Comparison and evaluation of three methods of multi attribute decision making methods in choosing the best plant species for environmental management (Case study: Chah Jam Erg)

Document Type : Scientific and Research


1 Professor of Physical Geography (Geomorphology), Faculty of Geography, University of Tehran, Tehran, Iran

2 Ph.D Candidate of Geomorpholog, Faculty of Humanities, Department of Geography, Tarbiat Modares University, Tehran, Iran


Today, environmental crisis and loss of natural resources are the principle causes of the creation of environmental management systems. The optimal management of natural resources requires the assessment and classification of ecological and environmental potentials. Using this method, the abilities and restrictions of resources can be recognized, and their future trends can be predicted. Nebka landscape is the natural reaction of ecosystem against the stress of wind erosion and ecosystem tries to adjust wind stress by creating this landscape. Therefore, the development of Nebka is the best and most suitable method for quicksand stabilization in the study area, and the most adaptable type of Nebka species must be identified and selected for the development of the ecosystem. This important aim will not be achieved except through careful and scientific investigation of Nebka phenomenon. According to the present environmental conditions, a suitable method with high accuracy is required in order to evaluate and manage natural resources and environment for achieving sustainable development. The aim of this study was to select the best Nebka species for quicksand stabilization using their morphometric parameters analysis by multi attribute decision making (MADM) methods. The results of this study show that in three models, Haloxylon obtained the highest point. Therefore, it has the highest effect in stabilization of quicksand. For implementation of stabilization projects of mobile sands in the study area, development of Haloxylon Nebka systems have the highest importance and efficiency. The results of this study will be beneficial in systemic management of desert regions and stabilization projects of quicksand.


