ArticleScientific reports2026
Assessing county-level high-quality development and spatial adaptation paths under the space of flows perspective: a coupling detrended fluctuation analysis approach.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Given the limited research on high-quality development (HQD) at the county level, especially in major agricultural provinces such as Henan, this study constructs a multidimensional evaluation system tailored to local heterogeneity. Guided by the Five Development Concepts and incorporating the space of flows perspective to reveal inter-county spatial linkages, we introduce a coupling detrended fluctuation analysis (CDFA)-based assessment method to develop a temporally informed county-specific weighting mechanism. This enables the calculation of county-specific indicator weights and overcomes the limitation of traditional methods that assign fixed and uniform weights. Using panel data on 19 indicators for 102 counties in Henan Province from 2010 to 2021, we examine the spatiotemporal trends and structural heterogeneity of county-level HQD. Results indicate broad-based improvement in county-level HQD, while high- and medium-high-quality counties became more concentrated around core urban areas and the remaining weaker counties were mainly located in peripheral areas, demonstrating a clearer core-periphery spatial pattern under overall upgrading. The CDFA-based weighting results reveal significant county-level differences in the relative structural roles of economic vitality, green development, social welfare, and inter-county association, highlighting substantial heterogeneity in county-level indicator-weight profiles rather than a uniform indicator structure across the province. Comparative analysis shows that the proposed method is broadly consistent with a conventional objective weighting approach in overall classification patterns, while offering additional insight into county-level heterogeneity. The optimal parameters-based geographical detector further indicates that locational conditions, industrial foundations, and topographic constraints are important explanatory factors for the spatial differentiation of county-level HQD, and that factor interactions generally produce stronger explanatory power than single factors. Based on these findings, this study proposes differentiated development strategies for core counties, transitional counties, agricultural counties, and peripheral ecologically constrained areas, thereby providing a methodological reference for HQD assessment in spatially heterogeneous regions and supporting regional spatial governance.
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