Author
Listed:
- Qiao Yu
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
- Fangxiong Wang
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
- Yingzi Hou
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
- Zhenqi Cui
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
- Junfu Wang
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
- Yi Lu
(School of Geographical Sciences, Liaoning Normal University, Dalian 116029, China
Liaoning Provincial Key Laboratory of Physical Geography and Geomatics, Liaoning Normal University, Dalian 116029, China)
Abstract
Mid-channel bars are fundamental fluvial geomorphic units that regulate sediment transport, channel stability, and riparian ecosystems, and their spatiotemporal evolution provides critical insights for sustainable river management. This study examines the structural reorganization and migration dynamics of mid-channel bars along the mainstem of the transboundary Yalu River using multi-temporal Sentinel-2 imagery acquired in 2019, 2022, and 2024. An automated extraction framework combining a dense atrous U-Net (DA-UNet) with multispectral indices was developed to robustly identify mid-channel bars under complex water–land transition conditions. Based on the extracted results, changes in bar number, area, size composition, morphological characteristics, and centroid migration were systematically analyzed. The results reveal a pronounced reorganization of mid-channel bars systems over the study period: although the number of bars increased from 111 to 136, the total area decreased from 168.97 km 2 to 165.00 km 2 , indicating a transition from a “few-large” to a “many-small” configuration. Size-based analysis further shows an increase in small and medium bars, while large bars remained relatively stable, leading to a more differentiated multi-scale structure. These findings highlight the effectiveness of integrating multi-temporal remote sensing and deep learning for long-term monitoring of geomorphic dynamics and provide scientific evidence to support sustainable river regulation and transboundary watershed management.
Suggested Citation
Qiao Yu & Fangxiong Wang & Yingzi Hou & Zhenqi Cui & Junfu Wang & Yi Lu, 2026.
"Spatiotemporal Evolution of Mid-Channel Bars in the Yalu River Based on DA-UNet,"
Sustainability, MDPI, vol. 18(3), pages 1-24, February.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:3:p:1681-:d:1858991
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