707–1737. DOI: 10.1007/s11069-015-1922-4.
- Biswas, B., V. K.S and R. Ranjan. 2021. Landslide susceptibility mapping using integrated approach of multi-criteria and geospatial techniques at Nilgiris district of India. Arab J. Geosci., 14:980. DOI: 10.1007/s12517-021-07341-763-0.
- Yin, K. L. and T.Z. Yan. 1988. Statistical prediction models for slope instability of metamorphosed rocks. In Landslides. C. Bonnard. Fifth International Symposium on Landslides, Balkema, Rotterdam. Proceedings, pp 1269–1272.
- Van Westen, C.J., et al. 1993. GISSIZ: Training package for geographic information systems in slope instability zonation. ITC, Enschede, The Netherlands.
- Chalkias C, S. Kalogirou and M. Ferentinou. 2014. Landslide susceptibility, Peloponnese peninsula in south Greece. J. Maps. 10(2):211–222. DOI: 10.1080/17445647.2014.884022.
- Kanungo, D.P., 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.
- Wubalem, A. and M. Meten. 2020. Landslide susceptibility mapping using information value and logistic regression models in Goncha Siso Eneses area, northwestern Ethiopia. SN Appl. Sci., 2:807. DOI: 10.1007/s42452-020-25.
- Anbalagan, R. and R. Kumar. 2015. Reservoir induced landslides- A case study of reservoir rim region of Tehri dam. TIFAC-IDRIM conference, New Delhi, India.
