Ecological security and structural optimization of land space in the Pearl River Delta Urban Agglomeration: an approach based on the footprint family

文献类型： 外文期刊

第一作者： Huang, Cong

作者： Huang, Cong;Yin, Hanyu;Cao, Wei;Tan, Wenfang;Chen, Jiali;Xiao, Rui;Liu, Jun;Zhang, Zhonghao;Liu, Lumeng;Fei, Xufeng;Xu, Chen;Li, Kai

作者机构：

关键词： Land space; Footprint family; Ecological security; Land spatial planning

期刊名称：ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY （ 影响因子：4.2； 五年影响因子：4.5 ）

ISSN： 1387-585X

年卷期： 2025 年

页码：

收录情况： SCI

摘要： Land space plays a critical role in economic and ecological sustainability, particularly in densely populated and rapidly urbanizing regions like the Pearl River Delta Urban Agglomeration (PRDUA), where intensive human activities and urban sprawl amplify ecological pressures. The region faces severe ecological risks including water scarcity, carbon emissions, and ecosystem fragmentation, driven by industrial expansion and population growth. To address these issues, we assess ecological security and optimize land spatial patterns in PRDUA using an integrated framework of multi-objective optimization and PLUS model based on footprint family analysis. Specifically, we quantify farmland, water, and carbon footprints to assess ecological carrying capacity, then employ the PLUS model to simulate sustainable spatial configurations. Our findings reveal that in 2020, per capita water use ecological footprint was the highest among PRDUA cities, and most highly urbanized cities are also facing significant water pollution and carbon emission pressures. Dongguan, Foshan, and Guangzhou facing the greatest ecological risks, their ecological security index (ESI) fell below 3.6, indicating high environmental vulnerability. Based on these results, we propose a 3% urban expansion and a 624.77 km2 increase in agricultural land by 2025 to promote ecological sustainability. This study provides key policy insights, urging a balance between urban growth and ecological security for sustainable land use planning. By integrating footprint family analysis with multi-objective optimization, we offer a novel approach to assessing ecological sustainability in urban agglomerations.

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