Locating the optimal model of urban green space using Fuzzy Logic and AHP,By GIS. Case study: the city of Mashhad
Subject Areas :Davod Hatami 1 , Zahra Arabi 2 , Esmail Rahmani 3
1 - MA Geography and Urban Planning, University of Sistan and Baluchestan
2 - Geography Department, Payam Noor University, Tehran, Iran
3 - MA Geography and Urban Planning, University of Sistan and Baluchestan
Keywords: fuzzy logic, Geographic Information System (GIS), Analytical Hierarchy Process (AHP), locating, landscaping Me, city mashhad,
Abstract :
Today, with respect to the role and importance of urban green space in urban life and its physical stability and effectiveness of urban systems and benefits in different ecological, social and economic, it is undeniable to use green space per capita in urban areas as one of the basic issues in planning and urban management. Urban green space, including land use and distribution that it is important in the Mashhad city, including the cities of the status of green space, is not appropriate; so that based on the findings, the average green space per capita in Mashhad is 5.51, m , while the standard MHUD is 12 square meters per capita . Therefore, it has suggested, there seems to exist a huge gap. However, its spatial distribution is very unbalanced and disproportionate. Green space areas such as Samen with 1.2, square meters and 21 square meters has per capita area of only seven. The method of this study was descriptive-analytic and theoretical-practical. The nature shows that, contrary to national and international standards for green space, the green space in the city is very low and its spatial distribution in twelve areas in Mashhad, is also facing a severe failure and is not balanced in this regard. In this study for analysis to determine the optimum location of green space model layers required Logic Fuzzy, AHP and means nearest neighbor were used for the operation of the software of ARC / GIS and Expert choice. Five spectra of very good, good, fair, poor and very poor were recognized. Then the act of prioritizing was rendered.