These days profitable development and the need to create new urban land uses to ask needs of urban residents has gradually declined and these located in the incorrect place. It causes, the distribution of green spaces in the city was often inappropriate and social injustice is created. The purpose of this paper is to evaluate the 15 regions of the Isfahan municipality in order to determine regions which have priority for the development of urban green space. Isfahan is one of the metropolises in Iran that has many environmental problems such as drought and water crisis, lack of proper urban land for developing of green space, air pollution, increasing population and vehicles and etc. So a systematic planning in the field of optimum locating for green spaces is very necessary. This paper looking for answering this question: What is the priority of creating green spaces in 15 regions of Isfahan? So at first 18 parameters which are effective in the construction of green spaces have been determined. Based on the data available of these parameters in the 15 regions, F’ANP model has been used in order to build composite index and evaluate regions.Isfahan, with an area of over 550 square kilometers and a population of more than two million, is the third metropolis in the center of Iran. Service range of this city consists of 15 regions which this paper has been studied separately. Any prioritization requires the selection of indicators and criteria which related to that category. The importance of each of these indicators is indicated with considering the weight for each indicator. Among the effective indicators choosing the right place (which was discussed in the theoretical foundations), indicators which are compatible with conditions of Isfahan, were selected and studied in the 15 regions.
In the first step, 18 key indicators have been extracted from theoretical literature. In the second step these indicators according to documents and information available are calculated in the 15 regions and required data have been provided in order to analyze indices. In the third step obtained data are considered as model’s inputs. The reason for using this method is that it covers one of the most important methodological problems in the field of location and prioritization. Previous studies show that prioritizations have so far been according to the subjective methods. In order word weight of influencing parameters have been done by experts and researchers.
Mentality of the parameters' weight are resolved by F’ANP model. In fact, the Isfahan’s environment determines parameters' weight and how to prioritize by determining relationships between parameters. This paper is in the category of applied research and it’s methodology is analytical-descriptive.
In this model, the adequacy of the sample size which be evaluated by test Sphere s’Bartlett and Kaiser- Meyer- Olkin (KMO) is more important than the amount of the sample size. So as long as if the values of these two tests do not reach the standard level, the sample size should increase or communalities should change. In this paper with regards to limitations of checked options (15 regions), suitable amount of these tests is obtained by reducing the number of variables. Therefore, 8 parameters deleted in order to increase the accuracy of the model. Then the factors are named according to the gender and nature of the indicators (Table1). After removing some indicators, the amount of KMO and Bartlett’s test are arrived to the standard value (Table2). These values show that the accuracy of the model is acceptable.
At the end of the research, composite index of need for green space development is calculated. So achieved weights are multiplied by the values of each indicators. The result of this operation shows values of indicators. The following formula has been used in order to build composite index:
〖NGSD 〗_i=∑_(j=1)^J▒〖W_(F^' ANP j ) QV_ij 〗
In this formula 〖NGSD〗_i is composite index of need for green space development which belongs to region i. ، W_(F^' ANP j ) is the relative weight of indicator j which is obtained from F’ANP model as output. And QV_ij is the amount of score indicator j in region i.
Then 15 regions of Esfahan have been prioritized by achieved composite index. These scores mean that the each region which is weaker in each indicator, it’s score is lower too. In fact less score indicates the more critical in existing green space in the region. So that region should be located at the higher priority of developing of green space.
Green space in the city is one of the most important indicators which affects the quality of life. With the growing urbanization, green spaces have been damaged by city managers for supplying other needs of citizens or by Land traders. So these days choosing the right priority of the development of green spaces and right place to create green space is more important than the past. So we can say this is one of the most important managerial needs in the modern cities. So far, many studies have been done in theoretical literature on urban planning and the environment. Lack of systematic approach which is far from the minds of experts is one of the most important gaps in this theoretical literature. The purpose of this article is to provide a method which is based on a systematic approach.
For this purpose, 18 parameters which explain how to prioritize the development of green spaces have been evaluated using the F'ANP model.
The results indicate that three factors of "physical and functional needs", "natural and environmental needs" and "economic and social needs" explain the priority of the need to develop green space in Isfahan.
The findings show that regions of 8 and 10 placed in the top priority and region of 9 placed in the least priority. The results of this research have been checked with reports of the need to develop green space which is done in the municipality of Isfahan that results confirm the prioritization of this model.
This indicates that we can achieve valuable results in terms of prioritization by applying a systematic approach to this issue and by using systematic multivariate methods of evaluation.