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Deciphering the evolving trajectories of China's megaregions from 1992 to 2020: A novel morphological approach based on global land cover products
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Deciphering the evolving trajectories of China's megaregions from 1992 to 2020: A novel morphological approach based on global land cover products
Haojie Cao; Yu Li; Min Weng; Shiliang Su; Mengjun Kang
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From:Applied Geography
2024 Vol.164 , Pages 000-000(doi:10.1016/j.apgeog.2024.103205)

Abstract:The monitoring of megaregion boundaries (MBs) is of vital importance for optimizing land use decision-making. However, the morphological structure of megaregions is currently insufficiently identified due to the nontransparent proprietary or inherent deficiency data sources. Thus, this study utilized land cover products integrated with morphological approaches to delineate the evolving trajectories of China's megaregions from 1992 to 2020. Firstly, core areas of megaregions and periphery affected areas were extracted from urban land density maps based on the gravity model and landscape metrics . Secondly, contiguous urban-rural fringes were improved based on the morphological operations and the rank-size distribution. Thirdly, urban land was automatically allocated to megaregions, considering planning policies. Furthermore, three indicators (gross domestic product, population, and land use density) are considered to validate our results, and our extracted MBs show a better understanding than the administrative divisions. The dynamic expansion patterns of twenty identified MBs were captured. As urbanization continues, the boundaries between megaregions become increasingly blurred and eventually merged into large-scale continuous megaregions that extend far beyond administrative divisions. Our study provides valuable insights for megaregion planning, including the effective urban management policies , the role of core cities in each megaregion in terms of radiation and capability.
KeyWord:Megaregion boundary; Land cover maps; Morphological boundary; Landscape metrics; Gravity model; Rank-size distribution;

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