Spatiotemporal dynamics of urban forest conversion through model urbanization in Shenzhen, China

Abstract

In southern coastal China, Shenzhen Special Economic Zone (SEZ) was established as a model city by the government of mainland China in 1979 to demonstrate the competitive edge over Hong Kong across the straight. In less than three decades, Shenzhen has become a symbolic model city and changed from an agriculture-dominated landscape to a modern industrialization urban setting. The remote sensing approach for exploring historical land-cover change and landscape conversion paralleling a functional zone-based grid cellular analysis were used to examine the spatial–temporal changes of urban forest in Shenzhen from 1973 to 2009. Urban forest cover has been widely believed to decrease linearly and inversely to urban land regardless of spatial and temporal drivers, while our study demonstrated, in fact, that it presented as the nonlinear change with the development of the city and the transformations of underlying human demands and government's policy. Meanwhile, forest conversions over time also showed the spatial heterogeneity, which was caused by the discrepancy of urbanization range or intensity and related to both the geographical settings and socio-economic zonings of land use. In conclusion, this study revealed urbanization and its underlying biophysical and socio-economic factors could bring about the spatiotemporal dynamics of urban forest conversion (loss or gain), which affected ecosystem health and sustainable development, and reflected on the conservation management and the balance check on policy impacts on a society.

Acknowledgements

We thank Nan Lu, Haiqiang Guo, Burkhard Wilske, Ranjeet John, Jessica Schaefer and Jianye Xu in the LEES Laboratory at the University of Toledo; Luo Guo, Yantun Song, Zhi Chen and Jie Wu in the 3S Laboratory of Sun Yat-sen University; Nan Li from Fairylake Botanical Garden of Shenzhen; and the anonymous reviewers for their help in the research or their constructive suggestions on revising the earlier manuscript. We also thank Dr. Luo Guo for providing some remote sensing data. This study was supported by the City Management Department of Shenzhen, the Zhang-Hongda Science Foundation of Sun Yat-sen University, the University of Toledo and the China Scholarship Council.

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