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A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology

Year 2015, Volume: 5 Issue: 2, 7 - 16, 23.07.2016

Abstract

This work presents Analytical Hierarchy Process (AHP) method available in Geographic Information System (GIS) to identify and classify the Penang Island according to the grade of present or potential danger of land failure happening. Landslide susceptibility zonation map has been generated by considering seven factors. Sensitivity analysis was performed in detail by varying the contributing factors weights and their effects on defined landslide susceptible locations. In other part of the analysis, ordinary least square (OLS) technique has been used to estimate weights of point parameters then its result compared with AHP technique result. Finally, the landslide susceptibility maps resulted from AHP and OLS method has been compared to the landslide inventory map containing 355 real occurred landslides in order to verify the practicality of susceptibility maps. The outcome was that the 75% of occurred land failures fit into the very high and high susceptibility class of AHP map (using seven parameters), while this is 73.8% in the case of AHP with point parameters (using four parameters), and 65.8% for the OLS map. As conclusion, the AHP method yields reasonable results which make it reliable and credible approach in comparison with OLS, especially in the case of using large number of landslide contributing factors

References

  • Abdullahi, S., Rodzi, A., & Pradhan, B. (2013). Spatial modelling of site suitability assessment for hospitals using geographical information system-based multicriteria approach at Qazvin city, Iran. Geocarto International, (February 2013), 1–21. doi:10.1080/10106049.2012.752531
  • Althuwaynee, O. F., Pradhan, B., & Lee, S. (2012). Application of an evidential belief function model in landslide susceptibility mapping. Computers & Geosciences, 44, 120–135. doi:10.1016/j.cageo.2012.03.003
  • Ayalew, L., & Yamagishi, H. (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65(1-2), 15–31. doi:10.1016/j.geomorph.2004.06.010
  • Ayalew, L., Yamagishi, H., Marui, H., & Kanno, T. (2005). Landslides in Sado Island of Japan: Part II. GISbased susceptibility mapping with comparisons of results from two methods and verifications. Engineering Geology, 81(4), 432–445. doi:10.1016/j.enggeo.2005.08.004
  • Ayalew, L., Yamagishi, H., & Ugawa, N. (2004). Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides, 1(1), 73–81. doi:10.1007/s10346-003-0006-9
  • Pachari, AK., Gupta, PV., Chander, R. (1998). Landslide zoning in a part of the, 36(January), 325–334. Chen, Y., Yu, J., Shahbaz, K., & Xevi, E. (2009). A GIS-based sensitivity analysis of multi-criteria weights. 18th World IMACS/MODISM …, (July), 3137–3143. Retrieved from http://metronu.ulb.ac.be/imacs/cairns/I2/chen_y.pdf
  • Cevik, E., & Topal, T. (2003). GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environmental Geology, 44(8), 949–962. doi:10.1007/s00254-003- 0838-6
  • Dia, F.C., Lee, C.F., Li, J., Xu, Z.W. (2001). Assessment of landslide susceptibility on the natural terrain of Lantau Island , Hong Kong, 40(January), 381–391.
  • Lee, S., & Pradhan, B. (2006). Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. Journal of Earth System Science, 115(6), 661–672. doi:10.1007/s12040-006-0004-0
  • 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(7), 1477-1479. Doi:10.1080/01431160412331331012
  • Mancini, F., Ceppi, C., & Ritrovato, G. (2010). GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy. Natural Hazards and Earth System Science, 10(9), 1851–1864. doi:10.5194/nhess-10-1851-2010
  • Matori, A. N., Basith, A., & Harahap, I. S. H. (2011). Study of regional monsoonal effects on landslide hazard zonation in Cameron Highlands, Malaysia. Arabian Journal of Geosciences, 5(5), 1069–1084. doi:10.1007/s12517-011-0309-4
  • Oh, H.-J., & Pradhan, B. (2011). Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Computers & Geosciences, 37(9), 1264–1276. doi:10.1016/j.cageo.2010.10.012
  • Pourghasemi, H. R., Pradhan, B., & Gokceoglu, C. (2012). Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural Hazards, 63(2), 965– 996. doi:10.1007/s11069-012-0217-2
  • Pradhan, B., Lee, S., & Buchroithner, M. F. (2010). A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Computers, Environment and Urban Systems, 34(3), 216–235. doi:10.1016/j.compenvurbsys.2009.12.004
  • Pradhan, B., & Youssef, A. M. (2009). Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arabian Journal of Geosciences, 3(3), 319–326. doi:10.1007/s12517-009-0089-2
  • Satty, T.L. (1980). The Analytical Hierarchy Process 1st edn. McGraw Hill, New York, USA.
  • Saaty, T. L. (1999). Fundamentals of the analytic network process. In: Proceedings International Symposium on Analytical Hierarchy Process. Kobe, Japan, pp. 1–14.
  • Tangestani, M. H. (2009). A comparative study of Dempster–Shafer and fuzzy models for landslide susceptibility mapping using a GIS: An experience from Zagros Mountains, SW Iran. Journal of Asian Earth Sciences, 35(1), 66–73. doi:10.1016/j.jseaes.2009.01.002
  • Thanh, L. N., & De Smedt, F. (2011). Application of an analytical hierarchical process approach for landslide susceptibility mapping in A Luoi district, Thua Thien Hue Province, Vietnam. Environmental Earth Sciences, 66(7), 1739–1752. doi:10.1007/s12665-011-1397-x
  • Tien Bui, D., Pradhan, B., Lofman, O., Revhaug, I., & Dick, O. B. (2012). Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS. Computers & Geosciences, 45, 199–211. doi:10.1016/j.cageo.2011.10.031
  • Vahidnia, M. H., Alesheikh, A. a., Alimohammadi, A., & Hosseinali, F. (2010). A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping. Computers & Geosciences, 36(9), 1101–1114. doi:10.1016/j.cageo.2010.04.004
  • Yalcin, a., Reis, S., Aydinoglu, a. C., & 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. doi:10.1016/j.catena.2011.01.014
  • Yalcin, A. (2008). GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena, 72(1), 1–12. doi:10.1016/j.catena.2007.01.003
  • Yilmaz, I. (2009). The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability and artificial neural networks. Environmental Earth Sciences, 60(3), 505–519. doi:10.1007/s12665-009-0191-5
  • Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.
Year 2015, Volume: 5 Issue: 2, 7 - 16, 23.07.2016

