Geomechanics and Engineering

  • 제37권2호
  • /
  • Pages.135-147
  • /
  • 2024
  • /
  • 2005-307X(pISSN)
  • /
  • 2092-6219(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Assessing landslide susceptibility along the Halong - Vandon expressway in Quang Ninh province, Vietnam: A comprehensive approach integrating GIS and various methods

  • Nguyen-Vu Luat (Gia Dinh University) ;
  • Tuan-Nghia Do (Faculty of Civil Engineering, Thuyloi University) ;
  • Lan Chau Nguyen (Faculty of Civil Engineering, University of Transportation and Communications) ;
  • Nguyen Trung Kien (Institute of Geological Sciences-Vietnam Academy of Science and Technology)
  • 투고 : 2023.05.08
  • 심사 : 2024.03.28
  • 발행 : 2024.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

A GIS-based landslide susceptibility mapping (LSM) was carried out using frequency ratio (FR), modified frequency ratio (M-FR), analytic hierarchy process (AHP), and modified analytic hierarchy process (M-AHP) methods to identify and delineate the potential failure zones along the Halong - Vandon expressway. The thematic layers of various landslide causative factors were generated for modeling in GIS, including geology, rainfall, distance to fault, distance to road, slope, aspect, landuse, density of landslide, vertical relief, and horizontal relief. In addition, a landslide inventory along the road network was prepared using data provided by the management department during the course of construction and operation from 2017 to 2019, when many landslides were documented. The validation results showed that the M-FR method had the highest AUC value (AUC = 0.971), which was followed by the FR method with AUC = 0.961. The AUC values were 0.939 and 0.892 for the M-AHP and AHP methods, respectively. The generated LSM obtained from M-FR method classified the study area into five susceptibility classes: very low (0), low (0-1), moderate (1-2), high (2-3), and very high (3-4) classes, which could be useful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.

키워드

과제정보

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 105.08-2020.25.

