Analysis of Spatial Organization in Urban Network Based on Air Flows of People: Empirical Evidence for Iran

Studying the spatial structure of urban systems and the inter-urban relationships in particular, has occupied a special place in the context of urban and regional studies for a long time (Meijers, 2007, 245). Since the late 1960s and the emergence of a system approach an urban system is not only a set of physical instances- in this case urban nodes- but rather it includes the spatial interurban linkages (Simmons, 1978) and is defined through relations and flows among cities and their position in the outer complex network. Therefore, a change in any defining components of an urban system (including nodes and linkages) can be associated with a change in its spatial constellation including spatial structure and organization. In other words, increase in accessibility between places are more a function of cross-border networks and are increasingly determined by flows within system (Derudder and Witlox, 2005; Neal, 2010) rather than what fixed within them (Smith, 2003). As most of empirical evidences have been done so far was based on location attributes derived by size-based approach (like population), a little attention has been paid to connections between urban nodes. Apart from these short comings, few attempts are made to propose a methodology for assessment and evaluation of an urban system configuration based on the analysis of exchanges flows. Therefore, in one hand, this article attempts to present a more complete and advanced methodology of the study on the nature of the spatial constellation in urban systems to advance this research field. This helps identification of different dimensions of their configuration as derived from an interaction approach. On the other hand, it attempts to identify urban spatial constellation by providing empirical evidence from Air Passenger Flows (APF) in 2006 and compare this with the resulted urban hierarchy based on population in the same year. In this study, data were used from long-distance personal travel. With regard to the purpose of this research and within its defined theoretical framework, only O-D data were applied. The required O-D data for APF were obtained from the statistical year book of Air Transport of Iran published by the Iran Airlines Organization (IAO) in 2006. According to this report, there were 59 domestic airports in Iran in 2006, with the nearest city to each airport utilized as the relevant transport network (city) node in the calculations (Statistical Annals of Aerial Transportation of Iran, 2006). The spatial scale of this study is national, but in respect of mentioned limitations in providing geographical information on the origin and destination of long-distance travels, it is preferable and plausible to use political division of provinces as delimitation of the study area. For this reason, we employ thirty provincial main urban areas in 2006 as spatial units of analysis. As a result, the spatial level has been restricted to inter urban relations through flows of people. The five dimensions of an urban systems spatial configuration investigated are including:. centrality and the dominance of the vertices, 2. network cohesion, 3. network strength, 4. network symmetry, and 5. communities and levels, which are described systematically and made measurable due to the values of the indices. The position of the spatial configuration, regardless of spatial scale or the type of flow, ranges across a continuum from purely monocentric to completely networked. In APF the total number of movement of passengers via inner aerial public transportation fleet in 2006 was 12, 225, 183 According to the first dimension, centrality and power, out of 400 possible centrality points, Tehran had value of 271. Mashhad with a centrality of 166.17, which is substantially less than that for Tehran, was ranked at second. Consequently, it is concluded that the APF is topologically monocentric. The maximum value for network cohesion can be 700 and the APF gains only 457.70 scores and this network with low cohesion differs significantly from a networked constellation and has greater similarity to mono-polar structures. The maximum value of the third dimension, network strength, can be as high as 300 and the APF is a more concentrated network with strength of 169.13. The range of the obtained values for the fourth dimension, network symmetry, can be from 0 to 200 and according to obtained value (193.43), it can be claimed that the air flows of people is symmetrical. The results from the fifth dimension, community and levels, shows that for APF, which has more in common with the mono-centric model, because of limitation of city organization in superior levels, only two communities of vertices and three levels were detectable. The empirical findings expresses that Tehran is in the first rank and then Mashhad as having significant differences in comparison with other cities at lower spatial levels in that it is the prime city of network; hence the spatial constellation of the network is considerably different from a polycentric. In regard to the second dimension, network cohesion, APF represents low level of cohesion. This occurred because for APF, Mashhad, Bandar Abbas, Ahvaz and Shiraz are all located at further geographical distances from the network central city (Tehran) and yet are still able to achieve efficient interactions with Tehran. The third dimension, network strength shows that APF is a concentrated network, so it is best described by a monocentric constellation structure with regard to both topology and weight. According to the results of network symmetry dimension, the flows of people are symmetrical nationally and annually. In the fifth dimension, one of the reasons that clusters are not formed at this level is the absence of a central city at the median level that can attract significant passenger flows. The expansion of areal flows in long-distance travels does not allow the formation of median cities close to their peripheral cities where are accessible by other terrestrial modes of transportation. Thus, urban hierarchy derived by size-based approach because of observing distinguished dimensions is different from network-based one.