1. Ahmadi, H. 1998. Applied Geomorphology, second volume wind erosion, University of Tehran.
2. Asgharpour, A.A., 2012. Multi CriteriaDecision Making, Second Edition, University of Tehran.
3. Bellman, R.E., Zadeh, L.A., 1970. Decision-making in a fuzzy environment, Management Sciences, 17, 141–164.
4. Bishop, S.R., Momiji, H., Carretero-Gonzalez, R., Warren, A., 2002. Modelling desert dune fields based on discrete dynamics. Discrete Dynamicsin Nature and Society, 7, 7–17.
5. Boender, C.G.E., Graan, J.G., Lootsma, F.A., 1989. Multi-attribute decision analysis with fuzzy pairwise comparisons, Fuzzy Sets and Systems, 29, 133–143.
6. Chang, Y.H., Yeh, C.H., 2002. A survey analysis of service quality for domestic airlines, European Journal of Operational Research, 139, 166–177.
7. Chen, C.T., 2000. Extensions to the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets and Systems, 114- 119.
8. Chen, S.J., Hwang, C.L., 1992. Fuzzy multiple attribute decision making methods and application, in: Lecture Notes in Economics and MathematicalSystems, Springer, New York.
9. Danin, A., 1996. Plants of desert dunes. Springer, 177,136 p.
10. Douseri, A., 1995. Sedimentolongical and Morohological characteristics of some nebkha deposits in the northern coastal plain of Kuwait, Arabia. J. Arid Environ, 29,267-292.
11. Dougill, A.J., Thomas, A.D., 2002. Nebkha dunes in the Molopo Basin, South Africa and Botswana, 145-189.
12. Feng, C.M., Wang, R., 2000. Performance evaluation for airlines including the consideration of financial ratios, Journal of Air Transport Management, 6, 133–142.
13. Ghodsi Poor, H., 2009. Analysis Hierarchal Process, Tehran, Amir Kabir University Press, Fifth Edition.
14. Hesp, P., 2002. Foredunes and blowouts: Initiation, geomorphology and dynamics. Geomorphology, 48, 245–268.
15. Hsu, H.M., Chen, C.T., 1996. Aggregation of fuzzy opinions under group decision making, Fuzzy Sets and Systems, 79, 279–285.
16. Hsu, H.M., Chen, C.T. 1997. Fuzzy credibility relation method for multiple criteria decision-making problems, Information Sciences, 96, 79–91.
17. Hwang, C.L., Yoon, K., 1981. Multiple Attribute Decision Making: Methods and Application, Springer, New York.
18. Jain, R., 1978. A procedure for multi-aspect decision making using fuzzy sets, The International Journal of Systems Sciences, 8, 1–7.
19. Kacprzyk, J., Fedrizzi, M., Nurmi, H., 1992. Group decision making and consensus under fuzzy preferences and fuzzy majority, Fuzzy Sets andSystems, 49, 21–31.
20. Keeney, R., Raiffa, H., 1976. Decision with Multiple Objective: Preference and Value Tradeoffs, Wiley, New Work.
21. Lee, H.S. 1999. Optimal consensus of fuzzy opinions under group decision making environment, in: IEEE International Conference onSystems, Man and Cybernetics, Tokyo, Japan, 314–319.
22. Liang, G.S., 1999. Fuzzy MCDM based on ideal and anti-ideal concepts, European Journal of Operational Research, 112, 682–691.
23. Mousavi, S.H., Moyari, M., Sayf, A., Vali, A.A., 2012. Selection of the most appropriate plant species for stabilizing of sand dunes using AHP model (Case study: Najarabad Erg. Northeastern of troud, Journal of environmentalogy, 61, 105-116.
24. Nickling, W.G., Wolfe, S.A., 1994. The Morphology and Ongin of Nebkhas, Region of Mopti, Mali, West Africa,Journal of Arid Environments, 28, 13-30.
25. Nurmi, H., 1981. Approaches to collect decision making with fuzzy preference relations, Fuzzy Sets and Systems, 6, 249–259.
26. Olson, D.L., 2004. Comparison of weights in TOPSIS models, Mathematical and Computer Modeling, 40, 21-727.
27. Pradhan, B., 2011. An Assessment of the Use of an Advanced Neural Network Model with Five Different Training Strategies for the Preparation of Landslide Susceptibility Maps. Journal of Data Science, 9, 65-81.
28. Raj, P.A., Kumar, D.N., 1999. Ranking alternatives with fuzzy weights using maximizing set and minimizing set, Fuzzy Sets and Systems, 105, 365–375.
29. Refahi, H., 2004. Wind erosion and its control, University of Tehran.
30. Roy, B., 1991. The outranking Approach and the foundation of ELECTRE Methods, Theory and Decision, 31, 49-73.
31. Tavakoli, A., Aliahmaid, A., 2005. Modelselectionand prioritizationmethodsof transfer of technology, Tehran, published by University of Science and Technology. 
32. Tanino, T., 1984. Fuzzy preference in group decision making, Fuzzy Sets and Systems, 12, 117–131.
33. Tsaur, S.H., Chang, T.Y., Yen, C.H., 2002. The evaluation of airline service quality by fuzzy MCDM, Tourism Management, 23, 107–115.
34. Tengberg, A. 1994. Nebkhas-their Spatial Distribution Morphometry, Composition and Age in the Sidi Bouzid Area, Central Tunisia, Zeitschrift Fur Geomorphology, 38, 311-325.
35. Tengberg, A., 1995. Nebkha Dunes as Indicators of Wind Erosion and Land Degradation in The Sahel Zone of Burkina Faso, Journal of Arid Environ Ments, 30, 265-282.
36. Tengberg, A., Chen, D., 1998. A Comparative Analysis of Nebkha in Centeral Tunisia and Northern Burkina Faso, Geomorphology, 22, 181-192.
37. Thomas, D.S.G., Tsoar, H., 1990. The Geomorphological Role of Vegetation in Desert Dune Systems. In Vegetation and Erosion, Processes and Environments, Thornes JB (ed)., John Wiley: Chichester, 471-489.
38. Tille, M., Dumont, A.G., 2003. Methods of Multi criteria Decision Analysis Within the Road Project like an Element of the Sustainability, 3rd Swiss Transport Research Conference, March, 19-21.
39. Vami, H., 1992. Project opportunity Study on Integrated use of the Razgah Nepheline ores, Iran by metallurgical processing into Alumina Cement, sodium Carbonate and potash, final report, Volume, general explanatory note.
40. Vali, A., Poorgsrvani, M., 2008. Comparison Analysis Nebka Morphometric Relationships between Components and Morphology of Plant Species Tamarix Mascatensis, Reaumuria Turkestanica,Mannifera Alhagi in Khairabad Sirjan, Geography and Environmental Planning, 20, 35, 119-134.
41. Wasson, R.J., Hyde, R., 1983. Factors determining desert dune type. Nature 304, 337–339.
42. Wang, Y.J., Lee, H.S., Lin, K., 2003. Fuzzy TOPSIS for multi-criteria decision-making, International Mathematical Journal, 3, 367–379.
43. Wanga, B., Wanga, X.T., Donga, Z., Liuc, B. X., Qiana, G., 2006. Nebka Development and its Significance to Wind Erosion and Land Degradation in Semi-arid Northern China, Journal of Arid Environments, 65, 129-141.
44. Werner, B.T., 1995. Eolian dunes: computer simulation and attractor interpretation, Geology, 23, 1107–1110.
45. Zadeh, L.A., 1965. Fuzzy sets, Information and Control, 8, 338–353.
46. Zimmermann, H.J., 1987. Fuzzy Set, Decision Making and Expert System, Kluwer, Boston.
47. Zimmermann, H.J., 1991. Fuzzy Set Theory – And its Application, 2nd ed., Kluwer, Boston.