참고문헌

  1. An, H., Viet, T.T., Lee, G., Kim, Y., Kim, M., Noh, S. and Noh, J. (2016), "Development of time-variant landslide-prediction software considering three-dimensional subsurface unsaturated flow", Environ. Model. Softw., 85, 172-183. https://doi.org/10.1016/j.envsoft.2016.08.009.
  2. Ayalew, L., Yamagishi, H., Marui, H. and Kanno, T. (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. https://doi.org/10.1016/j.enggeo.2005.08.004.
  3. Begueria, S. (2006), "Validation and evaluation of predictive models in hazard assessment and risk management", Nat. Hazards, 37(3), 315-329. https://doi.org/10.1007/s11069-005-5182-6.
  4. Chowdhuria, I., Pal, S.C., Saha, A., Chakrabortty, R. and Roy, P. (2022), "Profitable agricultural land use planning in a red and lateritic soil of subtropical environment using field-based index of crop suitability (ICS)", Geocarto Int., 37(27), 17603-17624. https://doi.org/10.1080/10106049.2022.2129840.
  5. Chauhan, S., Sharma, M., Arora, M.K. and Gupta, N.K. (2010), "Landslide susceptibility zonation through ratings derived from Artificial Neural Network", Int. J. Appl. Earth Observ. Geoinform., 12, 340-350. https://doi.org/10.1016/j.jag.2010.04.006.
  6. Corominas, J., van Westen, C., Frattini, P., Cascini, L., Malet, J.P., Fotopoulou, S., Catani, F., van Den Eeckhaut, M., Mavrouli, O., Agliardi, F., Pitilakis, K., Winter, M.G., Pastor, M., Ferlisi, S., Tofani, F., Hervas, J. and Smith, J.T. (2014), "Recommendations for the quantitative analysis of landslide risk", Bull. Eng. Geol. Environ., 73(2), 209-263. https://doi.org/10.1007/s10064-013-0538-8.
  7. Dai, F.C., Lee, C.F., Li, J. and Xu, Z.W. (2001), "Assessment of landslide susceptibility on the natural terrain of Lantau Island, Hong Kong", Environ. Geol., 40(3), 381-391. https://doi.org/10.1007/s002540000163.
  8. Ercanoglu, M. and 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(3-4), 229-250. https://doi.org/10.1016/j.enggeo.2004.06.001.
  9. Fawcett, T. (2006), "An introduction to ROC analysis", Pattern Recognit. Lett., 27(8), 861-874. https://doi.org/10.1016/j.patrec.2005.10.010.
  10. Guzzetti, F., Mondini, A.C., Cardinali, M., Fiorucci, F., Santangelo, M. and Chang, K.T. (2012), "Landslide inventory maps: New tools for an old problem", Earth-Sci. Rev., 112(1-2), 42-66. https://doi.org/10.1016/j.earscirev.2012.02.001.
  11. Jenks, G.F. (1967), The data model concept in statistical mapping. Int. Year Book Cartogr, 7, 186-190.
  12. Lee, S. and Talib, J.A. (2005), "Probabilistic landslide susceptibility and factor effect analysis", Environ. Geol., 47(7), 982-990. https://doi.org/10.1007/s00254-005-1228-z.
  13. Li, L.P., Lan, H.X., Guo, C.B., Zhang, Y.S., Li, Q.W. and Wu, Y.M. (2017), "A modified frequency ratio method for landslide susceptibility assessment", Landslides, 14, 727-741. https://doi.org/ 10.1007/s10346-016-0771-x.
  14. Luat, N.V., Nguyen, V.Q., Lee, S., Woo, S. and Lee, K. (2020), "An evolutionary hybrid optimization of MARS model in predicting settlement of shallow foundations on sandy soils", Geomech. Eng., 21(6), 583-598. https://doi.org/10.12989/gae.2020.21.6.583.
  15. Luat, N.V., Shin, J. and Lee, K. (2022), "Hybrid BART-based models optimized by nature-inspired metaheuristics to predict ultimate axial capacity of CCFST columns", Eng. Comput., 38(2), 1421-1450. https://doi.org/10.1007/s00366-020-01115-7.
  16. Nefeslioglu, H.A., Sezer, E.A., Gokceoglu, C. and Ayas, Z. (2013), "A modified analytical hierarchy process (M-AHP) approach for decision support systems in natural hazard assessments", Comput. Geosci., 59, 1-8. https://doi.org/10.1016/j.cageo.2013.05.010.
  17. Nguyen, L.C., Tien, P.V. and Do, T.N. (2020), "Deep-seated rainfall-induced landslides on a new expressway: a case study in Vietnam", Landslides, 17(2), 395-407. https://doi.org/10.1007/s10346-019-01293-6.
  18. Pourghasemi, H.R., Moradi, H.R. and Fatemi Aghda, S.M. (2013), "Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances", Nat. Hazards, 69(1), 749-779. https://doi.org/10.1007/s11069-013-0728-5.
