Geosimulation model using geographic automata for simulating land-use patterns in urban partitions

Shen, Zhenjiang; Kawakami, Mitsuhiko; Kawamura, Ippei

doi:10.1068/b34148t

Cited by 28 publications

(11 citation statements)

References 12 publications

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“…However, the conventional raster-based CA models are sensitive to the size of the grid cells and how they are configured, and thus have limited power to simulate the real world, which has more complex land use layouts and street networks. Vector-based CA models were later developed to simulate the process of urban change with irregular polygons as cells to represent more realistic urban phenomenon (Shen et al, 2009;Stevens and Dragi cevi c, 2007). However, both raster and vector CA models have limitations in incorporating human decision behaviors (Arsanjani et al, 2013).…”

Section: Typical Urban Modelsmentioning

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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Section: Typical Urban Modelsmentioning

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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“…In the geographical sciences, a main motivation is to energize our theories, observations, hypotheses, and data over space and time and many models are beginning to focus on explicitly spatial processes (as well as spatialized economic, social, environmental, and so on processes) to achieve this [139]. In part, the field of geosimulation [39] and tool-kits such as geographic automata has been developed and advanced in response to this impulse [140][141][142][143][144].…”

Section: Discussionmentioning

confidence: 99%

Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

Torrens

Kevrekidis

Ghanem

et al. 2013

Entropy

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Abstract:Reconciling competing desires to build urban models that can be simple and complicated is something of a grand challenge for urban simulation. It also prompts difficulties in many urban policy situations, such as urban sprawl, where simple, actionable ideas may need to be considered in the context of the messily complex and complicated urban processes and phenomena that work within cities. In this paper, we present a novel architecture for achieving both simple and complicated realizations of urban sprawl in simulation. Fine-scale simulations of sprawl geography are run using geographic automata to represent the geographical drivers of sprawl in intricate detail and over fine resolutions of space and time. We use Equation-Free computing to deploy population as a coarse observable of sprawl, which can be leveraged to run automata-based models as short-burst experiments within a meta-simulation framework.

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“…In this context, then, they serve as ideal base ingredients for building common and extensible data and process model functionality for VGE elements. The parameterization of GA is well-discussed elsewhere (Benenson and Torrens 2003;Shen, Kawakami, and Kawamura 2009;Torrens 2007b;Torrens and Benenson 2005), but I introduce some basic notation for them below, before describing how they function as objects for slipstreaming in simulation.…”

Section: Geographic Automata Building-blocks and The Polyspatiality Tmentioning

confidence: 99%

“…State information is the main fuel source for all automata (Shannon 1948;Turing 1950), and GA are no exception in this regard. Recall that our GA rely on states generally, but also on location as a specific form of state, from which they piece-together space-time phenomena and processes.…”

Section: Acquiring Geographic Informationmentioning

confidence: 99%

Slipstreaming human geosimulation in virtual geographic environments

Torrens

2015

Annals of GIS

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Virtual geographic environments (VGEs) have long enjoyed significant synergy with geosimulation as a visual medium for model results, but more could be done to fashion two-way harmony between them, with the potential benefit that geosimulation could usefully serve as a process engine for VGEs and as a unifying scaffold for connecting VGEs to other systems. In this article, I argue for three promising bridges between geosimulation and VGEs. First, geosimulation could be relied upon in introducing synthetic human characters in VGEs to augment the significant physical detail that VGEs currently provide with ambient behavioural processes. Second, building blocks of geosimulation, based around polyspatial automata, could help to resolve long-standing requirements for common data and process models for VGEs. Finally, slipstreaming of geographic information across geosimulation and VGE scaffolds could be useful in reconciling diverse and many-model processes, with disparate form and scales, in a cohesive pipeline. Together, these three variations can facilitate the exchange of diverse model objects, processes, and information between geosimulation and VGEs, greatly expanding their interoperability and explorative reach. I demonstrate the usefulness of these developments with example scenarios that focus on urban mobilities, urban complexity, and urban failures in both ordinary and extraordinary scenarios. Applications to urban phenomena, in particular, may have particular value as we approach new vantages on cities supported by big data, big awareness, and immersive media that greatly expand the volume, breadth, and depth of questioning that our VGEs may be called on to support.

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Geosimulation model using geographic automata for simulating land-use patterns in urban partitions

Cited by 28 publications

References 12 publications

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

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

Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

Slipstreaming human geosimulation in virtual geographic environments

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