Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-7147-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-17-7147-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Spatial patterns of sandy beaches in China and risk analysis of human infrastructure squeeze based on multi-source data and ensemble learning
Jie Meng
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China
Duanyang Xu
CORRESPONDING AUTHOR
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Zexing Tao
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Quansheng Ge
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
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Short summary
This study used multi-source remote sensing data and ensemble learning methods to map the distribution of sandy beaches in China from 2016 to 2024. A total of 3447 sandy beaches were identified with high accuracy by integrating Sentinel-1/2 satellite imagery, terrain, and nighttime light data. Since 1990, the area at risk from human infrastructure squeeze has significantly increased. This study provides an updated dataset to support sustainable coastal management.
This study used multi-source remote sensing data and ensemble learning methods to map the...
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