Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: A case study in Mizunami City, Japan

Journal of Applied Remote Sensing

Volumn 7, Issue 1, 2013, Pages

  Wang, Liang Jie ^a   Sawada, Kazuhide ^a   Moriguchi, Shuji ^a  

^a GIFU UNIVERSITY   (Japan)

Author keywords

digital elevation model; landslide susceptibility analysis; logistic regression model

Indexed keywords

DIGITAL INSTRUMENTS; FORESTRY; GEOMORPHOLOGY; LANDSLIDES; OPTICAL RADAR; REGRESSION ANALYSIS;

CLASSIFICATION ACCURACY; DIGITAL ELEVATION MODEL; DISTRIBUTION CHARACTERISTICS; LANDSLIDE SUSCEPTIBILITY; LIGHT DETECTION AND RANGING; LOGISTIC REGRESSION MODELING; LOGISTIC REGRESSION MODELS; LOGISTIC REGRESSIONS;

SURVEYING;

EID: 84905472411     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.7.073561     Document Type: Article

References (30)

1. B. Pradhan and S. Lee, "Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models," Environ. Earth Sci. 60(5), 1037-1054 (2010), http://dx.doi.org/10.1007/s12665-009-0245-8.
2. B. Pradhan and S. Lee, "Landslide susceptibility assessment and factor effect analysis: back-propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling," Environ. Model. Softw. 25(6), 747-759 (2010), http://dx.doi.org/10.1016/j.envsoft.2009.10.016.
3. N. R. Regmi, J. R. Giardino, and J. D. Vitek, "Assessing susceptibility to landslide: using models to understand observed changes in slopes," Geomorphology 122(1-2), 25-38 (2010), http://dx.doi.org/10.1016/j. geomorph.2010.05.009.
4. N. R. Regmi, J. R. Giardino, and J. D. Vitek, "Modeling susceptibility to landslides using the weight of evidence approach: western Colorado, USA," Geomorphology 115(1-2), 172-187 (2010), http://dx.doi.org/10.1016/j.geomorph.2009.10.002.
5. S. Lee, "Comparison of landslide susceptibility maps generated through multiple logistic regression for three test areas in Korea," Earth Surf. Process. Land. 32(14), 2133-2148 (2007), http://dx.doi.org/10.1002/(ISSN) 1096-9837.
6. M. C. Tunusluoglu et al., "Extraction of potential debris source areas by logistic regression technique: a case study from Barla, Besparmak and Kapi mountains (NW Taurids, Turkey)," Environ. Geol. 54(1), 9-22 (2008), http://dx.doi.org/10.1007/s00254-007-0788-5.
7. S. B. Bai et al., "GIS-based logistic regression for landslide susceptibility mapping of the Zhongxian segment in the Three Gorges area, China," Geomorphology 115(1-2), 23-31 (2010), http://dx.doi.org/10.1016/j. geomorph.2009.09.025.
8. I. Das et al., "Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India)," Geomorphology 114(4), 627-637 (2010), http://dx.doi.org/10.1016/j.geomorph .2009.09.023.
9. A. Nandi and A. Shakoor, "A GIS-based landslide susceptibility evaluation using bivariate and multivariate statistical analyses," Eng. Geol. 110(1-2), 11-20 (2010), http://dx.doi.org/10.1016/j.enggeo.2009.10.001.
10. H. J. Oh and S. Lee, "Cross-validation of logistic regression model for landslide susceptibility mapping at Ganeoung areas, Korea," Disaster Adv. 3(2), 44-55 (2010).
11. M. Ercanoglu and C. Gokceoglu, "Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach," Environ. Geol. 41(6), 720-730 (2002), http://dx.doi.org/10.1007/ s00254-001-0454-2.
12. S. Lee, "Application and verification of fuzzy algebraic operators to landslide susceptibility mapping," Environ. Geol. 52(4), 615-623 (2007), http://dx.doi.org/10.1007/s00254-006-0491-y.
13. D. P. Kanungo et al., "Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas," Landslides 5(4), 407-416 (2008), http://dx.doi.org/10 .1007/s10346-008-0134-3.
