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- W4283799981 abstract "The spatial distribution pattern of brownfields can help governments at all levels, and investors have more detailed information on land resources, prioritize brownfield redevelopment, and guide urban spatial and strategic planning. Despite increasing global concern, yet knowledge of brownfield distribution patterns at the macro-scale remains limited, especially in China. Derived from the China National Knowledge Infrastructure (CNKI), Web of Science (WOS), and Chinese Industrial Heritage List published between 2001 and 2019, we present the first comprehensive dataset of known brownfield sites and their distributions in China. The results revealed that the dataset contains 816 georeferenced brownfield records from 255 cities. Brownfields were mainly distributed southeast of the “Heihe-Tengchong Line,” with an overall spatial distribution pattern of “East-dense-West-sparse.” In terms of brownfield type, industrial brownfields were the most numerous, followed by mining brownfields. Nearest neighbor indicator analysis suggested that brownfields in China present significant spatial agglomeration characteristics, and that the six types of brownfields manifest different scales of spatial agglomeration. The hot spots were mainly concentrated in the Yangtze River Delta, Beijing–Tianjin–Hebei, and Pearl River Delta urban agglomerations. Factors influencing brownfield formation were related to industrial structure adjustments, resource depletion, accelerated urbanization, and the orientation of national policies, with industrial structure adjustments being the leading cause. Mastering the spatial distribution of brownfields can coordinate land use transformation planning and guide brownfield redevelopment." @default.
- W4283799981 created "2022-07-05" @default.
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- W4283799981 date "2022-07-04" @default.
- W4283799981 modified "2023-09-25" @default.
- W4283799981 title "Exploring Spatial Distributions and Formation Factors of Brownfields in China: From Macro-Scales" @default.
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- W4283799981 doi "https://doi.org/10.3389/fenvs.2022.918621" @default.
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