بررسی ارتباط میان ساختار فضایی منطقه‌ای، پراکنده رویی و الگوی سفر بین‌شهری در استان‌های ایران

Many experts and regional planners believe that multicenter development can create a balance between growth, dispersion, and compression, and while protecting land, reduce greenhouse gas emissions by reducing motor vehicle trips. Based on this, this article seeks to strengthen the decision makers' understanding of its application by examining the relationship between polycentricity or monocentricity in 31 country provinces, the travel pattern and scattered behaviour. Thus, the logic of the current research is comparative and based on descriptive and correlational methods. First, using two criteria of city size distribution and spatial distribution of centres, the degree of polycentricity of the country's provinces was determined. Then, using Pearson's correlation, the relationship between the spatial structure indicators and topographically dispersed variables and travel patterns at the level of the country's provinces was investigated. The results show that more polycentric provinces generate more trips per person (personal and public). Also, there is a positive and significant link (0.825) between the spatial distribution of cities, the degree of polycentricity of provinces and energy consumption caused by transportation. Although, at first glance, the increase in the share of trips by private car can appear as a threat in multi-centred areas, but according to the travel demand, it can be an economic justification for strengthening public transportation and an opportunity to reduce pollution, especially in multi-centred metropolitan areas. In addition, there is an inverse relationship between the size distribution of cities, and the number and area of building permits (respectively, -0.37 and -0.36), which can indicate the weakening of economic incentives for urban sprawl. Finally, it seems that the polycentric-intensive model can be a more suitable structure for sustainable development.
Extended Abstract
Introduction
Today, the role of urban structure has been revealed as an essential factor in facilitating travel, as it provides a framework for locating homes and businesses. After the publication of the European spatial development vision document (1999), polycentric development became a promising tool to achieve the macro goals of spatial policies, such as promoting social cohesion, economic competitiveness, and environmental sustainability. Since such political goals are often set on a large scale, they are also easily accepted on smaller scales. Regarding the relationship between a polycentric city and environmental sustainability, some authors refer to polycentric development as a middle ground for the spatial organization of monocentric/compact areas and scattered areas. According to them, this model can allow the regions to benefit from the benefits of spatial expansion without paying the cost of the scattered development mentioned in the literature. Even in terms of traffic, polycentric development can facilitate shorter distances and the use of public transport. Therefore, a more sustainable movement pattern in terms of time and pollution emissions. In this way, considering the country's political system, the lack of multi-level governance, and policies on local features and characteristics, the provincial scale and the morphological dimension is the most important point of intersection. Also, conducting comparative studies examining the relationships between polycentric indicators and environmental sustainability in different contexts and comparing them with other countries' findings can resolve ambiguities. Based on this, the present article examines the relationship between the polycentric city, dispersion indicators, and energy consumption caused by travel flows.
 
Methodology
Considering the nature of the topic and the hypotheses raised about the relationship between polycentric cities, travel patterns, and dispersion, the correlation method has
 
been used in this research. In this regard, firstly, the degree of the polycentric city or monocentric of the provinces was measured based on the components of the size distribution of the cities and their spatial distribution and compared with each other.  For this purpose, urban primate city index was exerted to measure the size distribution of cities and their spatial distribution. Also, hot spots analysis in GIS was exploited. After calculating the indices, the obtained values were standardized and combined to define the degree of the polycentric city of the provinces between 0 and 1. The number 1 indicates a completely polycentric spatial structure. The data in this section have been collected from the statistical yearbook of 2015. Then, using Pearson's correlation, the relationship between spatial structure indicators and dispersion variables and travel patterns at the level of the provinces was investigated.
 
Results and discussion
The results show that Mazandaran, Golestan, and Kurdistan are the most balanced provinces of the country in terms of population size distribution. On the other hand, the provinces of Qom, Tehran, Alborz, Yazd, Khorasan Razavi, and Isfahan, respectively, have a higher level of urban importance. In terms of spatial distribution, Mazandaran's natural and geographical features have formed a completely decentralized spatial area, which defines this province as a completely polycentric region from this point of view. Thus, Mazandaran is at the top of this list, and after that, Kerman, Khuzestan, and Fars provinces are known as the most decentralized provinces of the country. On the other hand, Qom, Tehran, and Alborz provinces should be introduced as the most concentrated provinces of the country in terms of space. Finally, from the sum of the standardized scores of the two components of center size distribution and their spatial distribution, the degree of the polycentric city of the country's provinces was determined. The results of this section show that the provinces of Mazandaran, Kerman, Khuzestan, and West Azarbaijan are the most polycentric. On the contrary, the provinces of Qom, Tehran, Yazd, and Alborz are the most monocentric provinces of the country. An important point in this evaluation is the intermediate structures so that the main parts of the country's provinces are located in one of the forms of a scattered monocentric region or a centralized a polycentric region. For example, Ilam and Semnan provinces can be introduced as examples of relatively polycentric but concentrated regions. One of the first assumptions related to the benefits of polycentric region is its support for public transportation and reducing dependence on private cars. Examining the analysis findings among the 31 provinces of the country shows an inverse relationship between the rank-size index and the share of public trips.
 
Conclusion
In recent years, many researchers believed that polycentric spatial structures could balance economic growth, territorial cohesion, and environmental sustainability. This has caused many studies on the effectiveness and efficiency of these areas in different spatial scales. While most studies focus on economic and social goals and metropolitan or national scales, examining the relationship between spatial structure indicators and environmental sustainability at the regional scale has been largely neglected. In this regard, the present study seeks to examine this assumption in the provinces of the country by measuring the polycentric city of the spatial structure and emphasizing the two components of the pattern of intercity travel and dispersion. In examining the relationship between dispersion and polycentric city indicators, the findings indicate an inverse and positive link between the rank-size index and the spatial distribution of cities with the increase in permits and the area of ​​construction of residential units, respectively. In other words, a set of small and medium-sized cities that are close can avoid the increase of residential construction as an indicator of dispersion. These findings somehow support polycentric urban areas. However, when the number of households is considered in the number of constructions, there is no intermediate link between population balance and the increase and area of ​​constructions; instead, this link with spatial distribution is still established.
 
Funding
There is no funding support.
 
Author’s Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper