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Assessment of co-seismic landslide susceptibility using LR and ANCOVA in Barpak region, Nepal

  • Suchita Shrestha
  • Tae-Seob Kang
  • Jung Chang Choi
Article

Abstract

Nepal was affected by a catastrophic earthquake with Mw 7.8 on 25th April, 2015 with its epicenter in the central part of Barpak village. A number of co-seismic landslides were triggered by the main shock of the event and associated aftershocks. Due to the rugged topography and vicinity of the main shock, the village was extremely affected by co-seismic landslides. In total, 59 landslides were identified using Google Earth and were verified during the field survey in Barpak village. Furthermore, 11 conditioning factors, including Peak ground acceleration (PGA), epicenter proximity, fault proximity, geology, slope, elevation, plan curvature, profile curvature, topographic wetness index, drainage proximity and the sediment transport index were selected as independent variables for analysis. In this study, logistic regression (LR) and analysis of covariance (ANCOVA) models were used and their performance was assessed. Finally, the landslide susceptibility classes were produced and an evaluation of models was done by using receiver operating characteristic curves. The area under the curve for LR and ANCOVA showed 85.38 and 78.4% accuracy, respectively. Based on the overall assessments, the LR model was more accurate than the ANCOVA model for co-seismic landslide prediction in the study area. The result of this study can be used to mitigate landslide-induced hazards and for land-use planning.

Keywords

Analysis of covariance co-seismic landslide GIS logistic regression landslide susceptibility 

Notes

Acknowledgements

This work was supported by a Research Grant of Pukyong National University (in the year 2016).

