Spatiotemporal Coupling Dynamics of Ecological Quality and Human Activity Intensity in China’s Huai River Basin: A Multi-Dimensional Assessment Framework (2012–2024)

Understanding how ecological quality and human activity co-evolve in densely populated watersheds is essential for sustainable land management, yet spatially explicit long-term evidence remains limited. This study investigated the spatiotemporal dynamics and coupling coordination between ecological quality and multi-dimensional human activity intensity in the Huai River Basin (approximately 269,000 km2) from 2012 to 2024. An Improved Remote Sensing Ecological Index (IRSEI) was constructed by integrating EVI, wetness, dryness, land surface temperature, and a salinity index through annual principal component analysis. A composite Human Activity Intensity (HAI) index combining nighttime light, built-up intensity, and population density was derived with objectively determined weights. The coupling coordination degree (CCD) model and a pixel-level four-quadrant classification were then applied to characterize the human–environment interaction. Results showed that the basin-wide mean IRSEI declined from 0.564 in 2012 to 0.516 in 2020, before recovering to 0.566 in 2024, while HAI increased moderately by 16.9%. CCD improved slightly from 0.451 to 0.480, indicating limited but positive coordination gains. Four-quadrant transitions revealed that high-ecology, low-activity areas expanded, low-ecology, low-activity areas contracted, whereas low-ecology, high-activity zones persisted as stable pressure cores. These findings demonstrate that ecological recovery and human activity intensification can coexist spatially, but persistent high-pressure areas require targeted management interventions.

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Publication Details

Journal
Land
Published
2026-06-16
DOI
https://doi.org/10.3390/land15061064
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Spatiotemporal Coupling Dynamics of Ecological Quality and Human Activity Intensity in China’s Huai River Basin: A Multi-Dimensional Assessment Framework (2012–2024)

Haoyu Hu, Yan Xu, Xiaoyu Hu, Lina Wang et al.
Land
Remote Sensing in Agriculture
article

Spatiotemporal Coupling Dynamics of Ecological Quality and Human Activity Intensity in China’s Huai River Basin: A Multi-Dimensional Assessment Framework (2012–2024)

Haoyu Hu, Yan Xu, Xiaoyu Hu, Lina Wang, Yuehua Chen, Di Shi, Hedong Wang, Chunliu Luo, Xinrui Yu, Tianyu Zeng, Jianbao Huang, Yuandong Zou, Zhiyin Mo
article en

Abstract

Understanding how ecological quality and human activity co-evolve in densely populated watersheds is essential for sustainable land management, yet spatially explicit long-term evidence remains limited. This study investigated the spatiotemporal dynamics and coupling coordination between ecological quality and multi-dimensional human activity intensity in the Huai River Basin (approximately 269,000 km2) from 2012 to 2024. An Improved Remote Sensing Ecological Index (IRSEI) was constructed by integrating EVI, wetness, dryness, land surface temperature, and a salinity index through annual principal component analysis. A composite Human Activity Intensity (HAI) index combining nighttime light, built-up intensity, and population density was derived with objectively determined weights. The coupling coordination degree (CCD) model and a pixel-level four-quadrant classification were then applied to characterize the human–environment interaction. Results showed that the basin-wide mean IRSEI declined from 0.564 in 2012 to 0.516 in 2020, before recovering to 0.566 in 2024, while HAI increased moderately by 16.9%. CCD improved slightly from 0.451 to 0.480, indicating limited but positive coordination gains. Four-quadrant transitions revealed that high-ecology, low-activity areas expanded, low-ecology, low-activity areas contracted, whereas low-ecology, high-activity zones persisted as stable pressure cores. These findings demonstrate that ecological recovery and human activity intensification can coexist spatially, but persistent high-pressure areas require targeted management interventions.

LandVol. 15(6)
Guangxi University (CN), University of Manchester (GB)
Life in Land
Openalex Percentile: Top 7%
Remote Sensing in Agriculture
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