14. K. Muthu et al., "Landslide possibility mapping using fuzzy approaches," IEEE Trans. Geosci. Rem. Sens. 46(4), 1253-1265 (2008), http://dx.doi.org/10.1109/TGRS.2007 .912441.
15. B. Pradhan et al., "Landslide susceptibility mapping by neuro-fuzzy approach in a landslide prone area (Cameron Highland Malaysia)," IEEE Trans. Geosci. Rem. Sens. 48(12), 4164-4177 (2010), http://dx.doi.org/10.1109/ TGRS.2010.2050328.
16. C. Melchiorre et al., "Artificial neural net-works and cluster analysis in landslide susceptibility zonation," Geomorphology 94(3-4), 379-400 (2008), http://dx.doi.org/10.1016/j .geomorph.2006.10.035.
17. C. H. Chen, C. C. Ke, and C. L. Wang, "A back-propagation network for the assessment of susceptibility to rock slope failure in the eastern portion of the Southern Cross-Island Highway in Taiwan," Environ. Geol. 57(4), 723-733 (2009), http://dx.doi.org/10.1007/s00254-008-1350-9.
18. C. P. Poudyal et al., "Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya," Environ. Earth Sci. 61(5), 1049-1064 (2010), http://dx.doi.org/10.1007/s12665-009-0426-5.
19. I. Yilmaz, "Comparison of landslide susceptibility mapping methodologies for Koyulhisar, Turkey: conditional probability, logistic regression, artificial neural networks, and support vector machine," Environ. Earth Sci. 61(4), 821-836 (2010), http://dx.doi.org/10.1007/s12665-009- 0394-9.
20. M. H. Vahidnia et al., "A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping," Comput. Geosci. 36(9), 1101-1114 (2010), http://dx.doi.org/10.1016/j.cageo.2010. 04.004.
21. X. Yao, L. G Tham, and F. C. Dai, "Landslide susceptibility mapping based on support vector machine: a case study on natural slopes of Hong Kong, China," Geomorphology 101(4), 572-582 (2008), http://dx.doi.org/10.1016/j. geomorph.2008.02.011.
22. H. Saito, D. Nakayama, and H. Matsuyama, "Comparison of landslide susceptibility based on a decision tree model and actual landslide occurrence: The Akaishi Mountains, Japan," Geomorphology 109(3-4), 108-121 (2009), http://dx.doi.org/10.1016/j.geomorph.2009.02.026.
23. Y.-K. Yeon et al., "Landslide susceptibility mapping in Injae, Korea, using a decision tree," Eng. Geol. 116(3-4), 274-283 (2010), http://dx.doi.org/10.1016/j.enggeo.2010.09 .009.
24. M. L. Süzen and V. Doyuran, "Data driven bivariate landslide susceptibility assessment using Geographical Information Systems: a method and application to Asarsuyu catchment, Turkey," Eng. Geol. 71(3-4), 303-321 (2004), http://dx.doi.org/10.1016/S0013-7952(03)00143-1.
25. E. M. Blyth et al., "Can soil moisture be mapped onto the terrain?," Hydrol. Earth Syst. Sci. 8(5), 923-930 (2004), http://dx.doi.org/10.5194/hess-8-923-2004.
26. I. D. Moore, R. B. Grayson, and A. R. Ladson, "Digital terrain modelling: a review of hydrological, geomorphological, and biological applications," Hydrol. Process 5(1), 3-30 (1991), http://dx.doi.org/10. 1002/(ISSN)1099-1085.
27. S. K. Mittal et al., "Design and development of instrumentation network for landslide monitoring, and issue an early warning," J. Sci. Ind. Res. 67(5), 361-365 (2008).
28. D. J. Varnes, "Slope movements: types and processes," in Landslide Analysis and Control, Transportation Research Board Special Report 176, R. L. Schuster and R. J. Krizek, Eds., pp. 11-33, National Academy of Sciences, Washington (1978).
29. E. Yesilnacar and T. Topal, "Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey)," Eng. Geol. 79(3-4), 251-266 (2005), http://dx.doi.org/10.1016/j.enggeo.2005 .02.002.
30. T. Fawcett, "An introduction to ROC analysis," Pattern Recogn. Lett. 27(8), 861-874 (2006), http://dx.doi.org/10.1016/j.patrec.2005.10.010.