Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China

Coastal cities in China are challenged by multiple growth paths and strategies related to demands in the housing market, economic growth and eco-system protection. This paper examines the effects of conflicting strategies between economic growth and environmental protection on future urban scenarios...

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Main Authors: Yan Liu, Yongjiu Feng
Format: Article
Language:English
Published: MDPI AG 2016-10-01
Series:Sustainability
Subjects:
Online Access:http://www.mdpi.com/2071-1050/8/10/1045
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spelling doaj-01a4a6e6531e4e62a0b8d297b6a15f512020-11-24T23:47:11ZengMDPI AGSustainability2071-10502016-10-01810104510.3390/su8101045su8101045Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, ChinaYan Liu0Yongjiu Feng1School of Geography, Planning and Environmental Management, The University of Queensland, Brisbane, QLD 4072, AustraliaCollege of Marine Sciences, Shanghai Ocean University, Shanghai 201306, ChinaCoastal cities in China are challenged by multiple growth paths and strategies related to demands in the housing market, economic growth and eco-system protection. This paper examines the effects of conflicting strategies between economic growth and environmental protection on future urban scenarios in Ningbo, China, through logistic-regression-based cellular automata (termed LogCA) modeling. The LogCA model is calibrated based on the observed urban patterns in 1990 and 2015, and applied to simulate four future scenarios in 2040, including (a) the Norm-scenario, a baseline scenario that maintains the 1990–2015 growth rate; (b) the GDP-scenario, a GDP-oriented growth scenario emphasizing the development in city centers and along economic corridors; (c) the Slow-scenario, a slow-growth scenario considering the potential downward trend of the housing market in China; and (d) the Eco-scenario, a slow-growth scenario emphasizing natural conservation and ecosystem protections. The CA parameters of the Norm- and Slow-scenarios are the same as the calibrated parameters, while the parameters of proximities to economic corridors and natural scenery sites were increased by a factor of 3 for the GDP- and Eco-scenarios, respectively. The Norm- and GDP-scenarios predicted 1950 km2 of new growth for the next 25 years, the Slow-scenario predicted 650 km2, and the Eco-scenario predicted less growth than the Slow-scenario. The locations where the newly built-up area will emerge are significantly different under the four scenarios and the Slow- and Eco-scenarios are preferable to achieve long-term sustainability. The scenarios are not only helpful for exploring sustainable urban development options in China, but also serve as a reference for adjusting the urban planning and land policies.http://www.mdpi.com/2071-1050/8/10/1045future scenariourban modelingcellular automataeconomic growthenvironmental protectionNingbo
collection DOAJ
language English
format Article
sources DOAJ
author Yan Liu
Yongjiu Feng
spellingShingle Yan Liu
Yongjiu Feng
Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
Sustainability
future scenario
urban modeling
cellular automata
economic growth
environmental protection
Ningbo
author_facet Yan Liu
Yongjiu Feng
author_sort Yan Liu
title Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
title_short Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
title_full Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
title_fullStr Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
title_full_unstemmed Simulating the Impact of Economic and Environmental Strategies on Future Urban Growth Scenarios in Ningbo, China
title_sort simulating the impact of economic and environmental strategies on future urban growth scenarios in ningbo, china
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2016-10-01
description Coastal cities in China are challenged by multiple growth paths and strategies related to demands in the housing market, economic growth and eco-system protection. This paper examines the effects of conflicting strategies between economic growth and environmental protection on future urban scenarios in Ningbo, China, through logistic-regression-based cellular automata (termed LogCA) modeling. The LogCA model is calibrated based on the observed urban patterns in 1990 and 2015, and applied to simulate four future scenarios in 2040, including (a) the Norm-scenario, a baseline scenario that maintains the 1990–2015 growth rate; (b) the GDP-scenario, a GDP-oriented growth scenario emphasizing the development in city centers and along economic corridors; (c) the Slow-scenario, a slow-growth scenario considering the potential downward trend of the housing market in China; and (d) the Eco-scenario, a slow-growth scenario emphasizing natural conservation and ecosystem protections. The CA parameters of the Norm- and Slow-scenarios are the same as the calibrated parameters, while the parameters of proximities to economic corridors and natural scenery sites were increased by a factor of 3 for the GDP- and Eco-scenarios, respectively. The Norm- and GDP-scenarios predicted 1950 km2 of new growth for the next 25 years, the Slow-scenario predicted 650 km2, and the Eco-scenario predicted less growth than the Slow-scenario. The locations where the newly built-up area will emerge are significantly different under the four scenarios and the Slow- and Eco-scenarios are preferable to achieve long-term sustainability. The scenarios are not only helpful for exploring sustainable urban development options in China, but also serve as a reference for adjusting the urban planning and land policies.
topic future scenario
urban modeling
cellular automata
economic growth
environmental protection
Ningbo
url http://www.mdpi.com/2071-1050/8/10/1045
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