The concept of urban intensity and China's townization policy: Cases from Zhejiang Province

Guan, ChengHe; Rowe, Peter G.

doi:10.1016/j.cities.2016.03.012

Cited by 30 publications

(13 citation statements)

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“…Local autocorrelation analysis and the polarization index were complementary and measured changes in spatial agglomeration or dispersion that indicated different levels of urban development. Moran’s I and LISA agglomeration are commonly used indicators of spatial autocorrelation [ 27 , 28 , 29 ]. The polarization index quantified the degree of polarization of regional development, but it could not indicate the specific regions of polarization in space.…”

Section: Methodsmentioning

confidence: 99%

“…Previous studies have revealed the internal correlation of urban development within China using comprehensive quantitative methods, e.g., the spatial econometric regression model, entropy method, Moore’s structural change index, and Moran’s I index [ 26 ]. Most studies tend to measure the level of urbanization by calculating the Moran’s I index [ 27 , 28 , 29 ]; however, the Tsui–Wang (TW) index has been applied to analyze the overall polarization trend in related research [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

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Spatial Association of Urbanization in the Yangtze River Delta, China

Wei

Liu

Deng

et al. 2020

IJERPH

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China is urbanizing rapidly, but current research into the spatiotemporal characteristics of urbanization often ignores the spatial and evolutionary associations of cities. Using the theory of spatial polarization and diffusion, together with a systematic analysis method, this study examined the spatial development process of urbanization in the Yangtze River Delta (YRD) region of China during 1995–2015. Results showed clear patterns in the scale and hierarchy of regional urbanization. Shanghai ranked first as the regional growth pole, while Nanjing, Hangzhou, and Suzhou ranked second. The spatial linkage index of urbanization showed that 10 cities (including Shanghai, Suzhou, and Hangzhou) constituted the densest spatial linkage network. The diffused area often became spatially polarized before the polarization then weakened as a new diffusion stage developed. The study also revealed that the spatial correlation urbanization differences in the YRD generally decreased. The polarization index revealed increasing spatial integration and correlation of urbanization in the YRD. This study proved that each city had a different spatial role in relation to other cities during different stages of development. Investigation of the driving mechanism of regional urbanization indicated that industrial modernization and relocation within the region provided the main endogenous driving force for the formation of spatial polarization or diffusion. Our research provides important scientific support for regional development planning. Furthermore, our analysis of the impact of spatial correlation within cities or a region could provide an important reference in relation to the regional environment and public health.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial Association of Urbanization in the Yangtze River Delta, China

Wei

Liu

Deng

et al. 2020

IJERPH

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“…Another useful indicator is ‘urban intensity’ measured by four related concepts: compactness, diversity, density, and connectivity. Together they lead to a single idea when considering spatial distributions potentially in a virtuous manner with regard to resource consumption, economic opportunity, social integration, and environmental performance (Guan and Rowe, 2016). Another group of scholars focused on simulation and projections (Batty and Xie, 1994; Liu, 2009; Samat et al., 2011).…”

Section: Data Collection and Processingmentioning

confidence: 99%

“…The modification of parameters did not change how the principles of the Cellular Automata model operated. However, they did provide opportunities to reflect the influences of certain urban policies on the outcome of the urban land growth patterns predictions (Guan and Rowe, 2016). The scenario-based Cellular Automata model used the formula …”

Section: Modeling Modifications and Change Of Parametersmentioning

confidence: 99%

In pursuit of a well-balanced network of cities and towns: A case study of the Changjiang Delta Region in China

Guan

Rowe

2017

Environment and Planning B: Urban Analytics and City Science

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Development of urban networks of cities and towns has received attention including discussions of tensions between population concentrations and overlaps with environmentally sensitive and disaster-prone areas. Moreover, certain development in broad regions of China, such as its deltas, has become a subject of debate. Contrary to some assumptions, this development within places like the Changjiang Delta (also known as the Yangtze River Delta) has proceeded in a relatively incremental manner. However, at this juncture, controlled development of larger cities, like Shanghai, has shifted to more conventional urbanization pathways forward involving larger city expansions. Nevertheless, further urban growth management appears to depend on development and maintenance of a well-balanced network of large, medium, and small-scaled cities and towns. An important aspect of this development involves definition of the Changjiang Delta region itself, and in particular, alongside its likely further economic performance. To these ends, a scenario-based Cellular Automata model of spatial distribution is deployed, reflecting separate thematic projections. A baseline for economic performance is developed, incorporating measures of fixed-asset investment in urban service, revenue from urban maintenance, and Gross Domestic Product. Revelation of a well-performing network involves spatial distribution of development at various scales, and in various concentrations within the region, moreover, location of this development, largely perpendicular to well-travelled corridors, appears as a preferable outcome, contrary to earlier depictions along the major transportation corridors.

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“…Urban analysis performed by urban planners and architects is key to achieve the objectives set for a given urban project (Ayeni, 2017), as it helps to understand the inherent dynamics of places. Due to the multifaceted reality of urbanisation, urban analyses based on traditional static, monocriteria indicators are insufficient and researchers are turning to dynamic notions such as urban intensity (Fouchier, 1997;Da Cunha and Kaiser, 2009;Sevtsuk et al, 2013;Guan and Rowe, 2016;Chadee and Stoute, 2018;Stonor, 2019). This notion includes a set of characteristics which contribute to the understanding of complex urban systems.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Urban Intensity Through a City Information Model – Intermediate Results From an Action Research Project

Deprêtre

Jacquinod

2021

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Urban planning is a very complex task, especially considering the many challenges it faces, including an increasing need for housing in response to demographic growth and a need to limit abusive land artificialisation. As part of an interdisciplinary action-research project focused on experimenting with various uses of an existing City Information Model (CIM) for urban design, we are developing a new indicator to characterize urban intensity and a method to quantify it through the City Information Model (CIM) of a French eco-district. Our project is ongoing, and, in this paper, we present intermediate results on the potential of this CIM to support the automated quantification of our urban intensity indicator. We also describe the solutions currently implemented so that our experimental CIM can provide the necessary information for a more complete and automated urban intensity analysis. Finally, we shed light on key issues regarding the use of CIM, specifically CIM made up of various BIM models (of buildings lots and public spaces) for urban analysis at the district scale during the design phase. These issues include the need to generalize BIM entities and to manage property sets and nomenclatures to allow automation of analyses at the district scale, as long as there is no BIM+ data model allowing for urban analysis.

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The concept of urban intensity and China's townization policy: Cases from Zhejiang Province

Cited by 30 publications

References 8 publications

Spatial Association of Urbanization in the Yangtze River Delta, China

Spatial Association of Urbanization in the Yangtze River Delta, China

In pursuit of a well-balanced network of cities and towns: A case study of the Changjiang Delta Region in China

Evaluating Urban Intensity Through a City Information Model – Intermediate Results From an Action Research Project

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