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Cities and Regions as Self-Organizing Systems: Models of Complexity
Abstract
ABSTRACT
This book sets out the basic ideas underlying complexity and the qualitative, spatial evolution that it allows. It describes the conceptual framework of modelling, showing the assumptions involved in developing models which are: a) deterministic, non-linear equations, b) self-organizing dynamical systems, c) evolutionary systems. The paper then describes the mathematical modelling of the spatial self-organization that occurs in regional and urban development as a result of the interaction of economic, demographic and environmental factors. There are chapters on interurban evolution and the emergence of urban hierarchies, with several examples described in detail. It then moves on to intra-urban evolution, and again uses several examples to show how the ideas of complexity allow us to look at emergence and structural change in cities as different economic and residential functions generate interdependent patterns of land-use and of transport flows. It is a model of the multiple decision making processes that go on in the system, concerning short term flows of people, goods and services, involved in commuting and in the supply chain of the economic system, and also the longer term processes that drive migration and the spatial pattern of investment. There are at least two levels of description for the system. The first concerns individuals in small zones attempt to pursue their own goals, and those of their job, and a second, more macroscopic scale, of the urban and regional structure that results. This macroscopic structure, however, fashions the costs and benefits that enter into the individual/local decision making processes, giving rise to a "self-organization" of the system, as the micro and macro levels interact. Rather than predicting exact paths of the system the method is more useful in exploring the different kind of alternatives that are possible, and to perform a strategic analysis of different possible qualitative structures which the system might evolve. Several examples of these models will be briefly discussed: the Brussels Model within Belgium, other national models such as Senegal, the changing urban hierarchy of the USA reflecting migration flows, as well as interventions in intra-urban evolution that serve to demonstrate the potential usefulness of such systems.
... The current understanding of cities as complex adaptive systems (CAS) was already established in the 1990s (Allen 1997, Portugali 1999, Portugal et al. 2012, Batty 2007, deRoo & Silva 2010. Complexity theories form a credible planning paradigm, which can also integrate qualitative and quantitative studies, diverse cultural and social-economic dynamics while considering the spatial and physical urbanity. ...
... It may help the system to renew itself in time of crises (Walker & Salt 2012, Portugali 1999. Planning should acknowledge and allow preferable types of self-organization, hinder the harmful ones (segregation, monofunctional areas) and leave the rest to operate -similarly to the ecosystems in nature (Allen 1997, Partanen 2018). ...
Ubiquitous digitalization in our technology-mediated cities has recently pushed the computation from virtual worlds into the cybernetic sensor-guided cites. AI-driven architecture and planning assumedly make cities efficient, sustainable, and “smart” in a linear, mechanical manner. However, cities are complex adaptive, self-organizing systems evolving through transitions. They are hard to control using any planning tool founded on a rational comprehensive model. Computational, generative methods are established tools in the urban design and planning providing novel perspective for smart city planning. Moreover, the paradigm of complex systems and (universal) self-organization enable crossing of ideas in biological systems, cities, and digital systems. This generates intellectual progress in both philosophical and methods development for e-planning tools. Here, the author introduces an e-planning method applying self-organization of information, capable of reflecting the complex urban dynamics. She concludes by illustrating possible futures in self-organizing technology and planners' roles in it.
... Second, our model only uses landscape datasets as a priori conditions to reproduce the spatial patterns of population. In contrast, in addition to calibration against the population data itself, alternative realistic models incorporate a wide range of external datasets, including inter alia employment levels, economic growth, birth and death rates, bilateral trade flows income and demographic characteristics 15,16,49 . Nevertheless, the natural landscape itself is not included directly in most models, or plays a very limited role. ...
Emergence of cities and road networks have characterised human activity and movement over millennia. However, this anthropogenic infrastructure does not develop in isolation, but is deeply embedded in the natural landscape, which strongly influences the resultant spatial patterns. Nevertheless, the precise impact that landscape has on the location, size and connectivity of cities is a long-standing, unresolved problem. To address this issue, we incorporate high-resolution topographic maps into a Turing-like pattern forming system, in which local reinforcement rules result in co-evolving centres of population and transport networks. Using Italy as a case study, we show that the model constrained solely by topography results in an emergent spatial pattern that is consistent with Zipf’s Law and comparable to the census data. Thus, we infer the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern, that is then modified by higher-level historical, socio-economic or cultural factors.
