Landslide vulnerability assessment and zonation through ranking of causative parameters based on landslide density-derived statistical indicators

Geocarto International

Volumn 26, Issue 6, 2011, Pages 491-504

  Sharma, L P ^a   Patel, Nilanchal ^b   Ghose, M K ^c   Debnath, P ^d  

^a Geo Informatics Tashiling Secretariat   (India)

^b BIRLA INSTITUTE OF TECHNOLOGY   (India)

^c SIKKIM MANIPAL INSTITUTE OF TECHNOLOGY   (India)

^d Tree Improvement and Germplasm Resources Department   (India)

Author keywords

GIS; Landslide susceptibility index; Landslides; Parameters; Vulnerability; Zonation

Indexed keywords

ACCURACY ASSESSMENT; ASSESSMENT METHOD; EFFICIENCY MEASUREMENT; GIS; LANDSLIDE; PARAMETERIZATION; PREDICTION; RANKING; SPATIAL ANALYSIS; SPATIAL VARIATION; ZONATION;

TOBACCO RATTLE VIRUS;

EID: 80052421053     PISSN: 10106049     EISSN: None     Source Type: Journal    
DOI: 10.1080/10106049.2011.598951     Document Type: Article

References (26)

1. Atkinson, P.M. and Massari, R., 1998. Generalized linear modeling of susceptibility to landsliding in the central Apennines, Italy. Computers and Geoscience, 24, 373-385.
2. Bianca, C.V. and Nelson, F.F., 2004. Landslide in Rio de Ianeiro: the role played by variations in soil hydraulic conductivity. Hydrological Process, 18 (4), 791-805.
3. Dhakal, A.S. and Sidle, R.C., 2002. Physically based landslide hazard model 'U' method and issues. In: EGS XXVII general assembly, Nice, France, April 21-26, 2002, 21-26.
4. Ercanoglu, M. and Gokceoglu, C., 2004. Use of fuzzy relations to produce landslide susceptibility slope failure risk maps of the Altindag (settlement) region in Turkey.Engineering Geology, 55, 277-296.
5. Gupta, M., Ghose, M.K., and Sharma, L.P., 2009. Application of remote sensing and GIS for landslides hazard and assessment of their probabilistic occurrence - a case study of NH31A between Rangpo and Singtam. Journal of Geomatics, 3 (1), 13-7.
6. Lee, S., 2005. Application of logistic regression model and its validation for landslide susceptibility mapping using GIS and remote sensing data. International Journal of Remote Sensing, 26, 1477-1491.
7. Lee, S., 2007. Application and verification of fuzzy algebraic operators to landslide susceptibility mapping. Environmental Geology, 52, 615-623.
8. Lee, S. and Sambth, T., 2006. Landslide susceptibility mapping in the Damrei Romel area,Cambodia using frequency ratio and logistic regression. Environmental Geology, 50,847-855.
9. Lee, S., et al., 2003a. Landslide susceptibility analysis using GIS and artificial neural network.Earth Surface Process Landforms, 28, 361-1376.
10. Lee, S., et al., 2003b. Landslide susceptibility analysis using artificial neural network at Bonn,Korea. Environmental Geology, 44, 820-833.
11. Lee, S., et al., 2004. Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Engineering Geology, 71, 289-302.
12. Pachauri, A.K. and Pant, M., 1992. Landslide hazard mapping based on geological attributes.Engineering Geology, 32, 81-100.
13. Pachauri, A.K., Gupta, P.V., and Chander, R., 1998. Landslide zoning in a part of the Garhwal Himalayas. Environmental Geology, 36 (3-4), 325-334.
14. Patanakanog, B., 2001. Landslide hazard potential area in 3 dimension by remote sensing and GIS technique [online]. Thailand: Land Development Department. Available from:http://www.ecy.wa.gov/programs/sea/landslides/help/drainage.html [Accessed 13 January 2010].
15. Pistocchi, A., Luzi, L., and Napolitano, P., 2002. The use of predictive modeling techniques for optimal exploitation of spatial databases: a case study in landslide hazard mapping with expert system-like methods. Environmental Geology, 58, 251-70.
16. Ramakrishna, D., et al., 2005. Probabilistic techniques, GIS and remote sensing in landslide hazard mitigation: a case study from Sikkim Himalayas, India. Geocarto International, 20(4), 53-58.
17. Roth, R.A., 1983. Factors affecting landslide susceptibility in San Mateo County, California.Bulletin of the Association of Engineering Geologists, 20 (4), 353-372.
18. Sakellariou, M.G. and Ferentinou, M.D., 2001. GIS-based estimation of slope stability.Natural Hazards Review, 2 (1), 12-21.
19. Samra, J.S. and Sharma, U.C., 2002. Soil erosion and conservation. In: G.S. Sekhon, ed. Fundamental of soil science. New Delhi, India: Indian Society of Soil Science, IARI, 162.
20. Sharma, L.P., et al., 2010a. Influence of Shannon's entropy on landslide-causing parameters for vulnerability study and zonation - a case study in Sikkim, India. Arabian Journal of Geosciences. doi 10.1007/s12517-010-0205-3.
21. Sharma, L.P., et al., 2010b. Assessing landslide vulnerability from soil characteristics - a GIS based analysis. Arabian Journal of Geosciences. doi 10.1007/s12517-010-0272-5.
22. Shu-Quing, W. and Unwin, D.J., 1992. Modelling landslide distribution on loess soils in China: an investigation. International Journal of Geographical Information Systems, 6 (5),391-405.
23. Sivakumar, G.L. and Mukesh, M.D., 2002. Landslide analysis in geographic information systems [online]. Bangalore, India: Department of Civil Engineering, Indian Institute of science. Available from: http://www.gisdevelopment.net/application/natural_hazards/landslides/nhls0011pf.htm [Accessed 26 February 2011].
24. Uromeihy, A. and Mahdavifar, M.R., 2000. Landslide hazard zonation of Khorshrostam area, Iran. Bulletin of Engineering Geology and the Environment, 58, 207-213.
25. Varnes, D.J., 1984. Landslide hazard zonation: a review of principles and practice. Paris:UNESCO, 1-55.
26. Wadge, G., 1988. The potential of GIS modeling of gravity flows and slope instabilities [online]. International Journal of Geographical Information Systems, 2, 143-152. Available from: http://en.wikipedia.org/wiki/Coefficient_of_variation [Accessed on 13th March 2011]