Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios

The urban growth boundary (UGB) plays an important role in the regulation of urban sprawl and the conservation of natural ecosystems. The delineation of UGBs is a common strategy in urban planning, especially in metropolitan areas undergoing fast expansion. However, reliable tools for the delineatio...

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Main Authors: Jianxin Yang, Jian Gong, Wenwu Tang, Yang Shen, Chunyan Liu, Jing Gao
Format: Article
Language:English
Published: MDPI AG 2019-11-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/11/21/6159
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spelling doaj-74ab6e23ce51406a9e72944f11ef64672020-11-24T21:56:45ZengMDPI AGSustainability2071-10502019-11-011121615910.3390/su11216159su11216159Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic ScenariosJianxin Yang0Jian Gong1Wenwu Tang2Yang Shen3Chunyan Liu4Jing Gao5Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, ChinaDepartment of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, ChinaCenter for Applied Geographic Information Science, the University of North Carolina at Charlotte, Charlotte, NC 28223, USADepartment of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, ChinaDepartment of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, ChinaDepartment of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, ChinaThe urban growth boundary (UGB) plays an important role in the regulation of urban sprawl and the conservation of natural ecosystems. The delineation of UGBs is a common strategy in urban planning, especially in metropolitan areas undergoing fast expansion. However, reliable tools for the delineation of informed UGBs are still not widely available for planners. In this study, a patch-based cellular automaton (CA) model was applied to build UGBs, in which urban expansions were represented as organic and spontaneous patch growing processes. The proposed CA model enables the modeler to build various spatial and socio-economic scenarios for UGB delineation. Parameters that control the patch size and shape, along with the spatial compactness of an urban growth pattern, were optimized using a genetic algorithm. A random forest model was employed to estimate the probability of urban development. Six scenarios in terms of the demand and the spatial pattern of urban land allocation were constructed to generate UGB alternatives based on the simulated urban land maps from the CA model. Application of the proposed model in Ezhou, China from 2004 to 2030 reveals that the model proposed in this study can help urban planners make informed decisions on the delineation of UGBs under different scenarios.https://www.mdpi.com/2071-1050/11/21/6159urban growth boundarycellular automatapatch growingrandom forestgenetic algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Jianxin Yang
Jian Gong
Wenwu Tang
Yang Shen
Chunyan Liu
Jing Gao
spellingShingle Jianxin Yang
Jian Gong
Wenwu Tang
Yang Shen
Chunyan Liu
Jing Gao
Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
Sustainability
urban growth boundary
cellular automata
patch growing
random forest
genetic algorithm
author_facet Jianxin Yang
Jian Gong
Wenwu Tang
Yang Shen
Chunyan Liu
Jing Gao
author_sort Jianxin Yang
title Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
title_short Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
title_full Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
title_fullStr Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
title_full_unstemmed Delineation of Urban Growth Boundaries Using a Patch-Based Cellular Automata Model under Multiple Spatial and Socio-Economic Scenarios
title_sort delineation of urban growth boundaries using a patch-based cellular automata model under multiple spatial and socio-economic scenarios
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2019-11-01
description The urban growth boundary (UGB) plays an important role in the regulation of urban sprawl and the conservation of natural ecosystems. The delineation of UGBs is a common strategy in urban planning, especially in metropolitan areas undergoing fast expansion. However, reliable tools for the delineation of informed UGBs are still not widely available for planners. In this study, a patch-based cellular automaton (CA) model was applied to build UGBs, in which urban expansions were represented as organic and spontaneous patch growing processes. The proposed CA model enables the modeler to build various spatial and socio-economic scenarios for UGB delineation. Parameters that control the patch size and shape, along with the spatial compactness of an urban growth pattern, were optimized using a genetic algorithm. A random forest model was employed to estimate the probability of urban development. Six scenarios in terms of the demand and the spatial pattern of urban land allocation were constructed to generate UGB alternatives based on the simulated urban land maps from the CA model. Application of the proposed model in Ezhou, China from 2004 to 2030 reveals that the model proposed in this study can help urban planners make informed decisions on the delineation of UGBs under different scenarios.
topic urban growth boundary
cellular automata
patch growing
random forest
genetic algorithm
url https://www.mdpi.com/2071-1050/11/21/6159
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