Complex systems are very often organized under the form of networks where nodes and edges are embedded in space. Transportation and mobility networks, Internet, mobile phone networks, power grids, social and contact networks, neural networks, are all examples where space is relevant and where topology alone does not contain all the information. Characterizing and understanding the structure and the evolution of spatial networks is thus crucial for many different fields ranging from urbanism to epidemiology. An important consequence of space on networks is that there is a cost associated to the length of edges which in turn has dramatic effects on the topological structure of these networks. Understanding the structure, formation and evolution of spatial networks implies then to combine both these informations about the topology and the spatial distribution of nodes. This richness and the ubiquity of these objects is what makes them so fascinating !
Science of Cities
There are always more data about cities and urban systems. This is unprecedented in our history and opens the exciting possibility of a new 'Science of Cities', with the aim of understanding and modeling phenomena taking place in the city. Urban morphology and morphogenesis, activity and residence location choice, urban sprawl and the evolution of urban networks, are just a few of the important processes that are discussed for a long time but that we now hope to understand quantitatively. Now is the time to participate to the first steps towards quantitative urbanism. This effort towards understanding an object as complex as a city is necessarily interdisciplinary: we will need to build up on early studies in quantitative geography and spatial economics, on the knowledge of architects, urbanists and urban sociologists, and on the tools of geomatics together with modeling approaches coming from statistical physics.