Abstract

References

  • Abdullahi, S., Rodzi, A., & Pradhan, B. (2013). Spatial modelling of site suitability assessment for hospitals using geographical information system-based multicriteria approach at Qazvin city, Iran. Geocarto International, (February 2013), 1–21. doi:10.1080/10106049.2012.752531
  • Althuwaynee, O. F., Pradhan, B., & Lee, S. (2012). Application of an evidential belief function model in landslide susceptibility mapping. Computers & Geosciences, 44, 120–135. doi:10.1016/j.cageo.2012.03.003
  • Ayalew, L., & Yamagishi, H. (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65(1-2), 15–31. doi:10.1016/j.geomorph.2004.06.010
  • Ayalew, L., Yamagishi, H., Marui, H., & Kanno, T. (2005). Landslides in Sado Island of Japan: Part II. GISbased susceptibility mapping with comparisons of results from two methods and verifications. Engineering Geology, 81(4), 432–445. doi:10.1016/j.enggeo.2005.08.004
  • Ayalew, L., Yamagishi, H., & Ugawa, N. (2004). Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area of Agano River, Niigata Prefecture, Japan. Landslides, 1(1), 73–81. doi:10.1007/s10346-003-0006-9
  • Pachari, AK., Gupta, PV., Chander, R. (1998). Landslide zoning in a part of the, 36(January), 325–334. Chen, Y., Yu, J., Shahbaz, K., & Xevi, E. (2009). A GIS-based sensitivity analysis of multi-criteria weights. 18th World IMACS/MODISM …, (July), 3137–3143. Retrieved from http://metronu.ulb.ac.be/imacs/cairns/I2/chen_y.pdf
  • Cevik, E., & Topal, T. (2003). GIS-based landslide susceptibility mapping for a problematic segment of the natural gas pipeline, Hendek (Turkey). Environmental Geology, 44(8), 949–962. doi:10.1007/s00254-003- 0838-6
  • Dia, F.C., Lee, C.F., Li, J., Xu, Z.W. (2001). Assessment of landslide susceptibility on the natural terrain of Lantau Island , Hong Kong, 40(January), 381–391.
  • Lee, S., & Pradhan, B. (2006). Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia. Journal of Earth System Science, 115(6), 661–672. doi:10.1007/s12040-006-0004-0
  • 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(7), 1477-1479. Doi:10.1080/01431160412331331012
  • Mancini, F., Ceppi, C., & Ritrovato, G. (2010). GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy. Natural Hazards and Earth System Science, 10(9), 1851–1864. doi:10.5194/nhess-10-1851-2010
  • Matori, A. N., Basith, A., & Harahap, I. S. H. (2011). Study of regional monsoonal effects on landslide hazard zonation in Cameron Highlands, Malaysia. Arabian Journal of Geosciences, 5(5), 1069–1084. doi:10.1007/s12517-011-0309-4
  • Oh, H.-J., & Pradhan, B. (2011). Application of a neuro-fuzzy model to landslide-susceptibility mapping for shallow landslides in a tropical hilly area. Computers & Geosciences, 37(9), 1264–1276. doi:10.1016/j.cageo.2010.10.012
  • Pourghasemi, H. R., Pradhan, B., & Gokceoglu, C. (2012). Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran. Natural Hazards, 63(2), 965– 996. doi:10.1007/s11069-012-0217-2
  • Pradhan, B., Lee, S., & Buchroithner, M. F. (2010). A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Computers, Environment and Urban Systems, 34(3), 216–235. doi:10.1016/j.compenvurbsys.2009.12.004
  • Pradhan, B., & Youssef, A. M. (2009). Manifestation of remote sensing data and GIS on landslide hazard analysis using spatial-based statistical models. Arabian Journal of Geosciences, 3(3), 319–326. doi:10.1007/s12517-009-0089-2
  • Satty, T.L. (1980). The Analytical Hierarchy Process 1st edn. McGraw Hill, New York, USA.
  • Saaty, T. L. (1999). Fundamentals of the analytic network process. In: Proceedings International Symposium on Analytical Hierarchy Process. Kobe, Japan, pp. 1–14.
  • Tangestani, M. H. (2009). A comparative study of Dempster–Shafer and fuzzy models for landslide susceptibility mapping using a GIS: An experience from Zagros Mountains, SW Iran. Journal of Asian Earth Sciences, 35(1), 66–73. doi:10.1016/j.jseaes.2009.01.002
  • Thanh, L. N., & De Smedt, F. (2011). Application of an analytical hierarchical process approach for landslide susceptibility mapping in A Luoi district, Thua Thien Hue Province, Vietnam. Environmental Earth Sciences, 66(7), 1739–1752. doi:10.1007/s12665-011-1397-x
  • Tien Bui, D., Pradhan, B., Lofman, O., Revhaug, I., & Dick, O. B. (2012). Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS. Computers & Geosciences, 45, 199–211. doi:10.1016/j.cageo.2011.10.031
  • Vahidnia, M. H., Alesheikh, A. a., Alimohammadi, A., & Hosseinali, F. (2010). A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping. Computers & Geosciences, 36(9), 1101–1114. doi:10.1016/j.cageo.2010.04.004
  • Yalcin, a., Reis, S., Aydinoglu, a. C., & 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. doi:10.1016/j.catena.2011.01.014
  • Yalcin, A. (2008). GIS-based landslide susceptibility mapping using analytical hierarchy process and bivariate statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena, 72(1), 1–12. doi:10.1016/j.catena.2007.01.003
  • Yilmaz, I. (2009). The effect of the sampling strategies on the landslide susceptibility mapping by conditional probability and artificial neural networks. Environmental Earth Sciences, 60(3), 505–519. doi:10.1007/s12665-009-0191-5
  • Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353.
There are 26 citations in total.

