Exploring the Annual Dynamics of China’s Rivers From 2016 to 2023 Based on Sentinel-Derived Datasets

Rivers play import roles in ecological biodiversity, shipping trade and carbon cycle. In our study, we developed an effective, robust, and accurate algorithm for national scale river mapping, and produced the annual China River Extent Dataset (CRED) from 2016 to 2023. We assessed the reliability of the CRED based on test samples and data inter-comparison. The results indicated that the overall accuracy (OAs) of the CRED were greater than 88.4% from 2016 to 2023. The rivers of the CRED from 2017 to 2023 achieved good accuracy, with the user accuracies (UAs), producer accuracies (PAs) and F1-score of rivers exceeding 80.4%, 85.0% and 83.7%, respectively. In 2016, rivers of the CRED achieved medium accuracy, with F1-score of 78.4%. A further data comparison indicated that our CRED had good consistency with existing river-related datasets, with correlation coefficient (R) greater than 0.75. The area statistics indicated that the river area in China were 44,948.78 km2 in 2023. From 2016 to 2023, the river areas were characterized by an initial increase, followed by a decrease and then a slight increase. Spatially, the decreased rivers were located mainly in Southeast China, whereas the increased rivers were distributed mainly in Central China and Northeast China. In general, the CRED explicitly delineated river extents and dynamics in China, which could provide a good foundation for improving river ecology and management.

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Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/jstars.2025.3584770
Citations
1
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
1.11

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article

Exploring the Annual Dynamics of China’s Rivers From 2016 to 2023 Based on Sentinel-Derived Datasets

Kaifeng Peng, Weiguo Jiang, Meihong Ma, Xuejun Wang et al.
1 citations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Flood Risk Assessment and Management
1.11
article

Exploring the Annual Dynamics of China’s Rivers From 2016 to 2023 Based on Sentinel-Derived Datasets

Kaifeng Peng, Weiguo Jiang, Meihong Ma, Xuejun Wang, Beibei Si
article en
1 citations

Abstract

Rivers play import roles in ecological biodiversity, shipping trade and carbon cycle. In our study, we developed an effective, robust, and accurate algorithm for national scale river mapping, and produced the annual China River Extent Dataset (CRED) from 2016 to 2023. We assessed the reliability of the CRED based on test samples and data inter-comparison. The results indicated that the overall accuracy (OAs) of the CRED were greater than 88.4% from 2016 to 2023. The rivers of the CRED from 2017 to 2023 achieved good accuracy, with the user accuracies (UAs), producer accuracies (PAs) and F1-score of rivers exceeding 80.4%, 85.0% and 83.7%, respectively. In 2016, rivers of the CRED achieved medium accuracy, with F1-score of 78.4%. A further data comparison indicated that our CRED had good consistency with existing river-related datasets, with correlation coefficient (R) greater than 0.75. The area statistics indicated that the river area in China were 44,948.78 km2 in 2023. From 2016 to 2023, the river areas were characterized by an initial increase, followed by a decrease and then a slight increase. Spatially, the decreased rivers were located mainly in Southeast China, whereas the increased rivers were distributed mainly in Central China and Northeast China. In general, the CRED explicitly delineated river extents and dynamics in China, which could provide a good foundation for improving river ecology and management.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
Tianjin Normal University (CN), Beijing Normal University (CN), State Key Laboratory of Remote Sensing Science (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 22%
Flood Risk Assessment and Management
1.11
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