PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Powiadomienia systemowe
  • Sesja wygasła!
  • Sesja wygasła!
  • Sesja wygasła!
Tytuł artykułu

An heuristic approach for mapping landslide hazard by integrating fuzzy logic with analytic hierarchy process

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study presents an integration of fuzzy sets theory with analytic hierarchy process (AHP) to model landslide hazard. The approach involves developing expert knowledge from existing landslide datascts which arc used for standardizing digital terrain attributes, a pairwise comparison method for the elicitation of attribute weights, and their subsequent aggregation through weighted linear combination (WLC) and ordered weighted average fOWA) function to generate landslide hazard maps. The approach enhances tlic methodology for modeling landslide hazard in roaded and roadless areas through the derivation of probabilistic maps. The maps can be used as a decision support tool in forest management and planning. A case study from the Clearwater National Forest in central Idaho, USA, illustrates the application of the approach in a practical setting.
Rocznik
Strony
121--146
Opis fizyczny
Bibliogr. 44 poz., rys., wykr.
Twórcy
autor
  • Department of Forest Resources, College of Natural Resources, University of Idaho Moscow, ID 83843, USA, peceg@uidaho.edu
Bibliografia
  • AYALEW, L., YAMAGISHI, H. and UGAWA, N. (2004) Landslide susceptibility mapping using GIS-based weighted linear combination, the case in Tsugawa area ofAgano River, Niigata Prefecture, Japan. Landslides 1, 73-81.
  • BARZILAI, J. (1998) On the decomposition of value functions. Operations Research Letters 22, 159-170.
  • BEZDEK, J.C. and SANKAR P.K. (1992) Fuzzy Models For Pattern Recognition: Methods That Search for Structures in Data. IEEE Press, New York.
  • BURROUGH, P.A. (1989) Fuzzy mathematical methods for soil survey and land evaluation. Journal of Soil Science 40, 477-492.
  • BURROUGH, P.A. and FRANK, P.A. (1995) Concepts and paradigms in spatial information: are current, geographical information systems truly generic? International Journal of Geographical Information Systems 2, 101-116.
  • BURROUGH, P.A. and MC'DONNELL, R.A. (1998) Principles of Geographic Information Systems. Oxford University Press.
  • BURROUGH, P.A., VAN GAANS, P.F.M. and MACMILLAN, R.A. (2000) High-resolution landform classification using fuzzy k-means. Fuzzy Sets and Systems 113, 37-52.
  • BURROUGH, P.A., WILSON, J.P., VAN GAANS, P.F.M. and HANSEN, A.J. (2001) Fuzzy k-means classification of topo-climatic data as an aid to forest mapping in the Greater Yellowstone Area, USA. Landscape Ecology 16, 523-546.
  • CARRARA, A. (1983) Multivariate Models for Landslide Hazard Evaluation. Mathematical Geology 15, 403-426.
  • CARRARA, A.; CARDINALI, M., DETTI, R., GUZZETTI, F., PASQUI V. and REICHENBACH P. (1991) GIS Techniques and statistical models in evaluating landslide hazard. Earth Surface Processes and Landfonns 16, 427-445.
  • CHEN, S.J. and HWANG; C.L. (1992) Fuzzy multiple attribute decision making. Springer-Verlag, Berlin.
  • CHUNG, C.F., FABBRI, A.G. and VAN WESTEN, C.J. (1995) Multivariate regression analysis for landslide hazard zonation, In: A. Carrara, F. Guzzetti, eds., Geographical Information Systems in Assessing Natural Hazards, Kluwer Academic Publishers, Dordrecht, 107-133.
  • CHUNG, C.F. and FABBRI, A.G. (1999) Probabilistic prediction model for landslide hazard mapping. Photogrammetric Engineering and Remote Sensing 65, 1389-1399.
  • DAI, F.C. and LEE, C.F. (2002) Landslide characteristics and slope instability modeling using GIS, Lantau Island, Hong Kong. Gepmorphology 42, 213-238.
  • DHAKAL. A.S., AMADA, T., and ANTYA, M. (2000) Landslide hazard mapping and its evaluation using GIS: An Investigation of Sampling Schemes for a Grid-Cell Based Quantitative Method. Photogrammetric Engineering and Remote Sensing 66, 981- 989.
  • EASTMAN, R.J. (2001) Guide to GIS and Image Processing, Release 32. Worcester, dark Labs, dark University, MA.
  • GALLANT, J.C. and WILSON, J.P. (2000) Primary Topographic Attributes. In: J.P Wilson and J.C. Gallant, eds., Terrain Analysis Principles and Applications. John Wiley & Sons, Inc. New York, 51-85.
  • GORSEVSKI, P.V., GESSLER, P.E. and FOLTZ, R.B. (2000) Spatial Prediction of Landslide Hazard Using Logistic Regression and GIS. In 4th International Conference on Integrating GIS and Environmental Modeling (GIS/EM4.): Problems, Prospects and Research, Needs. Banff, Alberta, Canada, September 2 - 8. [CD-ROM],
  • GORSEVSKI, P.V. (2002) Landslide Hazard Modeling Using GIS. Ph.D. Dissertation: University of Idalio, Moscow ID.
