Abstract
Keywords
Geomorphological Zoning of Arak City by Using Fuzzy logic Model
(The Approach to the Future Development of Arak)
M. Abedini[1]
Asisstant Prof. of Geomorphology, Mohaghegh Ardebili University, Ardebil, Iran
B. Mirzakhani,
Ph.D Student in Geomorphology, Mohaghegh Ardebili University, Ardebil, Iran
A. Asgari
P.h.D Student in Geomorphology, Tabriz Universit, Tabriz, Iran
Abstract
The main objective of this study refers to zone Arak city by using geomorphological parameters of the fuzzy logic model. In order to fulfil these objectives, 10 parameters such as effective height, the distance from fault, the distance from the main channel, the distance from sub-channel, distance out of the way of communication, slope percent, distance from settlements, topography type, land erosion and seismic vulnerability in the form of raster and vector maps were prepared. Each raster layer was defined based on research studies and expert’s opinion. But being in a range of vector layers 0 and 1 did not need to be defined. After applying the functions, operations, multiplication, addition and different values of gamma phase were also performed on the layers. So, ARC GIS 9.3 and ERDAS 9.1 software were used. Since, comparison analysis has been done between the suitable arenas to real situation of city according to the critical arenas and suitable arenas of the gammas quantities. Based on finding, the fuzzy gammas have been in match with the most suitable lands of the town. The results indicated that two stations in the West and the East of County seemed suitable for the future development of Arak, but the north and northeast arena of city were the first priority at present time. At last, the final map was classified to 5 classes: very low portion 2189, low proportion 389, medium proportion 593, high proportion 552 and very high proportion 381 with a great square kilometers were defined, respectively.
Key words: Spatial development, Fuzzy operator, Geomorphological parameters, Arak.
15. Ale sheikh, A., Soltani, M., Nouri, N., Khalilzadeh, M, (2008): Land Assessment for Flood Spreading Site Selection Using Geospatial Information System, International Journal of Environmental Science and Technology, Vole .5, No .4, 455-462.
16. Egger, S, (2005): Determining a sustainable city model. Environmental Modeling & Software.
19. Jiang, H. and Eastman, R, (2000): Application of fuzzy measurement in multi_ criteria evaluation in GIS. International Journal of Geographic Information System, vol.14, No2, pp.173-184.
20. Messer Y., (2003): Impact of Remote Sensing & GIS in Management of Cities Futures, Translated by Email Youssef, Urban Management Quarterly, No. 15-16.
21. Isaai,M., Kanani,K., Tootoonchi,M., Afzali,H.R, Intelligent timetable evaluation using fuzzy AHP. Expert Systems with Applications 38 (2011): 3718–3723.
22. Vahidnia, M.H., Alesheikh, A.A., Alimohammadi, A, Hospital site selection using fuzzy AHP and its derivatives, Journal of Environmental Management 90 (2009): 3048–3056.
23. Vickers, M. and Gavin Fleming.2009.Fuzzy logic: identifuing for mineral development.Position IT.
24. United Nations settlements program me (UN-HABITAT),(2003): the challenge of slums: global report on human settlements. London: Earth scan.