Abstract
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.
Highlights
The coastal cities are the most densely populated urban settlements and are growing very rapidly
It is necessary for policymakers to use science- and evidence-based scenario modeling to guide future urban development and be able to adequately assess the impact of different strategies, whether the focus is on economic growth or environmental protection [37]
cellular automata (CA)-based urban and land use modeling in Chinese cities have been extensively documented [19,22,28,38,39], few are concerned with predicting possible future scenarios, especially at the current turning point in time concerning urbanization, population growth, economic prosperity, and environmental protection [40]
Summary
The coastal cities are the most densely populated urban settlements and are growing very rapidly. Different strategic directions for coastal city development have been proposed under the somehow conflicting demands for economic growth and environmental protection. It is necessary for policymakers to use science- and evidence-based scenario modeling to guide future urban development and be able to adequately assess the impact of different strategies, whether the focus is on economic growth or environmental protection [37]. CA-based urban and land use modeling in Chinese cities have been extensively documented [19,22,28,38,39], few are concerned with predicting possible future scenarios, especially at the current turning point in time concerning urbanization, population growth, economic prosperity, and environmental protection [40]. This paper calibrates the LogCA model to simulate future urban scenarios of Ningbo, a rapidly evolving coastal city in eastern China. All data were resampled to 60 m spatial resolution except for the SRTM DEM to construct the LogCA model
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