Landslide Susceptibility Mapping Using Frequency Ratio and Weight of Evidence Models in Purchaudi Municipality, Baitadi District, Nepal
DOI:
https://doi.org/10.3126/njes.v12i2.73671Keywords:
Frequency ratio, landslide susceptibility, Sudurpaschim, weight of evidenceAbstract
Landslides are prevalent in the Himalayas, resulting in annual fatalities and economic losses during the monsoon season. Various studies are conducted for landslide susceptibility mapping in the Himalayas however many rural settlements are under the threat of landslide. The main objective of this study is to prepare the landslide susceptibility map by using the bivariate frequency ratio (FR) and weight of evidence (WoE) models. For this study, the landslide inventory map was initially developed allocating 70% of the data for training and 30% for testing by using Landsat-8, Google Earth, and Sentinel imageries. After a thorough examination of existing literature and extensive field research, a total of twelve potential factors that can cause landslides were selected. The success and prediction rate of both models were obtained by using the area under the curve (AUC) method. The findings show that the landslide susceptibility maps prepared by the weight of evidence (WoE) and the frequency ratio (FR) models are more or less similar and have similar prediction and accuracy rates. Both the WoE and FR models exhibit a success rate of 0.703. Similarly, the accuracy rates of the FR and WoE models are 0.777 and 0.775, respectively. Both models have an accuracy and prediction rate that exceeds 70%, making them suitable for evaluating landslide susceptibility in the same terrains of Sudurpaschim province. However, the frequency ratio model shows slightly better predictive ability compared to WoE. The landslide densities derived from both models exhibit a gradual increase from low to very high susceptibility class. Nevertheless, there is no significant difference in the success and prediction rates between the two models. This result may be useful as a reference for future studies on similar terrain in Nepal.
Downloads
References
Aleotti, P., & Chowdhury, R. (1999). Landslide hazard assessment: Summary review and new perspectives. Bulletin of Engineering Geology and the Environment, 58(1), 21–44. https://doi.org/10.1007/s100640050066
Armaş, I. (2012). Weights of evidence method for landslide susceptibility mapping. Prahova Subcarpathians, Romania. Natural Hazards, 60(3), 937–950. https://doi.org/10.1007/s11069-011-9879-4
Ayalew, L., & Yamagishi, H. (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65(1–2), 15–31.
Beven, K. J., & Kirkby, M. J. (1979). A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d’appel variable de l’hydrologie du bassin versant. Hydrological Sciences Journal, 24(1), 43–69.
Bhandari, B. P., & Dhakal, S. (2021). Decadal Evolution of Landslides in the Siwalik Zone: a Case Study of Babai Watershed, Nepal. Journal of Institute of Science and Technology, 26(1), 57–62. https://doi.org/10.3126/jist.v26i1.37864
Bhandari, B. P., Dhakal, S., & Tsou, C.-Y. (2024). Assessing the Prediction Accuracy of Frequency Ratio, Weight of Evidence, Shannon Entropy, and Information Value Methods for Landslide Susceptibility in the Siwalik Hills of Nepal. Sustainability, 16(5), 2092.
Bonham-Carter, G. F. (1989). Weights of evidence modelling: A new approach to mapping mineral potential. Statistical Applications in the Earth Sciences, 171–183.
Bonham-Carter, G. F. (1994). Geographic information systems for geoscientists-modeling with GIS. Computer Methods in the Geoscientists, 13, 398.
Burt, T., & Butcher, D. (1986). Stimulation from simulation? A teaching model of hillslope hydrology for use on microcomputers. Journal of Geography in Higher Education, 10(1), 23–39.
Chung, C.-J. F., & Fabbri, A. G. (2003). Validation of spatial prediction models for landslide hazard mapping. Natural Hazards, 30, 451–472.
Collins, B. D., Kayen, R., & Tanaka, Y. (2012). Spatial distribution of landslides triggered from the 2007 Niigata Chuetsu–Oki Japan Earthquake. Engineering Geology, 127, 14–26.
Cruden, D. M., & Varnes, D. J. (1996). Landslides: Investigation and Mitigation. Transportation Research Board Special Report, 247.
Dai, F. C., Xu, C., Yao, X., Xu, L., Tu, X. B., & Gong, Q. M. (2011). Spatial Distribution of Landslides Triggered by the 2008 Ms 8.0 Wenchuan Earthquake, China. Journal of Asian Earth Sciences, 40, 883-895. https://doi.org/10.1016/j.jseaes.2010.04.010.