References

  1. Beven K J and Kirkby M J 1979 A physically based, variable contributing area model of basin hydrology/Un modèle à base physique de zone d’appel variable del’hydrologie du bassin versant; Hydrol. Sci. J. 24(1) 43–69.CrossRefGoogle Scholar
  2. Bednarik M, Magulová B, Matys M and Marschalko M 2010 Landslide susceptibility assessment of the Kra_ovany–Liptovský Mikuláš railway case study; Phys. Chem. Earth Parts A/B/C 35(3) 162–171.CrossRefGoogle Scholar
  3. Bray J D, Rathje E M, Augello A J and Merry S M 1998 Simplified seismic design procedure for lined solid-waste landfills; Geosynthet. Int. 5(1–2) 203–235.CrossRefGoogle Scholar
  4. Chung C J F and Fabbri A G 1999 Probabilistic prediction models for landslide hazard mapping; Photogramm. Eng. Rem. Sens. 65(12) 1389–1399.Google Scholar
  5. 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.CrossRefGoogle Scholar
  6. Delgado J, Garrido J, López–Casado C, Martino S and Peláez J A 2011 On far field occurrence of seismically induced landslides; Eng. Geol. 123(3) 204–213.CrossRefGoogle Scholar
  7. Devkota K C, Regmi A D, Pourghasemi H R, Yoshida K, Pradhan B, Ryu I C, Dhital M R and Althuwaynee O F 2013 Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya; Nat. Hazards 65(1) 135—165.CrossRefGoogle Scholar
  8. Dewey J F and Burke K C 1973 Tibetan, Variscan and Precambrian basement reactivation: Products of continental collision; J. Geol. 81(6) 683–692.CrossRefGoogle Scholar
  9. Dou J, Bui D T, Yunus A P, Jia K, Song X, Revhaug I, Xia H and Zhu Z 2015 Optimization of causative factors for landslide susceptibility evaluation using remote sensing and GIS data in parts of Niigata, Japan; PLoS One 10:e0133262,  https://doi.org/10.1371/journal.pone.0133262.CrossRefGoogle Scholar
  10. Ercanoglu M, Gokceoglu C and Van Asch T W 2004 Landslide susceptibility zoning north of Yenice (NW Turkey) by multivariate statistical techniques; Nat. Hazards 32(1) 1–23.CrossRefGoogle Scholar
  11. George D and Mallery P 2000 SPSS for Windows: A simple guide and reference; Allyn & Bacon, Boston, MA.Google Scholar
  12. Gökceoglu C and Aksoy H 1996 Landslide susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques; Eng. Geol. 44(1–4) 147–161.CrossRefGoogle Scholar
  13. Hanley J A and McNeil B J 1982 The meaning and use of the area under a receiver operating characteristic (ROC) curve; Radiology 143(1) 29–36.CrossRefGoogle Scholar
  14. Harp E L, Jibson RW, Kayen R E, Keefer D K, Sherrod B L, Carver G A, Collins B D, Moss R E S and Sitar N 2003 Landslides and liquefaction triggered by the M 7.9 Denali fault earthquake of 3 November 2002; GSA Today 13(8) 4–10.CrossRefGoogle Scholar
  15. Hosmer D W and Lemeshow S 2000 Interpretation of the fitted logistic regression model. Appl. Logistic Regression; 2nd edn, pp. 47–90.Google Scholar
  16. Jade S and Sarkar S 1993 Statistical model for slope instability classifications; Eng. Geol. 36 71–98.CrossRefGoogle Scholar
  17. Jenks G 1967 The data model concept in statistical mapping; Int. Yearb. Cart. 7 347–356.Google Scholar
  18. Jibson R W, Harp E L and Michael J A 2000 A method for producing digital probabilistic seismic landslide hazard maps; Eng. Geol. 58(3) 271–289.CrossRefGoogle Scholar
  19. Kamp U, Growley B J, Khattak G A and Owen L A 2008 GIS-based landslide susceptibility mapping for the 2005 Kashmir earthquake region; Geomorphology 101(4) 631–642.CrossRefGoogle Scholar
  20. Kargel J S, Leonard J, Shugar D H, Haritashya U K, Bevington A, Fielding E J, Fujita K, Geertsema M, Miles E S, Steiner J and Anderson E 2016 Geomorphic and geologic controls of geohazards induced by Nepal’s 2015 Gorkha earthquake; Science 351(6269) 1–18, 17,  https://doi.org/10.1126/science.aac8353.
  21. Kavzoglu T, Sahin E K and Colkesen I 2014 Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression; Landslides 11(3) 425–439.CrossRefGoogle Scholar
  22. Keefer D K 1994 The importance of earthquake-induced landslides to long-term slope erosion and slope-failure hazards in seismically active regions; Geomorphology 10(1–4) 265–284.CrossRefGoogle Scholar
  23. Kritikos T, Robinson T R and Davies T R 2015 Regional coseismic landslide hazard assessment without historical landslide inventories: A new approach; J. Geophys. Res. Earth Surface 120(4) 711–729.CrossRefGoogle Scholar
  24. Lee C T, Huang C C, Lee J F, Pan K L, Lin M L and Dong J J 2008 Statistical approach to earthquake-induced landslide susceptibility; Eng. Geol. 100(1) 43–58.CrossRefGoogle Scholar
  25. Lee S and Evangelista D G 2006 Earthquake-induced landslide-susceptibility mapping using an artificial neural network; Nat. Hazard Earth Syst. 6(5) 687–695.CrossRefGoogle Scholar
  26. Leech N L, Barrett K C and Morgan G A 2005 SPSS for intermediate statistics: Use and interpretation; Psychology Press.Google Scholar
  27. Liao H W and Lee C T 2000 Landslides triggered by the Chi-Chi earthquake; In: Proceedings of the \(21{st}\) Asian Conference on Remote Sensing, Taipei, pp. 1–2.Google Scholar
  28. Magliulo P, Di L A, Russo F and Zelano A 2008 Geomorphology and landslide susceptibility assessment using GIS and bivariate statistics: A case study in southern Italy; Nat. Hazards 47(3) 411–435.CrossRefGoogle Scholar
  29. Mahalingam R, Olsen M J and O’Banion M S 2016 Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study); Geomat. Nat. Hazard Risk 7(6) 1884–1907.CrossRefGoogle Scholar