... Note that certain quantities might also exhibit what is known as an 'inverse cascade', where a transport process from small to large scales occurs, resulting in self-organized large-scale patterns (in the case of two-dimensional turbulence, for instance, vortices tend to develop in clusters and energy is transferred to large scales (Friedrich 2021)). Concepts and methods developed in the context of self-organizing systems have been applied rather extensively in the urban context for example as means to explain how cities evolve and form characteristic spatial patterns (Haken and Portugali 1995;Portugali 1997;Allen 2012). The second important assumption in the context of latter cascade processes is that interactions are assumed to be merely local, occurring from one scale to another. ...
The multitude of interwoven spatial scales and their relevance for urban systems has been of interest to the complexity science of cities since its conception. Today, we are well aware that urban environments are being simultaneously shaped and organised through actions at all levels. However, the fundamental question of how to reveal and quantify the interdependence of processes in between various spatial and temporal scales is less often addressed. Deepening our theoretical understanding of the multiscale spatiotemporal complexity of urban systems demands a transdisciplinary framework and the deployment of novel and advanced mathematical models. This article performs a multiscale analysis of urban structures using a large dataset of rent price values in the Ruhr area, Germany. We argue that, due to their many interacting degrees of freedom, urban systems exhibit similar features as other strongly correlated systems, for example, turbulent flows, notably the occurrence of extreme small-scale fluctuations. This analogy between urban and turbulent systems, which we support by empirical evidence, allows for the modelling of spatial structures on the basis of concepts and methods from turbulence theory. We demonstrate how by identifying the main turbulence-borrowed characteristics of an arbitrary two-dimensional urban field, it can be fully reproduced with a small number of prescribed points. Our findings have theoretical implications in the way we quantify and analyse scales in urban systems, model small-scale urban structures as well as potential policy relevance on understanding the evolution and spatial organisation of cities.
... Urban systems inherently show complexity, comprising numerous individual decisions and interactions (Allen 1997;Portugali 2000;Batty 2005;Tan et al. 2021). Although we stimulate two basic spatial interactions of concentration and integration within UAs, there are still numerous other complex spatial relationships between urban entities worthy of further investigation to improve our method. ...
Urban agglomeration (UA) is a special form of organization in which cities spontaneously participate in urban specialization and cooperative ventures and consequently establish socioeconomic and spatial ties with each other in a given region. Due to the unclear definition of UAs, coupled with an insufficient understanding of the UA formation mechanism, however, an objective and effective method for the spatial identification of UAs on an urban theoretical basis is still lacking. Therefore, this article proposes an approach to spatially and quantitatively identifying UAs based on urban density functions and density–density correlation functions. It is applied to delineate Chinese UAs and investigate their spatial distribution and evolution patterns. Three urban attributes (gross domestic product, population, and urban built-up areas) are measured, and the results show that the relationship between overall spatial correlations and distances approximately follows the negative exponential distribution at the national level. Based on these parameters, it is possible to objectively determine Chinese UAs; the analysis shows a belt-like spatial distribution along the major economic and transportation channels. At the UA level, two spatial patterns, fractional Gaussian noise and fractional Brownian motion, are identified, and there is a general transition from the former to the latter over time.
... Evolutionary thinking has been used for explaining the growth and life of cities for a long time. However, most of this evolutionary analysis has looked at the evolution of systems [25][26][27][28][29][30][31]. This aggregate evolutionary perspective is valid, but it omits to pay sufficient attention to the main mechanism that drives the behaviour of the individuals who build up the system and whose values create the rules for operation of the system. ...
The world is changing under the pressure of environmental and health crises, and in this context, location choice and political choice become of even more poignant importance. Following a Culture-Based Development (CBD) stand, our paper highlights the link between political voting and the cultural and ecological valuation of a place. We start from the premise that the individual utility functions of the urban inhabitant and the urban voter coincide, since they both express the citizen’s satisfaction with the life in a place. We suggest that the unified citizen’s utility function is driven by a trade-off between the availability of virtual and physical spaces for interaction. We expect that this trade-off can lead to dissatisfaction with the place and consequent political discontent if the incumbents’ access to green areas and artistic environment in a place is simultaneously hampered for a long time. Our operational hypothesis is that the political sensitivity of citizens is related to the local availability of green areas (geographies of flowers) and cultural capital endowments (geographies of flower power). Using individual-level data from the WVS from the period close before the pandemic—2017–2020, we test empirically this hypothesis. We use as an outcome of interest the individual propensity to active political behaviour. We explain this propensity through the geographies of flowers (i.e., green areas) and geographies of flower power (i.e., cultural and creative industries). We compare the effects for urban and for rural areas. We find strong dependence of politically proactive behaviour on the geographies of flowers and geographies of flower power, with explicit prominence in urban areas. We find a more pronounced effect of these two geographies on the utility function of incumbent than migrant residents. We also crosscheck empirically the relationship of this CBD mechanism on an aggregate level, using data from the Cultural and Creative Cities Monitor. The findings confirm the Schelling magnifying effect of micro preferences on a macro level.
