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Abstract
The coupled and coordinated development of population and land urbanization represents the core goal of new-type urbanization. However, existing research lacks refined measurement of the population-land urbanization coupling relationship at the county scale and insufficiently reveals the dynamic stage characteristics of its driving mechanism. To address this gap, this study takes counties in the Yangtze River Delta urban agglomeration as the research object. It integrates multi-source remote sensing data, including VIIRS NTL, LandScan population grid, CLCD land cover, and POI to construct a progressive analytical framework of fusion-extraction-assessment. First, the study uses wavelet transform to optimize the fusion of multi-source data. Second, it applies the U-Net deep learning model to finely extract the spatial patterns and temporal evolution characteristics of county land and population urbanization. Third, it uses a coupling coordination model to quantitatively evaluate the coupling matching relationship between the two from 2013 to 2025. Finally, it employs geographic detectors to identify the key driving factors and their explanatory power differences for coupling coordination development in different periods. The results show that the expansion speed of land urbanization in counties of the Yangtze River Delta urban agglomeration significantly exceeds that of population urbanization. Counties across the entire region exhibit varying degrees of population-land mismatch. The population-land urbanization coupling coordination degree of counties overall shows a steady upward trend. Spatially, it presents an evolutionary characteristic of spreading from point-like agglomeration in core cities to planar diffusion in the eastern region. The geographic detector results reveal a stage characteristic with dominant factors in different periods: foreign investment in 2013, economic development level in 2017, government expenditure in 2021, and industrial structure in 2025. This study meticulously reveals the spatiotemporal evolution patterns of population-land urbanization coupling coordination at the county scale. It identifies the dynamic evolution logic of population-land coordinated development in Yangtze River Delta counties. The study also constructs a technical framework for county urbanization research using multi-source remote sensing data fusion. This framework breaks through the limitations of single-indicator measurement and enhances the spatial precision and mechanism explanatory power of county urbanization research. This study provides empirical support for improving county-level spatial governance and promoting the coordinated development of population and land urbanization. It holds significant importance for enriching urbanization theory research and serving the implementation of the new-type urbanization strategy.
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