Urban Growth Processes Joining Cellular Automata and Multiagent Systems. Part 1: Theory and Models

Vancheri, Alberto; Giordano, Paolo; Andrey, Denise; Albeverio, Sergio

doi:10.1068/b31080a

Cited by 17 publications

(8 citation statements)

References 26 publications

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“…Discussion of self-organisation took many forms from models elucidating the mechanisms of urban self-organisation (Daffertshofer, 2001), the use of techniques to look for indicators of self-organisation (Chen and Zhou, 2006;Porta et al, 2006), unplanned, local initiatives such as guerilla gardening groups (Ache and Ferowitz, 2012;, techniques for incorporating self-organisation into the planning process (Rauws and de Roo, 2016), to a cursory mention of self-organisation at some point in the article, for example as a potential area of interest for future research (Janssen-Jansen, 2013), or an intrinsic aspect of urban complex systems (Vancheri et al, 2008).…”

Section: Resultsmentioning

confidence: 99%

Biotic analogies for self-organising cities

Narraway

Davis²,

Lowell³

et al. 2019

Environment and Planning B: Urban Analytics and City Science

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Nature has inspired generations of urban designers and planners in pursuit of harmonious and functional built environments. Research regarding self-organisation has encouraged urbanists to consider the role of bottom-up approaches in generating urban order. However, the extent to which self-organisation-inspired approaches draw directly from nature is not always clear. Here, we examined the biological basis of urban research, focusing on self-organisation. We conducted a systematic literature search of self-organisation in urban design and biology, mapped the relationship between key biological terms across the two fields and assessed the quality and validity of biological comparisons in the urban design literature. Finding deep inconsistencies in the mapping of central terms between the two fields, a preponderance for cross-level analogies and comparisons that spanned molecules to ecosystems, we developed a biotic framework to visualise the analogical space and elucidate areas where new inspiration may be sought.

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Section: Resultsmentioning

confidence: 99%

Biotic analogies for self-organising cities

Narraway

Davis²,

Lowell³

et al. 2019

Environment and Planning B: Urban Analytics and City Science

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“…Modelling methods that have been used in the urban planning field include agent based (O'Sullivan and Haklay, 2000;Gero and Sarkar, 2005;Jordan et al, 2012) and cellular automata (Barredo et al, 2003;Fang et al, 2005;Waddell, 2002;He et al, 2008;Santé et al, 2010) as well as combinations of the two (Batty, 2005;Torrens and Benenson, 2005). Other combined models of urban growth processes include cellular automata (CA) with fuzzy functions (Vancheri et al, 2008) and CA with logistic functions (Poelmans and Van Rompaey, 2010). Mathematical programming has been used effectively (e.g.…”

Section: Selection Of the Modelling Methodsmentioning

confidence: 99%

Achieving Residential Connectivity and Density Goals with Computer-Generated Plans in a Greenfield Area

Sun

Qiu

Taplin

2014

Environ Plann B Plann Des

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An algorithm has been developed to generate, without external intervention, a road and land use plan for a regular or irregular site. It starts from an 'embryo' and grows a plan rather than trying to modify an initial solution. The basic modules are universal building blocks which change and adapt in a guided search with random selection of branching points followed by operations to add links or make connections. Deletion operators guide development by removing branches which do not improve the outcome. A hypothetical application, maximizing combined everyoneto-everyone connectivity and dwelling density, has evolved a highly interconnected street plan. However no step is specific to the example; the operators will grow a road and land use network under various specifications and constraints guided by an objective function. Making the process applicable to an actual development might require more constraints and certainly an enlarged objective function. Cost and other goals can be included so long as each goal is in some way functionally related to every change in the plan made by the search procedure. seemingly contradictory and imperfect urban form as suburbia can, and, indeed, does compose an integral part of contemporary capitalism.' Lovejoy et al (2010) note that a suburb often lacks the grid-like street pattern, mix of residential and commercial land uses and distinct centres usually associated with 'traditional' neighborhoods. Nevertheless, their rigorous quantitative assessment leads to the conclusion that '...some of the main differences between suburban and traditional neighborhood designs do not make much of a difference for how satisfied residents are with their neighborhoods, in either neighborhood type.' When comparing suburban neighborhoods in Houston, Rogers et al (2009) found that '...residents in ecologically designed neighborhoods have an enhanced sense of community, at

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“…In the government and public participation module, the government and the public participate in urban modeling by expressing their opinions on the street state transition (Vancheri et al, 2008). Two types of agent are embodied in our proposed urban modeling for streets: the government agent at an upper level and the public agent at a lower level.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Urban modeling for streets using vector cellular automata: Framework and its application in Beijing

Jia

Chen

et al. 2020

Environment and Planning B: Urban Analytics and City Science

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Zones, cells, and parcels have long been regarded as the main units of analysis in urban modeling. However, only limited attention has been paid to street-level urban modeling. The emergence of fine-scale open and new data available from various sources has created substantial opportunities for research on urban modeling at the street level, particularly for modeling the spatiotemporal process of urban phenomena. In this paper, the street is adopted as the spatial unit of an urban model, and a conceptual framework for such modeling based on cellular automata is proposed. The validity of the proposed framework is verified by an empirical application to the urban space within the Fifth Ring Road in Beijing from 2014 to 2018. The results show that the density of points of interest simulated by the cellular automata model for 2018 is basically consistent with the actual distribution according to direct observation, and there is no significant difference in the proportion of high, medium, and low points of interest density streets between different ring roads. In addition, the deviation rate and Kappa index are 0.1171 and 0.97, respectively, indicating the proposed model can replicate historical patterns well and predict the transition of points of interest density at the street level. Subsequently, we considered three scenarios, adopting 2018 as the base year and using the proposed model to simulate the distribution of points of interest density in 2022 and the changes in points of interest density from 2018 to 2022. The conceptual framework and empirical application also provide support for urban planning and design based on the integration of linear public space and big data.

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Urban Growth Processes Joining Cellular Automata and Multiagent Systems. Part 1: Theory and Models

Cited by 17 publications

References 26 publications

Biotic analogies for self-organising cities

Biotic analogies for self-organising cities

Achieving Residential Connectivity and Density Goals with Computer-Generated Plans in a Greenfield Area

Urban modeling for streets using vector cellular automata: Framework and its application in Beijing

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