Abstract
Slope failure in the mining region is one of the frequent accident events that cause damage to both property and life every year. The heavy mechanization and blasting operation in the mines generate a high degree of vibrations, which may cause slope failure. The present study attempts to develop a mechanism for predicting slope failure susceptibility index (SFSI) in mines using remote sensing and GIS technique. SFSI represents the proneness of the landslides of a particular location. The study area selected for the proposed study is the Panchpatmalli bauxite mine, NALCO, located in the Koraput District of Odisha, India. The study also demonstrates the effects of the fuzzification level of various criteria on SFSI through sensitivity analysis. The model validation results indicated that the SFSI in a reported failure zone was higher in the pre-failure condition than the post-failure conditions. Though the sensitivity analysis results showed that the SFSI significantly changed with the level of decision-making attitude and fuzzification level of the individual factors, the relative risks of the zones are more or less uniform. The study results assist in identifying the vulnerable zones, which are highly susceptible to failure. The proposed method can be used in decision-making for effective land-use planning.
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Open source data are used. The sources of the raw data are mentioned in the manuscript.
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ArcGIS software is used to process the data.
References
Ayalew, L., Yamagishi, H., Marui, H., & Kanno, T. (2005). Landslides in Sado Island of Japan: Part II GIS-based susceptibility map** with comparisons of results from two methods and verifications. Engineering Geology, 81(4), 432–445.
Basharat, M., Shah, H. R., & Hameed, N. (2016). Landslide susceptibility map** using GIS and weighted overlay method: A case study from NW Himalayas Pakistan. Arabian Journal of Geosciences, 9(4), 1–19.
Basu, T., & Pal, S. (2020). A GIS-based factor clustering and landslide susceptibility analysis using AHP for Gish River Basin, India. Environment, Development and Sustainability, 22, 4787–4819.
Caldwell, J. (2013) The Bingham Canyon Mine slope failure. [Accessed on 25th June 2020] Available at: http://www.mining.com/bingham-canyon-mine-slope-failure-37216/.
Calvello, M., Cascini, L., & Mastroianni, S. (2013). Landslide zoning over large areas from a sample inventory by means of scale-dependent terrain units. Geomorphology, 182, 33–48.
Chau, K. T., Sze, Y. L., Fung, M. K., Wong, W. Y., Fong, E. L., & Chan, L. C. P. (2004). Landslide hazard analysis for Hong Kong using landslide inventory and GIS. Computers & Geosciences, 30(4), 429–443.
Dai, F. C., & Lee, C. F. (2002). Landslide characteristics and slope instability modeling using GIS, Lantau Island Hong Kong. Geomorphology, 42(3–4), 213–228.
Dai, F. C., Lee, C. F., Li, J. X. Z. W., & Xu, Z. W. (2001). Assessment of landslide susceptibility on the natural terrain of Lantau Island Hong Kong. Environmental Geology, 40(3), 381–391.
Dhakal, A. S. (2000). Landslide hazard map** and its evaluation using GIS: An investigation of sampling schemes for a grid-cell based quantitative method. Photogrammetric Engineering and Remote Sensing, 70(8), 981–989.
Dhakal, A. S., Amada, T., & Aniya, M. (2000). Landslide hazard map** and its evaluation using GIS: An investigation of sampling schemes for a grid-cell based quantitative method. Photogrammetric Engineering and Remote Sensing, 66(8), 981–989.
El Jazouli, A., Barakat, A., & Khellouk, R. (2019). GIS-multicriteria evaluation using AHP for landslide susceptibility map** in Oum Er Rbia high basin (Morocco). Geoenvironmental Disasters, 6(1), 3.
Gilliam, F. S., Hédl, R., Chudomelová, M., McCulley, R. L., & Nelson, J. A. (2014). Variation in vegetation and microbial linkages with slope aspect in a montane temperate hardwood forest. Ecosphere, 5(5), 1–17.