... The complexity of cities have been addressed in a number of works, including Batty [1], [2], Allen [3], [4], White [5], Portugali [6], Siller [7], etc. For instance, emergent social phenomena have been studied from the perspective of complex systems. ...
The study of cities and their social phenomena have been carried out historically from a “classical focused discipline approach” by areas such as sociology, psychology, anthropology, and urbanism. However, over the past years this has evolved to a multidisciplinary approach with other areas being involved including computational sciences, complex systems, and network science. For instance, an area of interest within this new approach is the study of social fabric in cities. In this work, we study this phenomenon and present a conceptual model to establish the relationship between social fabric and other city phenomena (segregation and encounters). Then by using a proposed three layer abstraction we are able to associate emergent behaviors to social agents and the physical city. Finally, we derive an agent-based model and a study case for the city of Zapopan in Mexico where problems related to the social fabric and social segregation has been historically identified. Based on simulations and empirical evidence we conclude that the perception of the physical city affects the decision-making in mobility and the consequent segregation both related to social fabric.
Cette thèse de géographie analyse les rapports mutuels de production entre les espaces ouverts et la double métropole constituée de Valparaiso et de Santiago du Chili. Devant les fortes pressions urbaines que connaît la région centrale du Chili depuis les années 1970, la permanence de nombreux espaces de superficie différente mais tous encore peu bâtis et aux usages faiblement intensifs à une vingtaine de kilomètres seulement des centres des deux principales agglomérations de ce pays émergent peut en effet paraître paradoxale. Mais le processus de métropolisation a besoin des ressources que représentent les espaces ouverts pour s'alimenter et à l'inverse les espaces ouverts ont besoin de la métropole pour exister à travers ses infrastructures, ses acteurs, ses lois. Dans une démarche de géographie sociale inspirée des travaux d'Henri Lefebvre et en se fondant sur un travail de terrain approfondi autour de trois zones d'étude de la troisième couronne périurbaine de Santiago et de Valparaiso (une littorale, une de moyenne montagne et une dans la dépression centrale), cette recherche développe une méthodologie plurielle permettant de saisir au mieux la triple dimension conçue, vécue et perçue des espaces ouverts en lien avec la métropolisation. Pour marginaux et divers qu'ils soient, les espaces ouverts constituent des enjeux stratégiques pour la métropolisation qui expliquent à la fois les conflits qu'ils créent et qu'ils subissent ainsi que la nécessité pour les autorités de les prendre en compte dans leurs aménagements.
The concept of ‘urban proximity’, which has returned to the limelight with the promotion of the ‘15-min city’ developed and re-proposed for the post-COVID city, cannot simply be associated with the concept of physical proximity to the essential activities of daily life but must concern reinforcement of the social interactions that some places are able to activate better than others. This article focuses on the regeneration of Italian council housing neighbourhoods that lack relational proximity, even when functional proximity has been painstakingly achieved. It describes the fundamental steps of a working method that aims to strengthen the ‘relational performance’ of public spaces, using an interdisciplinary cognitive and assessment process and co-planning with the local community based on the issues of inclusiveness, safety, and climate vulnerability. The experimentation made in an economic and social housing district in a city in Central Italy revealed the need to ‘hook’ the space node onto the node of local capacities and resources, recognizing the local community as the bearer of desires, capacities, and planning will, capable of orienting and prefiguring the complex process of regeneration in the post-COVID city.
Emergence of cities and road networks have characterised human activity and movement over millennia. However, this anthropogenic infrastructure does not develop in isolation, but is deeply embedded in the natural landscape, which strongly influences the resultant spatial patterns. Nevertheless, the precise impact that landscape has on the location, size and connectivity of cities is a long-standing, unresolved problem. To address this issue, we incorporate high-resolution topographic maps into a Turing-like pattern forming system, in which local reinforcement rules result in co-evolving centres of population and transport networks. Using Italy as a case study, we show that the model constrained solely by topography results in an emergent spatial pattern that is consistent with Zipf’s Law and comparable to the census data. Thus, we infer the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern, that is then modified by higher-level historical, socio-economic or cultural factors.
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