Post-Soviet Street Patterns: Measuring Network Connectivity in the Largest Russian Cities

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Submission Summary
The share of street network in the urban fabric and its connectivity are crucial characteristics of the cities’ spatial structure. Cities with properly developed and well-connected street network tend to be livable and productive. A growing body of research suggests that street network connectivity has the largest effect on walking of all the built environment features and significant effects on transit use and the amount of driving (Ewing and Cervero, 2010). The connectivity concept is widely researched and frequently applied in built-environment studies coming from the developed countries. Therewith, in Russia and other post-Soviet states it is not explored yet. There is no known attempt to examine the street connectivity in the context of post-Soviet spatial structure and to assess this quantitatively. The present study seeks to address the knowledge gap of the street network measures in Russian cities in order to draw attention to the concept of street connectivity and its potential in promoting healthy lifestyles and supporting vibrant environment. Many studies of the post-Soviet (or more broadly, post-socialist) urban structure highlight its peculiarities stemming from specific political and economic conditions under which it formed (Tosics, 2005). In Russian cities the Soviet period of urbanisation became the defining one and in many ways paving the way for future development, since it is during this period that the main city growth took place, both population and territory-wise. As an essential element of urban structure, the street network of the post-Soviet city also has characteristic features that do not correspond to other found in the world. The study includes analysis of such components of street network connectivity as street density, LAS (land allocated to streets), intersection density and the link/node ratio. The three main objectives envisaged by this research - examining the configuration of street network, measuring its specific features and exploring their interrelation - are accomplished by using the GIS tools and statistical methods. The empirical analysis of the street patterns is performed on a sample of the 13 largest Russian cities. The results reveal major dysfunctionalities in the post-Soviet street patterns: all the Russian cities covered in the present study have comparatively low values of all four calculated connectivity components that are crucially important for creating an efficiently laid out street network. The Russian cities have inherited the post-Soviet urban structure with underdeveloped street network. The low motorisation rate typical of the Soviet cities resulted in the extremely low share of street network in the urban fabric: the indicator LAS in the largest Russian cities is characteristic of the cities in the pre-automobile era and 2-3 times lower than in the European and North American cities. The values of other indicators calculated for the Russian cities are also significantly lower in comparison with their 'western' counterparts. This is partially explained by the fact that evaluating transport demand or perspectives of the motorization rate growth during the Soviet period were often substituted by the purely architectural and aesthetic considerations. While the estimations of the road density and connectivity show significant lag of the Russian cities in this area and confirm the necessity of the construction and transformation of the current street networks, city authorities should ensure that the investment in urban transportation infrastructure are made where they are most needed. The cities with post-Soviet street patterns need to invest in adequate and well-laid out street networks, paying special attention to the improvement of the network quality characteristics such as permeability and uniformity and increasing the density and connectivity of the network, especially on the periphery.
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3: Planning for Urban Connectivity
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Senior lecturer
Perm National Research Polytechnic University
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