Abstract
Rapid urbanization is occurring throughout China, especially in megacities. Using a land use model to obtain future land use/cover conditions is an essential method to prevent chaotic urban sprawl and imbalanced development. This study utilized historical Landsat images to create land use/cover maps to predict the land use/cover changes of Tianjin city in 2025 and 2035. The cellular automata–Markov (CA–Markov) model was applied in the simulation under three scenarios: the environmental protection scenario (EPS), crop protection scenario (CPS), and spontaneous scenario (SS). The model achieved a kappa value of 86.6% with a figure of merit (FoM) of 12.18% when compared to the empirical land use/cover map in 2015. The results showed that the occupation of built-up areas increased from 29.13% in 2015 to 38.68% (EPS), 36.18% (CPS), and 47.94% (SS) in 2035. In this context, current urbanization would bring unprecedented stress on agricultural resources and forest ecosystems, which could be attenuated by implementing protection policies along with decelerating urban expansion. The findings provide valuable information for urban planners to achieve sustainable development goals.
Highlights
Land use/cover change has widespread impacts on many fields, including city planning, economics, agriculture, land surface temperature, and climate change [1,2,3]
The pink color represents the built-up area that changed from paddy fields from 2005 to 2015 and was primarily located in the east of Tianjin city
environmental protection scenario (EPS), crop protection scenario (CPS), and spontaneous scenario (SS) in our simulation are rooted in the environmental and agricultural concerns raised by urbanization in Tianjin city
Summary
Land use/cover change has widespread impacts on many fields, including city planning, economics, agriculture, land surface temperature, and climate change [1,2,3]. To discover the system and development of urban spatial structures, scenario-based simulations have been widely applied [7,8,9]. Recent works have shown that future urban structure can be predicted through the urban growth model with historical trends from spatiotemporal land use/cover changes under different scenarios [10]. Clarke et al (1997) predicted urban growth in the San Francisco bay area by using a cellular automata model [11]. Clarke and Gaydos (1998) calibrated the cellular automata model and predicted the land use/cover changes in San Francisco and Washington/Baltimore until 2100 [12]. Seto and Fragkias (2005) analyzed the dynamic land use/cover changes between four developing cities in China and illustrated that under the different economic and policy histories, the four cities showed consistent urban growth [14]
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