  • GORSEVSKI, P.V. and GESSLER, P.E. (2003) Bayesian modeling and GIS for evaluating landslide hazard. ASPRS 2003 Annual Conference: Anchorage, AK, May 5-9, 2003.
  • GORSEVSKI, P.V., GESSLER, P.E., FOLTZ, R.B. and ELLIOT, W.J. (2006) Spatial prediction of landslide hazard using logistic regression and ROC analysis. Transactions in GIS 10 (3), 395-415.
  • GORSEVSKI, P.V., GESSLER, P.E. and JANKOWSKI, P. (2003) Integrating a fuzzy k-means classification and a Bayesian approach for spatial prediction of landslide hazard. Journal of Geographical Systems 5, 223-251.
  • GORSEVSKI, P.V., GESSLER, P.E. and JANKOWSKI, P. (2004) Spatial prediction of landslide hazard using fuzzy k-means and Bayes theorem. In: W. Widacki, A. Bytnerowicz, and A. Riebau, eds., A Message From the Tatra: Geographical Information Systems and Remote Sensing in Mountain Environmental Research, Jagiellonian University Press: Krakow, Poland, 159-172.
  • GORSEVSKI, P.V., JANKOWSKI, P. and GESSLER, P.E. (2005) Spatial prediction of landslide hazard using fuzzy k-means and Dempster-Shafer theory. Transactions in GIS 9, 455-474.
  • JIANG, H. and EASTMAN, R.J. (2000) Application of fuzzy measures in multi-criteria evaluation in GIS. International Journal of Geographical Information Science 14, 173-184.
  • JUAN, S., QUANGONG, C., RUIJUN, L. and WENLAN, J. (2004) An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection. New Zealand Journal of Agricultural Research 47, 327-331.
  • LESKINEN, P. (2000) Measurement scales and scale independence in the analytic hierarchy process. Journal of Multi-Criteria Decision Analysis 9, 163-174.
  • LOOTSMA, F.A. (1993) Scale sensitivity in the Multiplicative AHP and SMART. Journal of Multi-Criteria Decision Analysis 2, 87-110.
  • MALCZEWSKI, J. (1999) GIS and multicriteria Decision Analysis. John Wiley & Sons, New York.
  • MACMILLAN, R.A., PETTAPIECE, W.W., NOLAN, S.C. and GODDARD, T.W (2000) A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic. Fuzzy Sets and Systems 113, 81-109.
  • MCCLELLAND, D.E., FOLTZ, R.B., WILSON, W.D., CUNDY, T.W., HEINEMANN, R., SAURBIER, J.A., and SCHUSTER, R.L. (1997) Assessment of the 1995 & 1996 floods and landslides on the Clear-water National Forest. Part I: Landslide Assessment, A Report to the Regional Forester Northern Region U.S. Forest Service, December.
  • MIKHAILOV, L. (2003) Deriving priorities from fuzzy pairwise comparison judgements. Fuzzy Sets and Systems 134, 365-385.
  • MONTGOMERY, D.R. and DIETRICH, W.E. (1994) A physically based model for the topographic control on shallow landsliding. Water Resources Research 30, 1153-1171.
  • MOORE, I.D., GESSLER, P.E., NIELSEN, G.A. and PETERSON, G.A. (1993) Soil attribute prediction using terrain analyses, Soil Science Society of America Journal 57, 443-452.
  • SAATY, T.L. (1998) The Analytic Hierarchy Process. McGraw-Hill, New York.
  • STEFANAKIS, E., VAZIRGIANNIS, M. and SELLIS, T. (1999) Incorporating fuzzy set methodologies in a DBMS repository for the application domain of GIS, International Journal of Geographical Information Science 13, G57-675.
  • VARGAS, L.G. (1990) An overview of the analytic hierarchy process and its applications. European Journal of Operational Research 48, 2-8.
  • VAIDYA, O.S. and KUMAR, S. (2004) Analytic Hierarchy Process: an overview of applications. European Journal of Operational Research, In press.
  • VOOGD, H. (1983) Multi-criteria Evaluations for Urban and Regional Planning. Princeton University, London.
  • Wu, W. and SIDLE, R. C. (1995) A distributed slope stability model for steep forested basins. Water Resources Research 31, 2097-2110.
  • YAGER, R.R. (1988) On Ordered Weighted Averaging aggregation operators in multicriteria decision making. IEEE Transactions on Systems. Man, and Cybernetics 8, 183-190.
  • ZADEH, L.A. (1965) Fuzzy sets. Information and Control 8, 338-353.
  • ZADEH, L.A. (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1, 3-28.
  • ZADEH, L.A. (1987) Fuzzy sets as a basis for a theory of possibility. In: R.R. Yager, S. Ovchinnikov, R.M. Tong and H.T. Nguyen, eds., Fuzzy sets and applications: selected papers by L.A. Zadeh, John Wiley and Sons, New York, 193-218.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0010-0056
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.