Ercanoglu, M., Kasmer, O., & Temiz, N. (2008). Adaptation and comparison of expert opinion to analytical hierarchy process for landslide susceptibility mapping. Bulletin of Engineering Geology and the Environment, 67(4), 565–578. https://doi.org/10.1007/s10064-008-0170-1
Fell, R., Corominas, J., Bonnard, C., Cascini, L., Leroi, E., & Savage, W. Z. (2008). Guidelines for landslide susceptibility, hazard and risk zoning for land use planning. Engineering Geology, 102(3–4), 85–98.
Getachew, N., & Meten, M. (2021). Weights of evidence modeling for landslide susceptibility mapping of Kabi-Gebro locality, Gundomeskel area, Central Ethiopia. Geoenvironmental Disasters, 8(1), 6. https://doi.org/10.1186/s40677-021-00177-z
Guzzetti, F., Mondini, A. C., Cardinali, M., Fiorucci, F., Santangelo, M., & Chang, K. T. (2012). Landslide inventory maps: New tools for an old problem. Earth Science Reviews, 112(1-2), 42-66.
Hamza, T., & Raghuvanshi, T. K. (2017). GIS based landslide hazard evaluation and zonation–A case from Jeldu District, Central Ethiopia. Journal of King Saud University-Science, 29(2), 151–165.
Hung, L. Q., Van, N. T. H., Son, P. V., Ninh, N. H., Tam, N., & Huyen, N. T. (2017). Landslide Inventory Mapping in the Fourteen Northern Provinces of Vietnam: Achievements and Difficulties. In K. Sassa, M. Mikoš, & Y. Yin (Eds.), Advancing Culture of Living with Landslides (pp. 501–510). Springer International Publishing. https://doi.org/10.1007/978-3-319-59469-9_44
Jana, S. K., Sekac, T., & Pal, D. K. (2019). Geo-spatial approach with frequency ratio method in landslide susceptibility mapping in the Busu River catchment, Papua New Guinea. Spatial Information Research, 27(1), 49–62. https://doi.org/10.1007/s41324-018-0215-x
Karimi, S. E., Ownegh, M., Sadaldin, A., & Mashayekhan, A. (2011). Probabilistic Landslide Risk Analysis and Mapping (Case Study: Chehel-Chai Watershed, Golestan Province, Iran).
Kavzoglu, T., Sahin, E. K., & Colkesen, I. (2014). Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression. Landslides, 11, 425–439.
Kayastha, P., Dhital, M. R., & De Smedt, F. (2013). Application of the analytical hierarchy process (AHP) for landslide susceptibility mapping: A case study from the Tinau watershed, west Nepal. Computers & Geosciences, 52, 398–408.
Khan, H., Shafique, M., Khan, M. A., Bacha, M. A., Shah, S. U., & Calligaris, C. (2019). Landslide susceptibility assessment using Frequency Ratio, a case study of northern Pakistan. The Egyptian Journal of Remote Sensing and Space Science, 22(1), 11–24.
Lee, S., & Min, K. (2001). Statistical analysis of landslide susceptibility at Yongin, Korea. Environmental Geology, 40(9).
Lee, S., & Pradhan, B. (2010). Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models. Landslides, 4(1), 33–41.
Lee, S., & Sambath, T. (2006). Landslide susceptibility mapping in the Damrei Romel area, Cambodia using frequency ratio and logistic regression models. Environmental Geology, 50(6), 847–855. https://doi.org/10.1007/s00254-006-0256-7
Manchado, M.T.; Allen, A.S.; Ballesteros-Canovas, J.A.; Dhakal, A.; Dhital, M.R.; Stoffel, M. Three decades of landslide activity in Western Nepal: New insights into trends and climate drivers. Landslides 2021, 18, 2001–2015.
Mathew, J., Jha, V., & Rawat, G. (2007). Application of binary logistic regression analysis and its validation for landslide susceptibility mapping in part of Garhwal Himalaya, India. International Journal of Remote Sensing, 28(10), 2257–2275.
Mezughi, T. H., Akhir, J. M., Rafek, A. G., & Abdullah, I. (2011). Landslide susceptibility assessment using frequency ratio model applied to an area along the EW highway (Gerik-Jeli). American Journal of Environmental Sciences, 7(1), 43.
