Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai, China

Han, Ji; Hayashi, Yoshitsugu; Cao, Xin; Imura, Hidefumi

doi:10.1016/j.landurbplan.2008.12.002

Cited by 264 publications

(146 citation statements)

References 27 publications

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“…Based on subsystem classifications and factor analysis methods for urban growth dynamics models, created using system dynamics (Xu et al 2015;Han et al 2009), this study further simplifies factors within a subsystem in the model. This is to improve the generality and accuracy of the model.…”

Section: Modellingmentioning

confidence: 99%

“…Usually, within certain environmental capacity, with the industrial development, the factories create more employment opportunities, and then, job requirements attract increase in urban population. Even if there are a few people moving out for some other reasons at the same time, in general, the overall relationship between industry and population will present a positive one, and this has been applied in a number of system dynamics model Han et al 2009;Xu et al 2015;Sterman 1984;Ford and Sterman 1998). However, when the environmental pollution becomes so excessive that urban liveability is reduced, increases in the total population (TP) will cease, although this assertion may not be true in all places by considering those who do not have an option to move out.…”

Section: Modellingmentioning

confidence: 99%

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Comparison of Ecological Risk among Different Urban Patterns Based on System Dynamics Modeling of Urban Development

Kang

2017

J. Urban Plann. Dev.

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Abstract:In this study an urban development model has been developed based on system dynamics, in order to compare four urban layout patterns, in terms of their effects on landscape ecology risk and environmental pollution. The four patterns are: centralised urban model, green corridor urban model, decentralised urban model (satellite city model) and resource-based city model. Landscape ecology risk assessments based on simulation results show that: the decentralised urban model is superior to the centralised urban model in terms of long-term landscape ecological development and environmental protection. In the meantime, the relationships between the patch spacing and evaluation index have been revealed.

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Section: Modellingmentioning

confidence: 99%

Section: Modellingmentioning

confidence: 99%

Comparison of Ecological Risk among Different Urban Patterns Based on System Dynamics Modeling of Urban Development

Kang

2017

J. Urban Plann. Dev.

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“…Natural and socioeconomic variables may be seen as spatio-temporal drivers especially when related to urban systems (Han et al, 2009). Sensitivity maps based on variables of urban change have a scale of propensity for the existence of built-up environments, and are relevant tools to assess the dynamics of land-use change over a given period.…”

Section: Multi-scenar Io Modelling Of the Algar Vementioning

confidence: 99%

A multi-scenario forecast of urban change: A study on urban growth in the Algarve

Vaz

Nijkamp

Paìnho

et al. 2012

Landscape and Urban Planning

138

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“…Landscape fragmentation, surface sealing, increased run-off, soil erosion as well as biodiversity decline are some of the indirect results of urban growth (Ceccarelli et al 2014). Also, urban & Sassan Mohammady Sassanmohammady@yahoo.com growth has caused the deterioration of urban environment, including increased air and water pollution, reduction of vegetation cover and rising level of diseases (Hana et al 2009). If this unavoidable phenomenon is leaved unchecked, then it causes unplanned urbanization.…”

Section: Introductionmentioning

confidence: 99%

Urban sprawl assessment and modeling using landsat images and GIS

Mohammady

Delavar

2016

Model. Earth Syst. Environ.

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Nowadays, urban sprawl phenomenon have been seen in many of cities in the developing and developed countries. Urban sprawl is considered as a particular kind of urban growth which comes up with a lot of negative effects. Thus, monitoring, analyzing and modeling of this phenomenon seem to be unavoidable. This paper assess urban sprawl in Tehran Metropolis as the capital of Iran and models urban sprawl in this mega city utilizing artificial neural networks and adaptive neuro-based fuzzy inference system methods with remote sensing data and geospatial information systems spatial analyses and modeling capabilities to simulate Tehran urban growth. The results confirm that this city has experienced sprawl and sprawl has an increasing rate. Three Landsat imageries from TM and ETM? sensors taken in 1988, 1999 and 2010 and seven predictor variables include distance to road, distance to green space, slope, elevation, distance to fault, distance to developed area and number of urban cells in 3 by 3 neighborhoods have been used for urban sprawl assessment and modeling. Relative operating characteristics (ROC) and sensitivity analyses have been used to evaluate simulation results. In this research, two evaluation steps have been implemented using ROC and on the both of them, ANFIS presented the best performance vs two different proposed ANN structures.

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Application of an integrated system dynamics and cellular automata model for urban growth assessment: A case study of Shanghai, China

Cited by 264 publications

References 27 publications

Comparison of Ecological Risk among Different Urban Patterns Based on System Dynamics Modeling of Urban Development

Comparison of Ecological Risk among Different Urban Patterns Based on System Dynamics Modeling of Urban Development

A multi-scenario forecast of urban change: A study on urban growth in the Algarve

Urban sprawl assessment and modeling using landsat images and GIS

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