Volume 17, Issue 45 (8-2017)
jgs 2017, 17(45): 7-24 |
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پهنهبندی خطر زمینلغزش با استفاده از روش آماری رگرسیون لجستیک در حوضه آبریز لواسانات. jgs 2017; 17 (45) :7-24
URL: http://jgs.khu.ac.ir/article-1-2797-en.html
URL: http://jgs.khu.ac.ir/article-1-2797-en.html
Abstract: (5979 Views)
18 - Ayalew. L. Yamagishi. H. Marui. H & Kanno. T. (2005). "Landslides in Sado Island of Japan: Part II. GIS-based susceptibility mapping with comparisons of results from two methods and verifications.", Engineering Geology 81. (2005). 432– 445.
19 - Ayalew,l. and Yamagishi, H. (2005):The application of GIS –based logistic regression for landslide susceptibility mapping in the Kakuda-Yaahiko Mountanins, central Japan, Geomorphology 65,15-31.
20 - Atkinson, P., Massari, R (2011). Logistic modeling susceptibility to land sliding in the Apennines, Italy Geomorphology.Vol.130.
21- Cornforth, D., H., 2005, "Landslides in practice: investigation, analysis, and remedial/preventative options in soils", Wiley, 1ed, 624 pp.
22 -Chen, Zhaohua. Wang, Jinfei (2007). Landslide hazard mapping using logistic regressionmodel in Mackenzie Valley, Canada. Geomorphology, Vol.42.
23 - Dai, F. C.& Lee, c. f. (2002): Landslide characteristics and slop instability modeling using GIS.Lantau,Hong Kong Gemorphology 42, 213-228.
24 - Das, I., Sahoo. S, Westen, A. Stein, A. Hack, A. (2010). Lanslidesusceptibility assessment using logistic regression and its comparison with a rock mass classification system, along road section in the northern Himalayas (India). Geomorphology, Vol.1147.
25 - Gregory C.Ohlmacher, John C. Davis (2003). Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Geomorphology,Vol 69.
26 - Hosseinzadeh, M., Servati, M. R., and Mansouri, A. 2009. Zonation of Mass Movements Occurring Risk using Logistic Regression Model. IRAN Geology Quarterly, 3 (11): 27-37. (in Per.)
27 - Lee, S. 2007. Application and Verification of Fuzzy Algebraic Operators to Landslide Susceptibility Mapping. Environment Geology, 52: 615-623. (In Eng.)
28 -Menard. S. (1995) Applied logistic regression analysis. Sage university Paper Series on Quantitative Applications in Social Sciences, vol. 106. Thousand Oaks. California. 98 pp.
29- Parthian, B., Lee, S. (2010). Landslide susceptibility assessment and factor effect analysis: bad propagation artificial neural networks and comparison with frequency ratio and bivariate logistic regression modeling. Geomorphology, Vol. 25.
19 - Ayalew,l. and Yamagishi, H. (2005):The application of GIS –based logistic regression for landslide susceptibility mapping in the Kakuda-Yaahiko Mountanins, central Japan, Geomorphology 65,15-31.
20 - Atkinson, P., Massari, R (2011). Logistic modeling susceptibility to land sliding in the Apennines, Italy Geomorphology.Vol.130.
21- Cornforth, D., H., 2005, "Landslides in practice: investigation, analysis, and remedial/preventative options in soils", Wiley, 1ed, 624 pp.
22 -Chen, Zhaohua. Wang, Jinfei (2007). Landslide hazard mapping using logistic regressionmodel in Mackenzie Valley, Canada. Geomorphology, Vol.42.
23 - Dai, F. C.& Lee, c. f. (2002): Landslide characteristics and slop instability modeling using GIS.Lantau,Hong Kong Gemorphology 42, 213-228.
24 - Das, I., Sahoo. S, Westen, A. Stein, A. Hack, A. (2010). Lanslidesusceptibility assessment using logistic regression and its comparison with a rock mass classification system, along road section in the northern Himalayas (India). Geomorphology, Vol.1147.
25 - Gregory C.Ohlmacher, John C. Davis (2003). Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA. Geomorphology,Vol 69.
26 - Hosseinzadeh, M., Servati, M. R., and Mansouri, A. 2009. Zonation of Mass Movements Occurring Risk using Logistic Regression Model. IRAN Geology Quarterly, 3 (11): 27-37. (in Per.)
27 - Lee, S. 2007. Application and Verification of Fuzzy Algebraic Operators to Landslide Susceptibility Mapping. Environment Geology, 52: 615-623. (In Eng.)
28 -Menard. S. (1995) Applied logistic regression analysis. Sage university Paper Series on Quantitative Applications in Social Sciences, vol. 106. Thousand Oaks. California. 98 pp.
29- Parthian, B., Lee, S. (2010). Landslide susceptibility assessment and factor effect analysis: bad propagation artificial neural networks and comparison with frequency ratio and bivariate logistic regression modeling. Geomorphology, Vol. 25.
Type of Study: Research |
Subject:
Geomorphology
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