Gou, C., Liu, R., & Feng, C. (2013). Gis-based landslide susceptibility map** using analytical hierarchy process in Wenchuan. In 2013 21st International Conference on Geoinformatics (pp. 1-4). IEEE.
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(1–4), 181–216.
Huang, J. (2014). Investigation on landslide susceptibility using remote sensing and GIS methods.
Kumar, R., & Anbalagan, R. (2016). Landslide susceptibility map** using analytical hierarchy process (AHP) in Tehri reservoir rim region, Uttarakhand. Journal of the Geological Society of India, 87(3), 271–286.
Martha, T. R., vanWesten, C. J., Kerle, N., Jetten, V., & Kumar, K. V. (2013). Landslide hazard and risk assessment using semi automatically created landslide inventories. Geomorphology, 184, 139–150.
Moayedi, H., Tien Bui, D., & Kok, Foong L. (2019). Slope stability monitoring using novel remote sensing based fuzzy logic. Sensors, 19(21), 4636.
Nichol, J., & Wong, M. S. (2005). Satellite remote sensing for detailed landslide inventories using change detection and image fusion. International Journal of Remote Sensing, 26(9), 1913–1926.
Odisha TV Bureau, Landslide in Koraput Disrupts Train Service, Odisha Television Ltd., (2015), odishatv.in/odisha-news/otherstories/land-slide-in-koraput-disrupts-trainservice-100223.
Omar, H., Ibrahim, A. L., & Hashimm, M. (2007). Slope stability analysis using remote sensing data. Faculty of Geo-information Science and Engineering, Universiti Teknologi Malaysia.
Panikkar, S. V., Subramanyan, V. (1997). Landslide hazard analysis of the area around Dehra Dun and Mussoorie, Uttar Pradesh. Current Science, pp.1117-1123.
Saaty, T. L. (1980). The analytic hierarchy process Mcgraw Hill. Agricultural.
Sarkar, S., Kanungo, D. P., Mehrotra, G. S. (1995). Landslide hazard zonation: a case study in Garhwal Himalaya, India. Mountain Research and Development, pp.301-309.
Sarkar, S., Kanungo, D. P., Patra, A. K., Kumar, P. (2012). GIS based landslide susceptibility map**–a case study in Indian Himalaya.
Sarkar, S., & Kanungo, D. P. (2004). An integrated approach for landslide susceptibility map** using remote sensing and GIS. Photogrammetric Engineering & Remote Sensing, 70(5), 617–625.
Shit, P. K., Bhunia, G. S., & Maiti, R. (2016). Potential landslide susceptibility map** using weighted overlay model (WOM). Modeling Earth Systems and Environment, 2(1), 21.
Sinha, B. N., Varma, R. S., & Paul, D. K. (1975). Landslides in Darjeeling District (West Bengal) and adjacent areas. Bulletins of the Geological Survey of India, Series B, 36, 45.
Vojteková, J., & Vojtek, M. (2020). Assessment of landslide susceptibility at a local spatial scale applying the multi-criteria analysis and GIS: A case study from Slovakia. Geomatics, Natural Hazards and Risk, 11(1), 131–148.
Wu, M., Shi, P., Chen, A., Shen, C., & Wang, P. (2017). Impacts of DEM resolution and area threshold value uncertainty on the drainage network derived using SWAT. Water SA, 43(3), 450–462.
Xu, C., Xu, X., Lee, Y. H., Tan, X., Yu, G., & Dai, F. (2012). The 2010 Yushu earthquake triggered landslide hazard map** using GIS and weight of evidence modeling. Environmental Earth Sciences, 66(6), 1603–1616.
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Gorai, A.K. Sensitivity Analysis of GIS-based Fuzzy-AHP Model for Prediction of Slope Failure Susceptibility Index. J Indian Soc Remote Sens 50, 715–733 (2022). https://doi.org/10.1007/s12524-021-01488-2
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DOI: https://doi.org/10.1007/s12524-021-01488-2