Mondal, S., & Mandal, S. (2019). Landslide susceptibility mapping of Darjeeling Himalaya, India using index of entropy (IOE) model. Applied Geomatics, 11(2), 129–146. https://doi.org/10.1007/s12518-018-0248-9
Moore, I. D., Grayson, R., & Ladson, A. (1991). Digital terrain modelling: A review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5(1), 3–30.
Petley, D. (2012). Global patterns of loss of life from landslides. Geology, 40(10), 927–930.
Pisano, L., Zumpano, V., Malek, Ž., Rosskopf, C. M., & Parise, M. (2017). Variations in the susceptibility to landslides, as a consequence of land cover changes: A look to the past, and another towards the future. Science of The Total Environment, 601, 1147–1159.
Pokhrel, K., & Bhandari, B. P. (2019). Identification of potential landslide susceptible area in the lesser Himalayan Terrain of Nepal. Journal of Geoscience and Environment Protection, 7(11), 24–38.
Pourghasemi, H. R., Teimoori Yansari, Z., Panagos, P., & Pradhan, B. (2018). Analysis and evaluation of landslide susceptibility: A review on articles published during 2005–2016 (periods of 2005–2012 and 2013–2016). Arabian Journal of Geosciences, 11(9), 193. https://doi.org/10.1007/s12517-018-3531-5
Pradhan, B. (2010). Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches. Journal of the Indian Society of Remote Sensing, 38(2), 301–320. https://doi.org/10.1007/s12524-010-0020-z
Pradhan, U., Shrestha, R., KC, S., & Sharma, S. (2002). Geological map of petroleum exploration block—7, Malangawa, Central Nepal (Scale: 1: 250,000). Petroleum Exploration Promotion Project, Department of Mines and Geology, Kathmandu.
Rasyid, A. R., Bhandary, N. P., & Yatabe, R. (2016). Performance of frequency ratio and logistic regression model in creating GIS based landslides susceptibility map at Lompobattang Mountain, Indonesia. Geoenvironmental Disasters, 3(1), 19. https://doi.org/10.1186/s40677-016-0053-x
Regmi, A.D.; Devkota, K.C.; Yoshida, K.; Pradhan, B.; Pourghasemi, H.R.;Kumamoto, T.; Akgun, A. Application of frequency ratio, statistical index, and Weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya. Arab. J. Geosci. 2013, 7, 725–742.
Regmi, A. D., Devkota, K. C., Yoshida, K., Pradhan, B., Pourghasemi, H. R., Kumamoto, T., & Akgun, A. (2014). Application of frequency ratio, statistical index, and weights-of-evidence models and their comparison in landslide susceptibility mapping in Central Nepal Himalaya. Arabian Journal of Geosciences, 7, 725–742.
Reichenbach, P., Rossi, M., Malamud, B. D., Mihir, M., & Guzzetti, F. (2018). A review of statistically-based landslide susceptibility models. Earth-Science Reviews, 180, 60–91.
Shahi, Y. B., Kadel, S., Dangi, H., Adhikari, G., KC, D., & Paudyal, K. R. (2022). Geological Exploration, Landslide Characterization and Susceptibility Mapping at the Boundary between Two Crystalline Bodies in Jajarkot, Nepal. Geotechnics, 2(4), 1059–1083.
Sun, X., Chen, J., Li, Y., & Rene, N. N. (2022). Landslide Susceptibility mapping along a rapidly uplifting river valley of the Upper Jinsha River, Southeastern Tibetan Plateau, China. Remote Sensing, 14(7), 1730.
Thapa, D., & Bhandari, B. P. (2019). GIS-Based frequency ratio method for identification of potential landslide susceptible area in the Siwalik zone of Chatara-Barahakshetra section, Nepal. Open Journal of Geology, 9(12), 873.
Thapa, P. B. (2015). Occurrence of landslides in Nepal and their mitigation options. Journal of Nepal Geological Society, 49(1), 17–28.
Van Westen, C., Rengers, N., & Soeters, R. (2003). Use of geomorphological information in indirect landslide susceptibility assessment. Natural Hazards, 30, 399–419.
Xu, C., Xu, X., Dai, F., Wu, Z., He, H., Shi, F., Wu, X., & Xu, S. (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. Natural Hazards, 68, 883–900.
Zhu, A.-X., Wang, R., Qiao, J., Qin, C.-Z., Chen, Y., Liu, J., Du, F., Lin, Y., & Zhu, T. (2014). An expert knowledge-based approach to landslide susceptibility mapping using GIS and fuzzy logic. Geomorphology, 214, 128–138.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Central Department of Environmental Science, Tribhuvan University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
