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Simulation of Land-Use Spatiotemporal Changes under Ecological Quality Constraints: The Case of the Wuhan Urban Agglomeration Area, China, over 2020–2030

Author

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  • Jingye Li

    (Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Jian Gong

    (Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Jean-Michel Guldmann

    (Department of City and Regional Planning, The Ohio State University, Columbus, OH 43210, USA)

  • Jianxin Yang

    (Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China)

  • Zhong Zhang

    (Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China)

Abstract

Human activities coupled with land-use change pose a threat to the regional ecological environment. Therefore, it is essential to determine the future land-use structure and spatial layout for ecological protection and sustainable development. Land use simulations based on traditional scenarios do not fully consider ecological protection, leading to urban sprawl. Timely and dynamic monitoring of ecological status and change is vital to managing and protecting urban ecology and sustainable development. Remote sensing indices, including greenness, humidity, dryness, and heat, are calculated annually. This method compensates for data loss and difficulty in stitching remote sensing ecological indices over large-scale areas and long time-series. Herein, a framework is developed by integrating the four above-mentioned indices for a rapid, large-scale prediction of land use/cover that incorporates the protection of high ecological quality zone (HEQZ) land. The Google Earth Engine (GEE) platform is used to build a comprehensive HEQZ map of the Wuhan Urban Agglomeration Area (WUAA). Two scenarios are considered: Ecological protection (EP) based on HEQZ and natural growth (NG) without spatial ecological constraints. Land use/cover in the WUAA is predicted over 2020–2030, using the patch-generating land use simulation (PLUS) model. The results show that: (1) the HEQZ area covers 21,456 km 2 , accounting for 24% of the WUAA, and is mainly distributed in the Xianning, Huangshi, and Xiantao regions. Construction land has the highest growth rate (5.2%) under the NG scenario. The cropland area decreases by 3.2%, followed by woodlands (0.62%). (2) By delineating the HEQZ, woodlands, rivers, lakes, and wetlands are well protected; construction land displays a downward trend based on the EP scenario with the HEQZ, and the simulated construction land in 2030 is located outside the HEQZ. (3) Image processing based on GEE cloud computing can ameliorate the difficulties of remote sensing data (i.e., missing data, cloudiness, chromatic aberration, and time inconsistency). The results of this study can provide essential scientific guidance for territorial spatial planning under the premise of ecological security.

Suggested Citation

  • Jingye Li & Jian Gong & Jean-Michel Guldmann & Jianxin Yang & Zhong Zhang, 2022. "Simulation of Land-Use Spatiotemporal Changes under Ecological Quality Constraints: The Case of the Wuhan Urban Agglomeration Area, China, over 2020–2030," IJERPH, MDPI, vol. 19(10), pages 1-19, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:6095-:d:817492
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    References listed on IDEAS

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    Cited by:

    1. Mingyang Nan & Jun Chen, 2022. "Research Progress, Hotspots and Trends of Land Use under the Background of Ecological Civilization in China: Visual Analysis Based on the CNKI Database," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    2. Min Wang & Kongtao Qin & Yanhong Jia & Xiaohan Yuan & Shuqi Yang, 2022. "Land Use Transition and Eco-Environmental Effects in Karst Mountain Area Based on Production-Living-Ecological Space: A Case Study of Longlin Multinational Autonomous County, Southwest China," IJERPH, MDPI, vol. 19(13), pages 1-23, June.

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