南海典型岛礁浅海地形遥感监测及时序变化研究*

doi:10.11978/2024218

热带海洋学报 ›› 2025, Vol. 44 ›› Issue (5): 140-153.doi: 10.11978/2024218CSTR: 32234.14.2024218

南海典型岛礁浅海地形遥感监测及时序变化研究^*

陈钰宸¹(), 付东洋¹(), 陶邦一², 李姬喆², 祝依娴², 刘贝¹, 林烨¹, 柴霞¹

1.广东海洋大学电子与信息工程学院, 广东湛江 524088
2.自然资源部第二海洋研究所卫星海洋环境动力学国家重点实验室, 浙江杭州 310012

收稿日期:2024-11-26 修回日期:2025-01-25 出版日期:2025-09-10 发布日期:2025-10-14
通讯作者: 付东洋
作者简介:
陈钰宸(2000—), 女, 江苏省泰州市人, 硕士研究生, 从事海洋遥感应用研究。email: 295428711@qq.com
*感谢国家地理信息公共服务平台(https://www.tianditu.gov.cn/)、哥白尼数据中心(https://browser.dataspace.copernicus.eu/)、NASA地球科学数据中心(https://search.earthdata.nasa.gov/search)提供数据支撑。
基金资助:
国家重点研发计划项目(2022YFC3103101); 南方海洋科学与工程广东省实验室(广州)重大专项团队项目(GML2021GD0809); 国家自然科学基金项目(42206187); 广东省教育厅重点科研项目(2023ZDZX4009)

Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea^*

CHEN Yuchen¹(), FU Dongyang¹(), TAO Bangyi², LI Jizhe², ZHU Yixian², LIU Bei¹, LIN Ye¹, CHAI Xia¹

1. College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China
2. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China

Received:2024-11-26 Revised:2025-01-25 Online:2025-09-10 Published:2025-10-14
Contact: FU Dongyang
Supported by:
National Key Research and Development Program of China(2022YFC3103101); Guangdong Provincial Laboratory of Southern Ocean Science and Engineering (Guangzhou) Major Project Team(GML2021GD0809); National Natural Science Foundation of China(42206187); Key Research Project of Guangdong Provincial Department of Education(2023ZDZX4009)

摘要/Abstract

摘要：

南沙群岛位于我国南海南部区域, 其地理位置对我国海洋权益、发展战略和国家安全都十分重要。开展南沙群岛岛礁水深及地形监测与变化研究, 对于国家战略具有重要意义。文章结合哨兵-2 (Sentinel-2)和冰、云和陆地高程卫星(ice, cloud, land elevation satellite-2, ICESat-2)数据, 采用主动-被动融合遥感测深算法, 对南海南沙群岛的柏礁和北子岛浅海区域的地形进行了反演研究及实验验证。这一方法能够利用时间序列分析, 揭示岛礁水深和地形的长期趋势和短期波动, 为理解人类活动和自然因素对岛礁地形变化的影响提供了新的视角。研究结果如下: 1) 验证了一个高精度的水深反演模型, 该模型在研究中表现出优异的性能, 相关系数R²> 0.9, 平均绝对误差(mean absolute error, MAE) < 0.4m, 均方根误差(root-mean-square error, RMSE) < 0.7m。2) 2018—2024年间柏礁和北子岛地形及空间结构均发生了不同程度的变化。柏礁因填海造陆工程, 陆地面积增加; 北子岛则受自然因素影响, 出现动态变化。3) 柏礁的地形变化主要由人为因素驱动, 包括填海造陆、资源开采等。北子岛的变化则主要是自然因素的结果, 包括季风、台风、海水冲刷和沉积物淤积等。

关键词: 南海岛礁, 哨兵-2, 冰、云和陆地高程卫星, 水深反演, 时空监测

Abstract:

