Building a science of cities

Abstract

Our understanding of cities is being transformed by new approaches from the complexity sciences (Batty, 2005). Here we review progress, sketching the background beginning with the systems approach which treated systems as being organised from the top down to that which now dominates where systems are treated as evolving from the bottom up. The switch in thinking we describe is best pictured in the transition from thinking of 'cities as machines' to 'cities as organisms'. We first review developments in the dynamics of cities where the notion of equilibrium has been replaced by a veritable potpourri of different types such as chaos, catastrophes, and bifurcations. We then look at patterns and processes that give rise to morphologies that illustrate fractal patterns and self-similarity. We follow this with ideas about networks and interactions that sustain cities through their transport and then we show how such processes of movement and mobility can give rise to the diffusion and segregation of different spatial activities. In all these developments, ideas about scaling that relate size, shape and scale in space and time are evident and we thus sketch three scaling laws based on rank-size, allometry and gravitation that are central to our synthesis of how spatial processes give rise to physical morphologies. We conclude with notions about how these ideas are being embedded into models that have potential applications to inform policy.

Superlinear and sublinear urban scaling in geographical networks modeling cities

“…It has been demonstrated that urban structure possesses a self-similar property [9][10][11][12][13][32][33][34][35]. It is therefore meaningful to explain urban scaling in a fractal-city framework, as allometric scaling in living organisms has been modeled with an idea of the fractal structure of living systems [3].…”

“…Similar to living organisms with the basal metabolic rate of an animal proportional to the 3/4 power of its body mass M [2,3] or the breathing rate (or heart rate) proportional to M −1/4 [4], there are various quantities related to activities or performances of cities such as urban road systems [5], night illuminations [6], and size distribution of buildings [7] that are described by power-law relations [8]. Power-law scaling has also been found in the morphology and evolution of cities and argued from a viewpoint of fractal cities [9][10][11][12][13]. In particular, it has been elucidated that urban indicators quantifying city activities on average scale with the population size in a power-law manner.…”

Un modelo de simulación computacional integrado a SIG para explorar la dinámica de crecimiento de la Zona Metropolitana de la Ciudad de México (1998-2008) / A Computer Simulation Model Integrated into SIG to Explore the Dynamics of Growth of the Metropoli

“…¿Es factible y adecuado utilizar los mismos modelos regionales que analizan el crecimiento entre regiones (estados) del país (por ejemplo los modelos tradicionales de convergencia o divergencia) para estudiar el crecimiento de unidades regionales en el interior de una zona metropolitana como la de la Ciudad de México?, ¿o conviene utilizar enfoques regionales que prioricen otro tipo de mecanismos en el interior de las ciudades? Cabe advertir al respecto que los enfoques teórico regionales recientes que analizan el crecimiento de las ciudades tienden a privilegiar el estudio de la interacción local (espacial) de los componentes microrregionales que conforman una ciudad o zona metropolitana; para poner esto en perspectiva en la polémica sobre modelación regional se ha dejado de analizar las ciudades como sistemas que se organizan de arriba hacia abajo para dar paso a enfoques de abajo hacia arriba (Batty, 2011).…”

U.S. Metropolitan Spatial Structure Evolution: Investigating Spatial Patterns of Employment Growth from 2000 to 2010

“…Or, maybe agglomeration economies are presenting themselves in a new form? In fact, a few studies [15][16][17][18][19][20][21] point out the complexity of the metropolitan spatial structures. They describe the structural complexity as being "beyond polycentricity" [19], a network of "trading places" [20], and "complex variation in density" [21].…”