上海市全行业土地利用的跨区域产业链驱动机制分析
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1.广东工业大学 生态环境与资源学院 湾区生态安全与绿色发展基础研究卓越中心;2.广东工业大学生态环境与资源学院

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国家自然科学基金


Driving mechanism for local full-sector land use in Shanghai through multi-regional supply chains
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School of Ecology, Environment and Resources, Guangdong University of Technology

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The National Natural Science Foundation of China

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    摘要:

    上海市人口和经济快速增长导致了严峻的土地利用形势。现有研究主要关注上海市社会经济活动的直接土地利用,其他地区生产消费活动对上海市土地利用的跨区域产业链驱动机制尚不清晰,无法为缓解上海市土地利用压力的政策决策提供充分依据。构建了一个全行业土地利用核算框架,并结合环境扩展多区域投入产出模型,从生产侧、需求侧、供给侧视角识别了多区域产业链中驱动上海市土地利用的关键地区与行业。结果表明,生产侧视角下,上海市用地面积最大的行业包括“种植业”和“批发和零售”;需求侧视角下,上海对“种植业”产品的需求驱动了大量的本市土地利用,河南、广东等省份的最终需求对上海市用地的驱动作用显著;供给侧视角下,关键初始投入行业包括上海市“种植业”和“批发和零售”,江苏等省份的初始投入行业间接驱动了较多的上海市用地。研究结果从多视角为上海市土地利用的可持续管理指出着力点,同时可为其他地区的土地利用研究提供参考。

    Abstract:

    Land resources are essential to socioeconomic development, as well as the material basis for human survival. The rapid population growth and accelerated industrialization in Shanghai have resulted in a significant shortage of land resources. Future socioeconomic development is expected to further intensify land use activities, potentially exacerbating the land resource challenges in Shanghai. Moreover, environmental impacts arising from land use changes may negatively affect climate and ecosystems, reduce human well-being, and restrict the coordinated development of society, economy, and environment. Therefore, to address the challenge of land resource scarcity, it is necessary to further optimize the structure of land use and improve land use efficiency. Existing studies primarily focus on the direct land use of socioeconomic activities in Shanghai. However, in addition to being directly affected by local production activities, the land use of a region is also indirectly affected by remote economic activities through multi-regional supply chains. Currently, the multi-regional supply chain driving mechanism of production and consumption activities in other regions (e.g., critical regions and industries) on Shanghai's land use remains unclear. This limits the effectiveness of policy-making on land use pressure mitigation. This study constructs a full-sector land use accounting framework based on road network data, point-of-interest (POI) information, and remote sensing data. Combined with an environmentally extended multi-regional input-output model, it identifies critical regions and industries driving land use in Shanghai from the perspectives of production, demand, and supply within the multi-regional supply chain network. We find three main findings: (1) On the production side, the industries occupying the largest land use areas include "agriculture" and "wholesale and retail" in Shanghai; (2) On the demand side, Shanghai’s demand for products of the "agriculture" industry drives substantial domestic land use; and the final demand of Guangdong, Henan, and other provinces has driven large amounts of land uses in Shanghai; (3) On the supply side, the primary inputs of industries including "agriculture" and "wholesale and retail" in Shanghai, and the "chemical products" industry in Jiangsu indirectly drive large amounts of Shanghai's land uses. This study identifies critical supply chain drivers of land use in Shanghai, providing multiple perspective policy decisions on alleviating land resource scarcity. Findings of this study have three policy implications: (1) For critical production-side industries, intensive land use measures (e.g., rational land planning) can be adopted to improve land use efficiency; (2) For critical demand-side industries, optimizing consumption behaviors of their products can encourage upstream suppliers to improve the productivity, which can alleviate land resource scarcity of the whole supply chains; (3) For critical supply-side industries, economic incentives can be introduced to optimize the distribution of products to downstream industries of more efficient land uses, which can facilitate the land use efficiency of the whole supply chains. The findings in this study provide the hotspots for sustainable management of land use in Shanghai from multiple perspectives. The analytical framework of this study can provide a reference for land use management in other regions. Improving the extraction and classification processes of POI data in future work can help to reduce the uncertainty of land use estimation results of this study.

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王淇,邢泽霖,李雨萌,梁赛.上海市全行业土地利用的跨区域产业链驱动机制分析.生态学报,,(). http://dx. doi. org/[doi]

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