  19. Pradhan, B. (2010), "Landslide susceptibility mapping of a catchment area using frequency ratio, fuzzy logic and multivariate logistic regression approaches", J. Indian Soc. Remote Sens., 38(2), 301-320. https://doi.org/10.1007/s12524-010-0020-z.
  20. Regmi, A.D., Devkota, K.C., Yoshida, K., Pradhan, B., Pourghasemi, H.R., Kumamoto, T. and 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", Arab. J. Geosci., 7(2), 725-742. https://doi.org/10.1007/s12517-012-0807-z.
  21. Saaty, T.L. (1977), "A scaling method for priorities in hierarchical structures", J. Math. Psychol., 15(3), 234-281. https://doi.org/https://doi.org/10.1016/0022-2496(77)90033-5.
  22. Shano, L., Raghuvanshi, T. K., and Meten, M., (2020), "Landslide susceptibility evaluation and hazard zonation techniques - a review", Geoenviron. Disasters, 7(18). https://doi.org/10.1186/s40677-020-00152-0.
  23. Shahabi, H., Khezri, S., Ahmad, B.B. and Hashim, M. (2014), "Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models", Catena, 115, 55-70. https://doi.org/10.1016/j.catena.2013.11.014.
  24. Soeters, R. and Westen, C.J. (1996), Slope instability Recognition, analysis and zonation, (Eds., Turner, A.K. and Schuster, R.L.), Landslide Investig. Mitigation. Spec. Report, Vol. 247. Transp. Res. Board, Natl. Res. Counc. Natl. Acad. Press, Washington, D.C.
  25. Soeters, R. and Westen, V.A.N. (1984), "Slope instability recognition, analysis and zonation", Landslides, Investig. Mitigation, Transp. Res. Board, Natl. Res. Counc., 129-177.
  26. Suzen, M.L. and Doyuran, V. (2004), "A comparison of the GIS based landslide susceptibility assessment methods: Multivariate versus bivariate", Environ. Geol., 45(5), 665-679. https://doi.org/10.1007/s00254-003-0917-8.
  27. Saha, A., Tripathi, L., Villuri, V.G.K. and Bhardwaj, A. (2024), "Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology", Environ. Sci. Pollut. Res., 31, 10443-10459. https://doi.org/10.1007/s11356-023-31670-7.
  28. Saha, A., Villuri, V.G.K. and Bhardwaj, A. (2022), Development and Assessment of GIS-Based Landslide Susceptibility Mapping Models Using ANN, Fuzzy-AHP, and MCDA in Darjeeling Himalayas, West Bengal, Land., 11, 1711-1737. https://doi.org/10.3390/land11101711.
  29. Saha, A., Villuri, V.G.K., Bhardwaj, A. and Kumar, S. (2023a), "A Multi-Criteria Decision Analysis (MCDA) approach for landslide susceptibility mapping of a part of darjeeling district in North-East Himalaya, India", Appl. Sci., 13, 5062-5084. https://doi.org/10.3390/app13085062.
  30. Saha, A., Villuri, V.G.K. and Bhardwaj, A. (2023b), "Development and assessment of a novel hybrid machine learning-based landslide susceptibility mapping model in the Darjeeling Himalayas", Stoch. Environ. Res. Risk Assess. https://doi.org/10.1007/s00477-023-02528-8
  31. Rawat, A., Kumar, D., Chatterjee, R.S. and Kumar, H. (2022), "A GIS-based liquefaction susceptibility mapping utilising the morphotectonic analysis to highlight potential hazard zones in the East Ganga plain", Environ. Earth, 81, 358. https://doi.org/10.1007/s12665-022-10468-9.
  32. van Westen, C.J. (1994), GIS in landslide hazard zonation: A review, with examples from the Andes Colombia, Mt. Environ. Geogr. Inf. Syst., (May), 135-165.
  33. Wang, Y.T., Seijmonsbergen, A.C., Bouten, W. and Chen, Q.T. (2015), "Using statistical learning algorithms in regional landslide susceptibility zonation with limited landslide field data", J. Mt. Sci., 12, 268-288. https://doi.org/10.1007/s11629-014-3134-x
  34. Wieczorek, G.F. (1983), "Preparing a detailed landslide-inventory map for hazard evaluation and reduction", Bull. Assoc. Eng. Geol., 21, 337-342. https://doi.org/10.2113/gseegeosci.xxi.3.337.
  35. Yalcin, A., Reis, S., Aydinoglu, A.C. and Yomralioglu, T. (2011), "A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon NE Turkey", Catena, 85(3), 274-287. https://doi.org/10.1016/j.catena.2011.01.014.
  36. Yu, T.T., Wang, T.S. and Cheng, Y.S. (2015), "Analysis of factors triggering shallow failure and deep-seated landslides induced by single rainfall events", J. Disaster Res., 10(5), 966-972. https://doi.org/10.20965/jdr.2015.p0966.