Spatiotemporal coupling mechanisms and driving forces of ecosystem services and human activity from a multidimensional perspective

Global environmental changes and human activities drive critical research into socio-ecological systems’ mechanisms for understanding sustainable development. Using the Shandong Peninsula urban agglomeration as a case study, this study integrating multi-source data (population density, GDP, transpor...

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Bibliographic Details
Main Authors: Daohong Gong, Dejin Dong, Huaqiang Du, Yufeng Zhou, Sang Fu, Yuichiro Fujioka
Format: Article
Language:English
Published: Taylor & Francis Group 2025-08-01
Series:International Journal of Digital Earth
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Online Access:https://www.tandfonline.com/doi/10.1080/17538947.2025.2512061
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Summary:Global environmental changes and human activities drive critical research into socio-ecological systems’ mechanisms for understanding sustainable development. Using the Shandong Peninsula urban agglomeration as a case study, this study integrating multi-source data (population density, GDP, transportation networks, and energy consumption) with advanced modeling techniques (InVEST, CASA, Theil-Sen, Mann-Kendall, and PLS-SEM), this study comprehensively quantifies and analyzes the spatiotemporal dynamics, spatial correlations, and driving mechanisms of human activity intensity (HAI) and comprehensive ecosystem services (CES) from 2001 to 2020. The results reveal (1) The HAI and CES in this study area exhibit significant spatial heterogeneity. (2) From 2001 to 2020, HAI and CES exhibited a robust positive spatial correlation with notable clustering patterns. (3) Spatially, HAI and CES demonstrated an escalating negative correlation, with Moran's I progressively declining from – 0.182 in 2001 to – 0.306 in 2020, indicating increasing spatial divergence. (4) The detrimental impact of HAI on CES intensified over time, with path coefficients decreasing from – 0.216 to – 0.374, while natural factors maintained a stable positive influence (0.299-0.378). This study systematically uncovers the spatiotemporal coupling mechanisms between HAI and CES in this study area through a multidimensional perspective, providing transferable methodological insights and empirical evidence to guide sustainable development strategies.
ISSN:1753-8947
1753-8955