Unraveling fundamental network features of complex urban transportation systems

Transportation networks represent one of the key structural elements behind the functional properties of a large number of natural and man-made systems. In urban systems, they represent some of the arteries that regulate human mobility, especially in commuting scenarios. Moreover, they are by essence linked to the growth and development of urban areas, both in the exploitation of the urban space and its efficiency. Understanding the interplay between networks and urban exploitation represents a step forward in the study of cities and urban areas as complex systems, which in turn can be helpful for decision makers and urban planners. In this thesis focus on urban transportation networks by first approaching the problem by framing the system in the field as spatial networks, in particular we study subway systems as they exhibit complex spatial features and we expose their interplay with urban land use features. We first provide a general review of the recent  literature of cities as complex systems and we frame the problem of metro systems in the context of spatial networks. As a first aim of this work, to reproduce some key results presented in literature. To this aim, datasets for these networks are essential, although limited urban networks datasets are available and not longitudinal to several cities. While several sources are available for public transportation information, these are often sparse, decentralized and specific of local providers. As a first task in this work, we describe the process of processing and mapping these data into a unified data structures of spatial weighted networks for a set of cities we have identified. Especially, we have analyzed the decomposition of subway systems in a combination of dense core structures with loops and branches in periphery.    Then, we realize there might be a pitfall in the definition of the center used until there in the literature – we propose a novel definition of a functional center and show its comparative benefits relative to the previous definition. We introduce also a set of novel metrics describing some of the network’s spatial properties and providing novel perspective to the analysis of these systems. This definition carves a more precise decomposition in a core and branch structure and yields clearer structural properties of the network,  initimately related to the efficiency of the network structure. Finally, we show that this definition coincides with the spatial maximum of amenities in various urban areas on which we focused.