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Analyzing and modeling the spatiotemporal dynamics of urban expansion: a case study of Hangzhou City, China

    Jie Zhao Affiliation
    ; Wenfu Yang Affiliation
    ; Junhuan Peng Affiliation
    ; Cheng Li Affiliation
    ; Zhen Li Affiliation
    ; Xiaosong Liu Affiliation

Abstract

Understanding the spatiotemporal characteristics of urban expansion is increasingly important for assisting the decision making related to sustainable urban development. By integrating remote sensing (RS), spatial metrics, and the cellular automata (CA) model, this study explored the spatiotemporal dynamics of urban expansion and simulated future scenarios for Hangzhou City, China. The land cover maps (2002, 2008, and 2013) were derived from Landsat images. Moreover, the spatial metrics were applied to characterize the spatial pattern of urban land. The CA model was developed to simulate three scenarios (Business-As-Usual (BAU), Environmental Protection (EP), and Coordination Development (CD)) based on the various strategies. In addition, the scenarios were further evaluated and compared. The results indicated that Hangzhou City has experienced significant urban expansion, and the urban area has increased by 698.59 km2. Meanwhile, the spatial pattern of urban land has become more fragmented and complex. Hangzhou City will face unprecedented pressure on land use efficiency and coordination development if this historical trend continues. The CD scenario was regarded as the optimized scenario for achieving sustainable development. The findings revealed the spatiotemporal characteristics of urban expansion and provide a support for future urban development.

Keyword : urban expansion, spatiotemporal dynamics, remote sensing, spatial patterns, cellular automata model, future scenario

How to Cite
Zhao, J., Yang, W., Peng, J., Li, C., Li, Z., & Liu, X. (2019). Analyzing and modeling the spatiotemporal dynamics of urban expansion: a case study of Hangzhou City, China. Journal of Environmental Engineering and Landscape Management, 27(4), 228-241. https://doi.org/10.3846/jeelm.2019.11561
Published in Issue
Nov 28, 2019
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This work is licensed under a Creative Commons Attribution 4.0 International License.

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