Eco-Environmental Risk Assessment and Its Precaution Partitions Based on a Knowledge Graph: A Case Study of Shenzhen City, China
Yijia Yang,
Xuexin Zhu
Abstract:The eco-environment is under constant pressure caused by the rapid pace of urbanization and changes in land use. Shenzhen is a typical “small-land-area, high-density” megalopolis facing various dilemmas and challenges; we must understand the eco-environmental risk (ER) of rapidly urbanizing regions and promote high-quality regional development. Therefore, with the help of the Python and Neo4j platforms, this study applies the theoretical foundation of knowledge graphs (KGs) and deep learning to form the KG of … Show more
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