  30. Mertler C A and Reinhart R V 2016 Advanced and multivariate statistical methods: Practical application and interpretation; Routledge.Google Scholar
  31. Miles S B and Keefer D K 2000 Evaluation of seismic slope–performance models using a regional case study; Environ. Eng. Geosci. 6(1) 25–39.CrossRefGoogle Scholar
  32. Miles S B and Keefer D K 2007 Comprehensive areal model of earthquake-induced landslides: Technical specification and user guide; US Geol. Survey.Google Scholar
  33. Miles S B and Keefer D K 2009a Evaluation of CAMEL – comprehensive areal model of earthquake-induced landslides; Eng. Geol. 104(1) 1–15.CrossRefGoogle Scholar
  34. Miles S B and Keefer D K 2009b Toward a comprehensive areal model of earthquake-induced landslides; Nat. Hazards Rev. 10(1) 19–28.CrossRefGoogle Scholar
  35. Moore I D and Burch G J 1986 Physical basis of the length-slope factor in the universal soil loss equation; Soil Sci. Soc. Am J. 50(5) 1294–1298.CrossRefGoogle Scholar
  36. Moore I D, Grayson R B and Ladson A R 1991 Digital terrain modelling: A review of hydrological, geomorphological, and biological applications; Hydrol. Process. 5 (3–30).Google Scholar
  37. Newmark 1965 Effects of earthquakes on dams and embankments; Geotechnique 15(1965) 139–159.CrossRefGoogle Scholar
  38. O’brien R M 2007 A caution regarding rules of thumb for variance inflation factors; Quality & Quantity 41(5) 673–690.CrossRefGoogle Scholar
  39. Pradhan A M S and Kim Y T 2015 Application and comparison of shallow landslide susceptibility models in weathered granite soil under extreme rainfall events; Environ. Earth Sci. 73(9) 5761–5771.CrossRefGoogle Scholar
  40. Pradhan A M S, Kang H S, Lee S and Kim Y T 2016 Spatial model integration for shallow landslide susceptibility and its runout using a GIS-based approach in Yongin, Korea; Geocarto. Int. 32(4) 420–441.CrossRefGoogle Scholar
  41. Pradhan A M S and Kim Y T 2016 Evaluation of a combined spatial multi-criteria evaluation model and deterministic model for landslide susceptibility mapping; Catena 140 125–139.CrossRefGoogle Scholar
  42. Pradhan A M S, Kang H S Lee S and Kim Y T 2017 Spatial model integration for shallow landslide susceptibility and its runout using a GIS-based approach in Yongin, Korea; Geocarto Int. 32(4) 420–441.CrossRefGoogle Scholar
  43. Pradhan B and Lee S 2010 Landslide susceptibility assessment and factor effect analysis: Back propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling; Environ. Modell. Softw. 25 747–759.CrossRefGoogle Scholar
  44. Regmi A D, Dhital M R, Zhang J Q, Su L J and Chen X Q 2016 Landslide susceptibility assessment of the region affected by the 25 April 2015 Gorkha earthquake of Nepal; J. Mt. Sci. 13(11) 1941–1957.CrossRefGoogle Scholar
  45. Regmi N R, Giardino J R and Vitek J D 2010 Modeling susceptibility to landslides using the weight of evidence approach: Western Colorado, USA; Geomorphology 115 172–187.CrossRefGoogle Scholar
  46. Reneau S L and Dietrich W E 1987 Size and location of colluvial landslides in a steep forested landscape; IAHS–AISH Publ. 165 39–48.Google Scholar
  47. Saputra A, Gomez C, Hadmoko D S and Sartohadi J 2016 Coseismic landslide susceptibility assessment using geographic information system; Geoenviron. Disast. 3(1) 27.CrossRefGoogle Scholar
  48. Sarma S K 1975 Seismic stability of earth dams and embankments; Geotechnique 25(4) 743–761.CrossRefGoogle Scholar
  49. Seed H B, Lee K L, Idriss I M and Makdisi R 1973 Analysis of the slides in the San Fernando dams during the earthquake of Feb. 9, 1971; Earth Eng. Research Center, University of California, Berkeley; Report No. EERC 73–2, 150p.Google Scholar
  50. Sharma C K 1990 Geology of Nepal Himalaya and Adjacent Countries; Sangeeta Sharma, Kathmandu.Google Scholar
  51. Swets J A 1988 Measuring the accuracy of diagnostic systems; Science 240(4857) 1285.CrossRefGoogle Scholar
  52. Wang L J, Guo M, Sawada K, Lin J and Zhang J 2015 Landslide susceptibility mapping in Mizunami City, Japan: A comparison between logistic regression, bivariate statistical analysis and multivariate adaptive regression spline models; Catena 135 271–282.CrossRefGoogle Scholar
  53. Wasowski J, Keefer D K and Lee C T 2011 Towards the next generation of research on earthquake-induced landslides: current issues and future challenges; Eng. Geol. 122(1) 1–8.CrossRefGoogle Scholar
  54. Weng M C, Wu M H, Ning S K and Jou Y W 2011 Evaluating triggering and causative factors of landslides in Lawnon River Basin, Taiwan;, Taiwan; Eng. Geol. 123(1) 72–82.CrossRefGoogle Scholar
  55. Yegian M K, Marciano E A and Ghahraman V G 1991 Earthquake-induced permanent deformations: probabilistic approach; J. Geotech. Eng. 117(1) 35–50.CrossRefGoogle Scholar
  56. Zhou S, Chen G and Fang L 2016 Distribution pattern of landslides triggered by the 2014 Ludian earthquake of China: Implications for regional threshold topography and the seismogenic fault identification; ISPRS Int. J. Geo-Inf. 5(4) 46.CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2018

Authors and Affiliations

  1. 1.Department of Earth and Environmental SciencesPukyong National UniversityBusanRepublic of Korea

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