Details

Other ID JA56EE54PR
Journal Section Articles
Authors

Sara Khodadad This is me

Dong-Ho Jang This is me

Publication Date July 23, 2016
Published in Issue Year 2015 Volume: 5 Issue: 2

Cite

APA Khodadad, S., & Jang, D.-H. (2016). A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. TOJSAT, 5(2), 7-16.
AMA Khodadad S, Jang DH. A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. TOJSAT. July 2016;5(2):7-16.
Chicago Khodadad, Sara, and Dong-Ho Jang. “A Comparative Study of Analytical Hierarchy Process and Ordinary Least Square Methods for Landslide Susceptibility Mapping Using GIS Technology”. TOJSAT 5, no. 2 (July 2016): 7-16.
EndNote Khodadad S, Jang D-H (July 1, 2016) A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. TOJSAT 5 2 7–16.
IEEE S. Khodadad and D.-H. Jang, “A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology”, TOJSAT, vol. 5, no. 2, pp. 7–16, 2016.
ISNAD Khodadad, Sara - Jang, Dong-Ho. “A Comparative Study of Analytical Hierarchy Process and Ordinary Least Square Methods for Landslide Susceptibility Mapping Using GIS Technology”. TOJSAT 5/2 (July 2016), 7-16.
JAMA Khodadad S, Jang D-H. A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. TOJSAT. 2016;5:7–16.
MLA Khodadad, Sara and Dong-Ho Jang. “A Comparative Study of Analytical Hierarchy Process and Ordinary Least Square Methods for Landslide Susceptibility Mapping Using GIS Technology”. TOJSAT, vol. 5, no. 2, 2016, pp. 7-16.
Vancouver Khodadad S, Jang D-H. A comparative study of Analytical Hierarchy Process and Ordinary Least Square methods for landslide susceptibility mapping using GIS technology. TOJSAT. 2016;5(2):7-16.