Calibrating and Validating Cellular Automata Models of Urbanization

Torrens, Paul M.

doi:10.1002/9780470979563.ch23

Cited by 18 publications

(7 citation statements)

References 66 publications

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“…However, most of these studies have not explored spatial heterogeneities in the effects of urbanization on these spatial patterns. Moreover, because urbanization is a complex process, entailing both spatial and temporal variation across different cities [20], its characteristics cannot be fully captured through an analysis of spatial changes confined to one time period. It is necessary to explore quantitative relationships between spatial patterns of urban green areas and urbanization relating to spatiotemporal changes [21].…”

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confidence: 99%

Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective

Zheng

Wang

et al. 2019

Forests

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Urbanization leads to the occupation of green areas, directly contributing to a high level of fragmentation of urban green spaces, which, in turn, results in numerous socioeconomic and environmental problems. Consequently, an understanding of the relationships between patterns of urban green spaces and urbanization processes is essential. Although previous quantitative studies have examined this relationship, they have not included an exploration of spatial heterogeneities in the effects of urbanization on the spatial patterns of urban green areas. We therefore applied a spatiotemporal perspective to examine the above relationship, while considering the wider planning context. First, we quantified the extent of fragmentation of urban green spaces using landscape metrics comprising the largest patch index (LPI) and landscape shape index (LSI). Next, using the calculated spatial metrics and nighttime light data (NTL) for central Beijing for the period 1992–2016, we applied a geographically weighted regression model to assess variations in the spatiotemporal effects of urbanization on the fragmentation of urban green spaces. The results showed that urbanization initially occurred mainly in the northern parts of Beijing, whereas urbanization of southern urban fringe areas occurred after 2008. The reduction in green spaces along with increasing fragmentation and complex spatial patterns are indicative of issues relating to Beijing’s rapid urbanization and planning policies. This study contributes to an understanding of how urbanization influences fragmentation of urban green spaces and offers insights for the planning of urban green spaces from the perspective of promoting sustainability.

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confidence: 99%

Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective

Zheng

Wang

et al. 2019

Forests

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“…In particular areas, where land resource is limited and land use is dynamic, the land uses are more likely to be converted to those with more economic power (Torrens, 2011). For example, due to high profit, new urban development projects often occur on agricultural land, even though the soil is very fertile and productive in the land.…”

Section: Factors Affecting Land Developmentmentioning

confidence: 99%

Critical issues in spatial distribution of public housing estates and their implications on urban renewal in Hong Kong

Zheng

Shen

Wang

et al. 2015

Smart and Sustainable Built Environment

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Public housing in Hong Kong plays an essential role in accommodation supply to people of low income. Access to social resources and rent levels of nearby private residential housing are two critical issues impacting the well-being of residents living in public housing estates. However, previous research has rarely focused on the spatial distribution of public housing estates through exploring these two critical issues. On the other hand, Hong Kong is currently experiencing an urban renewal process. It would be beneficial to consider these critical issues for spatial allocation of public housing in urban renewal decision-making. This paper aims at investigating these two critical issues in relation to the spatial distribution of public housing estates in Kowloon, Hong Kong. Methodology: Seven spatial variables were selected to reflect these critical issues. Spatial analysis in Geographic Information System was conducted to process the data required. Multiple logistic regression was employed to analyse the relationships between the spatial location of public housing estates and the seven selected variables. Findings: Based on the analysis results, several problems as well as geographical advantages of the current location of public housing estates were discovered, which can be valuable references for decision-making by government authorities for public housing development in the future.

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“…In either case, the scientific procedure really involves setting the model, winding it up, and letting it go. This can be something of a scattershot approach and a series of averaging procedures have been developed to, in essence, automate huge volumes of blind trial and error runs (see [92] for an overview). The often-mentioned intent of this experimental approach is to engage in 'generative' science [93], such that simulated cities are built from the bottom-up.…”

Section: Multi-scale Equation-free Computing On Populationmentioning

confidence: 99%

“…They differ from those illustrated in Figure 5 for that reason.) The difference maps shown in Figure 7 are roughly equivalent to standard kappa-statistics used in remote sensing registration [137] and in many urban CA model validation tests for per-pixel comparisons [92]. We have explored other registration and comparison schemes, which are discussed in [16].…”

Section: Plausibility Of Equation-free Sprawlmentioning

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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Calibrating and Validating Cellular Automata Models of Urbanization

Cited by 18 publications

References 66 publications

Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective

Urban Green Space Fragmentation and Urbanization: A Spatiotemporal Perspective

Critical issues in spatial distribution of public housing estates and their implications on urban renewal in Hong Kong

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

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