Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method

•UGBs under various scenarios can be generated by integrating CA with an SD model.•Macro policy (e.g., future demand of urban area) and spatial policy are considered.•Plausible UGBs can be effectively delineated by using a morphological method. Urban growth boundaries (UGBs) have been commonly regar...

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Published inLandscape and urban planning Vol. 177; pp. 47 - 63
Main Authors Liang, Xun, Liu, Xiaoping, Li, Xia, Chen, Yimin, Tian, He, Yao, Yao
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.09.2018
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Abstract •UGBs under various scenarios can be generated by integrating CA with an SD model.•Macro policy (e.g., future demand of urban area) and spatial policy are considered.•Plausible UGBs can be effectively delineated by using a morphological method. Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for controlling urban sprawl. There is a need to create models that can establish plausible UGBs for fast growing regions. Previous methods have merely focused on establishing a single UGB scenario over different time intervals, but rarely considered the influences of macro policy (e.g., future urban demand) and spatial policy (e.g., master plan) for regional planning. However, the spatial patterns of urban expansion are significantly affected by regional planning. In this paper, a CA-based method called the future land use simulation (FLUS) is applied to the delineation of UGBs. We argue that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios. The system dynamics model (SD) and cellular automaton model (CA) were interactively coupled in the FLUS model during the projection period. The top-down SD is used to project scenarios that relate to macro policy and socioeconomic status, and the bottom-up CA accounts for urban growth simulations under the influence of different driving factors and spatial planning policies. A morphological technology based on erosion and dilation is further proposed to generate the UGBs from the FLUS model’s simulated urban forms. The proposed UGB-FLUS model was applied to the establishment of UGBs in the Pearl River Delta region (PRD) from 2020 to 2050. The results demonstrate that the method can support urban planning by generating feasible patterns for UGBs under different planning scenarios.
AbstractList Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for controlling urban sprawl. There is a need to create models that can establish plausible UGBs for fast growing regions. Previous methods have merely focused on establishing a single UGB scenario over different time intervals, but rarely considered the influences of macro policy (e.g., future urban demand) and spatial policy (e.g., master plan) for regional planning. However, the spatial patterns of urban expansion are significantly affected by regional planning. In this paper, a CA-based method called the future land use simulation (FLUS) is applied to the delineation of UGBs. We argue that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios. The system dynamics model (SD) and cellular automaton model (CA) were interactively coupled in the FLUS model during the projection period. The top-down SD is used to project scenarios that relate to macro policy and socioeconomic status, and the bottom-up CA accounts for urban growth simulations under the influence of different driving factors and spatial planning policies. A morphological technology based on erosion and dilation is further proposed to generate the UGBs from the FLUS model’s simulated urban forms. The proposed UGB-FLUS model was applied to the establishment of UGBs in the Pearl River Delta region (PRD) from 2020 to 2050. The results demonstrate that the method can support urban planning by generating feasible patterns for UGBs under different planning scenarios.
•UGBs under various scenarios can be generated by integrating CA with an SD model.•Macro policy (e.g., future demand of urban area) and spatial policy are considered.•Plausible UGBs can be effectively delineated by using a morphological method. Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for controlling urban sprawl. There is a need to create models that can establish plausible UGBs for fast growing regions. Previous methods have merely focused on establishing a single UGB scenario over different time intervals, but rarely considered the influences of macro policy (e.g., future urban demand) and spatial policy (e.g., master plan) for regional planning. However, the spatial patterns of urban expansion are significantly affected by regional planning. In this paper, a CA-based method called the future land use simulation (FLUS) is applied to the delineation of UGBs. We argue that the delineation needs to integrate the top-down approach with CA for projecting complex land use changes under designed scenarios. The system dynamics model (SD) and cellular automaton model (CA) were interactively coupled in the FLUS model during the projection period. The top-down SD is used to project scenarios that relate to macro policy and socioeconomic status, and the bottom-up CA accounts for urban growth simulations under the influence of different driving factors and spatial planning policies. A morphological technology based on erosion and dilation is further proposed to generate the UGBs from the FLUS model’s simulated urban forms. The proposed UGB-FLUS model was applied to the establishment of UGBs in the Pearl River Delta region (PRD) from 2020 to 2050. The results demonstrate that the method can support urban planning by generating feasible patterns for UGBs under different planning scenarios.
Author Tian, He
Liang, Xun
Li, Xia
Chen, Yimin
Yao, Yao
Liu, Xiaoping
Author_xml – sequence: 1
  givenname: Xun
  surname: Liang
  fullname: Liang, Xun
  email: liangxunnice@foxmail.com
  organization: Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China
– sequence: 2
  givenname: Xiaoping
  surname: Liu
  fullname: Liu, Xiaoping
  email: liuxp3@mail.sysu.edu.cn
  organization: Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China
– sequence: 3
  givenname: Xia
  surname: Li
  fullname: Li, Xia
  email: lixia@mail.sysu.edu.cn
  organization: Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China
– sequence: 4
  givenname: Yimin
  surname: Chen
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  organization: Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China
– sequence: 5
  givenname: He
  surname: Tian
  fullname: Tian, He
  organization: Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, PR China
– sequence: 6
  givenname: Yao
  surname: Yao
  fullname: Yao, Yao
  organization: School of Information Engineering, China University of Geosciences, Wuhan, Hubei 430074, PR China
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UGB-FLUS model
Cellular automata
Urban growth boundaries (UGBs)
Planning scenarios
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Snippet •UGBs under various scenarios can be generated by integrating CA with an SD model.•Macro policy (e.g., future demand of urban area) and spatial policy are...
Urban growth boundaries (UGBs) have been commonly regarded as a useful tool for controlling urban sprawl. There is a need to create models that can establish...
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SubjectTerms Cellular automata
dynamic models
Erosion and dilation
issues and policy
land use change
Planning scenarios
regional planning
river deltas
rivers
socioeconomic status
UGB-FLUS model
Urban growth boundaries (UGBs)
urban planning
urbanization
Title Delineating multi-scenario urban growth boundaries with a CA-based FLUS model and morphological method
URI https://dx.doi.org/10.1016/j.landurbplan.2018.04.016
https://www.proquest.com/docview/2101316455
Volume 177
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