The Nansha Islands, located in the southern part of the South China Sea, hold significant strategic importance for China’s maritime rights and interests, development strategy, and national security due to its geographical location. It is of great significance to national strategy to carry out research on water depth monitoring and topographic changes of Nansha Islands and reefs. In this study, combined with Sentinel-2 and ICESat-2 (ice, cloud, land elevation satellite-2) data, an active-passive fusion remote sensing sounding algorithm was used to invert the shallow sea topography of the Bai Jiao and Beizi Dao areas in the Nansha Islands. This method enables time series analysis to reveal long-term trends and short-term fluctuations in water depth and reef terrain, providing new insights into the impacts of human activities and natural factors on reef topography changes. The research results are as follows: 1) A high-precision water depth inversion model was validated, showing excellent performance in the study area (R²> 0.9, MAE < 0.4 m, RMSE < 0.7 m). 2) From 2018 to 2024, both Bai Jiao and Beizi experienced varying degrees of terrain and spatial structure changes. Due to reclamation projects, the land area of Bai Jiao increased, whereas Beizi Dao’s changes were influenced by natural factors, exhibiting dynamic variations. 3) The topographic changes of Bai Jiao were mainly driven by human factors, including land reclamation and resource exploitation, while Beizi Dao’s changes mainly resulted from natural factors such as monsoons, typhoons, seawater erosion, and sediment deposition. This study demonstrates the effectiveness of active-passive fusion bathymetry, providing a valuable reference for efficient water depth and terrain detection of typical reefs in China. Moreover, it offers crucial technical support for long-term spatiotemporal monitoring of shallow sea terrain in areas such as the Nansha Islands.

Key words: South China Sea islands and reefs, Sentinel-2, ICESat-2, bathymetric inversion, spatiotemporal monitoring

中图分类号:

P737.13

陈钰宸, 付东洋, 陶邦一, 李姬喆, 祝依娴, 刘贝, 林烨, 柴霞. 南海典型岛礁浅海地形遥感监测及时序变化研究^*[J]. 热带海洋学报, 2025, 44(5): 140-153.

CHEN Yuchen, FU Dongyang, TAO Bangyi, LI Jizhe, ZHU Yixian, LIU Bei, LIN Ye, CHAI Xia. Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea^*[J]. Journal of Tropical Oceanography, 2025, 44(5): 140-153.

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年份	航道宽度/m	航道面积/km²	平均水深/m	陆地面积/km²
2022	84.25	0.02	14.77	0.17
2023	281.92	0.07	10.48	0.30 (5月)、0.96 (10月)
2024	299.98	0.09	11.37	1.55 (1月)、1.94 (6月)

经过时间	台风名称	最大风速/(m·s^-1)	气压/hPa	移动方向
2018.11.22	天兔(Usagi)	30	1004	西西南
2021.12.18	雷伊(Rai)	52	935	西西北

年份	沙滩区域面积/km²	沙滩区域面积变化率/%	礁坪区域面积/km²	礁坪区域面积变化率/%	礁前斜坡区域面积/km²	礁前斜坡区域面积变化率/%
2018	0.091		1.189		0.480
2018	0.091	1.9	1.189	-1.0	0.480	-4.2
2019	0.090	1.9	1.201	-1.0	0.501	-4.2
2019	0.090	-15.0	1.201	2.4	0.501	4.4
2020	0.103	-15.0	1.172	2.4	0.479	4.4
2020	0.103	-5.8	1.172	0.3	0.479	2.2
2021	0.109	-5.8	1.169	0.3	0.468	2.2
2021	0.109	23.1	1.169	-2.5	0.468	4.7
2022	0.084	23.1	1.197	-2.5	0.446	4.7
2022	0.084	-27.9	1.197	2.4	0.446	-8.4
2023	0.107	-27.9	1.169	2.4	0.483	-8.4
2023	0.107	-4.5	1.169	1.5	0.483	-1.9
2024	0.112	-4.5	1.151	1.5	0.493	-1.9

南海典型岛礁浅海地形遥感监测及时序变化研究^*

Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea^*

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南海典型岛礁浅海地形遥感监测及时序变化研究*

Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea*

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南海典型岛礁浅海地形遥感监测及时序变化研究^*

Study on remote sensing monitoring and time series change of shallow sea topography of typical islands and reefs in the South China Sea^*