Examining the Spatial Pattern of Industrial Activities in Tehran Metropolitan Region

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction
Various studies have been conducted to analyze the spatial structure of metropolitan regions over the past few decades. These studies can be classified mainly into two population and activity domains. The former explains the settlement system, and the latter explains the activity system. Majority of the studies on the spatial structure were activity-oriented. Spatial structure of activity, in fact, indicates employment and firm’s distribution in the spatial domain of metropolitan regions. In other words, it is the degree of spatial concentration of activity. To explain the spatial distribution of economic activities and understanding spatial-activity structure of the regions, employment density or a kind of economic agglomeration in the geographic domain is seen as an important and indispensable part of the activities distribution in the region. Thus, we can analyze the pattern of activity structure and also understand the influenced and independent points in the spatial-activity structure of the metropolitan regions. The main aim of this research is to examine industrial activities in Tehran metropolitan region and analyze the quality of these changes in relation to geographic characteristics of the principal city, which can be studied using influential variables and indexes. Based on previous studies, the way of dispersion of firms and industrial activities in the metropolitan region and the degree of units’ interrelations are influential variables on the activity-spatial structure through which the understanding of the activity-spatial structure of Tehran metropolitan region and its appropriate arrangement can be achieved.
Review of literature

The results of studies carried out in recent decades indicate that the spatial structure of the metropolitan areas is moving from a monocentric to a polycentric structure. In general, from the nineteenth century, the classic monocentric city model gradually became evolving. During this period, cities were expanded by the processes of industrialization. Hence, the suburbanization of the population accelerated with increasing levels of income combined with the invention and increase of ownership of cars and other transport systems and the construction of an extensive road infrastructure, making it possible for sites with lower densities, higher housing affordability, lack of disadvantages such as congestion, crime, and so on. During the twentieth century, these processes were more accelerated.
Suburban centers were developed over central business districts, while suburban areas developed over the city. Hence, in line with the growth of metropolises populations, their peripheral lands are developed, and the problem of sprawl and polycentric structures emerged. These dimensions represent the concentration of activity in the main city or the extent of the distribution of activity in one or more suburbs of the metropolitan area. In this situation, the spatial structure of the metropolitan area is largely defined in terms of features such as monocentric, polycentric, and dispersed patterns.
Method
The methodology adopted for the present study is quantitative and practical, and the approach is descriptive-analytical. The required data, including distribution and concentration of activities, number, and density of employment, are obtained from the Ministry of Industry and Trade (data of 2014). GIS layers, including the administrative-political divisions and the area and distance of each to rural districts and counties, are obtained from SCI in 2011. The most important tool for software analysis is ArcGIS, GEODA, and SPSS. To understand the spatial-activity pattern with regard to the distribution variable and the concentration of industrial activities, there are indicators and methods that show the distribution and concentration of industrial activities in the region and also in different districts. In this research, the method of distribution of industrial activities in the metropolitan area of ​​Tehran is used by the Herfindahl index, the Gini coefficient, and the global Moron, whereas the recognition of the industrial activity concentration patterns is achieved by the local Moran method.
Results and Discussion
The main objective of this paper is to analyze the spatial distribution of industrial activities in the Tehran metropolitan region and to analyze the quality of these changes in relation to the geographic features of the Tehran metropolitan region. The findings obtained based on the Gini coefficient show that the distribution of industrial activities in the eight industrial subdivisions has been randomly distributed, and the distribution in different parts of the metropolitan region have been dispersed. Furthermore, the results for the 28 subdivisions of the industry indicate that most of the sectors are still unbalanced. In contrast, the sub-sectors of basic metals, non-metallic mineral products, fabricated metal products, chemicals, and chemical production, and machine manufacturing Machinery and equipment have a more balanced distribution than other sectors.
Calculating the Hierpindal Index also shows that among the 8 sub-sections, the manufacturing sub-sections and materials have a more dispersed distribution than other sub-sections. Moreover, the service and financial sector with the highest index of Hierpindal indicates the accumulation and density of this sector in the Tehran metropolitan region. Based on the 28 industrial subdivisions, the Harpindal Index in the computer, energy generation, and tobacco products is at its maximum. This suggests that there is a complete concentration in these three sub-sections. But the production of metal and non-metallic products, wood products, machinery and food products, and the most balanced distribution are seen in other parts, indicating the distribution and agglomeration in the Tehran metropolitan region.
The results of the Moran Global Index for 8 industrial subdivisions show that all industrial sub-sectors of Tehran metropolitan region have a dispersed spatial pattern. Cluster patterns are not visible in the industrial area of ​​ the suburbs in Tehran. According to this method, in the raw materials sector, the most dispersion belongs to the region, while the least degree of dispersion belongs to the service and financial sector. There is a significant dispersion of 28 sub-sectors in the sub-sectors of paper, wood, rubber and plastics and also the production of basic metals and petroleum products, which shows that the production of these products is dispersed in Tehran metropolitan region.
Conclusion
From the above results, it can be concluded that spatial-patterns of the Tehran metropolitan region follows a concentrated pattern if the distribution of activities in the industrial sub-sectors is randomly observed. These random patterns are indicative of the fluctuation of programs and policies in the field of locating industrial activities. In addition, the spatial distribution of industrial activities is unbalanced and tends to disperse. Nevertheless, the concentrated pattern is trickled down; therefore, signs of the decentralization of industrial activities can be seen in the suburbs of Tehran such as Quds, Chardanje, Ray, Malard, Sharifabad, and Ahmad Abad.
In general, industrial subdivisions have different patterns that have shaped the industrial structure of the metropolitan area. However, two main eastern and western corridors can be generally seen in the region. In this context, various measures can be taken to strengthen these industrial centers and other centers in the region in order to strengthen the polycentric and network model, which requires identifying sub-centers with the capability and capacity of industrial activities in the industrial sector. For this reason, the program is considered to be necessary to form a poly-centric structure in the planning and management system.
Language:
Persian
Published:
Journal Of Geography and Regional Development Reseach Journal, Volume:16 Issue: 2, 2019
Pages:
179 to 212
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