测绘学报 ›› 2026, Vol. 55 ›› Issue (4): 632-646.doi: 10.11947/j.AGCS.2026.20250412

• 海岸带与海洋测绘遥感 • 上一篇    

光学遥感与SAR协同的茅尾海潮滩多维时空演变监测与分析

高二涛1,2,3(), 刘静1, 李淑瑾4, 周国清1,2(), 付波霖1,2,3, 李淑娴1   

  1. 1.桂林理工大学测绘地理信息学院,广西 桂林 541004
    2.广西空间信息与测绘重点实验室,广西 桂林 541004
    3.广西高校生态时空大数据感知服务重点实验室,广西 桂林 541004
    4.中南大学地球科学与信息物理学院,湖南 长沙 410083
  • 收稿日期:2025-10-19 修回日期:2026-03-25 发布日期:2026-05-11
  • 通讯作者: 周国清 E-mail:gaoertao@glut.edu.cn;gzhou@glut.edu.cn
  • 作者简介:高二涛(1991—),男,博士,副教授,研究方向为海岸带湿地遥感。 E-mail:gaoertao@glut.edu.cn
  • 基金资助:
    广西科技计划项目(2025GXNSFAA069642);国家自然科学基金(42371341);广西空间信息与测绘重点实验室开放基金(21-238-21-26);广西高校中青年教师科研基础能力提升项目(2023KY0265)

Multi-dimensional spatiotemporal monitoring and analysis of tidal flats in the Maowei Sea using integrated optical remote sensing and SAR

Ertao GAO1,2,3(), Jing LIU1, Shujin LI4, Guoqing ZHOU1,2(), Bolin FU1,2,3, Shuxian LI1   

  1. 1.College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
    2.Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004, China
    3.Guangxi Ecological Spatiotemporal Big Data Perception Service Laboratory, Guilin 541004, China
    4.School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
  • Received:2025-10-19 Revised:2026-03-25 Published:2026-05-11
  • Contact: Guoqing ZHOU E-mail:gaoertao@glut.edu.cn;gzhou@glut.edu.cn
  • About author:GAO Ertao (1991—), male, PhD, associate professor, majors in coastal wetland remote sensing. E-mail: gaoertao@glut.edu.cn
  • Supported by:
    Guangxi Science and Technology Base and Talent Project(2025GXNSFAA069642);The National Natural Science Foundation of China(42371341);Guangxi Key Laboratory of Spatial Information and Geomatics Fund(21-238-21-26);Guangxi University Young and Middle-Aged Teachers' Basic Scientific Research Ability Improvement Project(2023KY0265)

摘要:

潮滩地处海陆交互作用的过渡地带,在维持海岸生态系统健康、蓝碳固存等方面发挥着不可替代的作用。在全球海平面上升、人类活动加剧等背景下,潮滩的时空分布、地表形变等亟须得到有效的监测及分析。本文以我国北部湾茅尾海海岸带为研究区,综合利用2015—2023年的Sentine-l2影像、低潮位Sentine-l1影像,结合海平面变化、降水量、水文变化等多源数据,开展了以下研究:①基于Google Earth Engine(GEE)云平台,利用时序Sentine-l2影像,结合最大光谱指数合成算法(MSIC)和大津算法(OTSU),构建了一种潮滩识别方法,准确提取了研究区潮滩的分布。结果发现,茅尾海地区潮滩面积由2016年的19.98 km2减少到2023年的15.80 km2,减少幅度为20.9%,土地利用的类型由潮滩向红树林、建设用地等转换。②构建了一种利用部分永久稳定散射体(PS)参与小基线集干涉测量技术(SBAS-InSAR)的“PS+SBAS-InSAR”形变提取方法,监测了潮滩的形变信息。结果发现,2015—2023年间,潮滩地表形变速率介于-54.72~41.71 mm/a之间。最大沉降地区位于红树湾,累计达-308.21 mm,最大抬升地区位于康熙岭,累计达到311.90 mm。茅尾海潮滩呈现不均匀形变变化,整体以微弱的抬升为主。其中,尖山河道两岸和红树湾呈现沉降,而康熙岭和尖山西北部呈现抬升,龙门七十二径东西两岸呈现不规则抬升和沉降。③综合多源数据分析发现,降水量、水文运动、海平面上升、红树林变化是潮滩地表形变的主导因子,且海平面上升与潮滩地表形变呈负相关。其中降水量、极端天气的影响具有季节性,而红树林、海平面上升和近海养殖的影响是长期的。

关键词: 潮滩, 遥感, 形变监测, 关键驱动, 茅尾海

Abstract:

Tidal flats are transitional areas where land meets the sea and play a crucial role in maintaining the health of coastal ecosystems and in sequestering blue carbon. With the challenges posed by global sea-level rise, increased human activities, and frequent natural disasters, there is an urgent need for effective monitoring and analysis of the spatial and temporal distribution, as well as the surface deformation, of tidal flats. This study focuses on the coastal zone of Maowei Sea in the Beibu Gulf, China. By integrating Sentinel-2 imagery from 2015 to 2023 with low-tide Sentinel-1 imagery and various other data sources, including sea-level changes, precipitation, and hydrological variations, the following investigations were conducted: ① Employing the Google Earth Engine (GEE) cloud platform, this study used time-series Sentinel-2 imagery along with the enhanced mangrove vegetation index (EMVI), normalized difference water index (NDWI), the maximum spectral index composite (MSIC) algorithm, and Otsu's method (OTSU). This approach successfully identified intertidal flats within the study area. Results demonstrated an overall accuracy of 96.6% and a Kappa coefficient of 0.92, confirming the reliability of this identification method. The tidal flat area in Maowei Sea decreased from 19.98 km2 in 2016 to 15.80 km2 in 2023, a 20.9% reduction. Land use types shifted from tidal flats to mangrove forests, construction land, and other categories. ② A deformation extraction method termed “PS+SBAS-InSAR” was developed, incorporating partial permanent scatterers (PS) into small baseline subset synthetic interferometric aperture radar (SBAS-InSAR) technology to monitor tidal flat deformation. Results show that between 2015 and 2023, the surface deformation rates on the tidal flats ranged from-54.72 mm/a to 41.71 mm/a. During this period, 98.77% of the area experienced deformation rates between-20 mm/a and 20 mm/a, and 84.62% of the area had rates between-10 mm/a and 10 mm/a, indicating overall stable ground deformation. The most significant subsidence was observed at Mangrove Bay, with a cumulative total of-308.21 mm, while the highest uplift occurred at Kangxi Ridge, with a cumulative total of 311.90 mm. The tidal flats of Maowei Sea show uneven deformation patterns, mainly characterized by slight uplift. Specifically, subsidence occurs along both banks of the Jianshan River and in Hongshu Bay, while uplift is observed at Kangxi Ridge and in the northwestern part of Jianshan. Irregular uplift and subsidence patterns are evident along both banks of Longmen Qishierjing. ③ Comprehensive analysis of multiple data sources shows that precipitation, hydrological movement, sea-level rise, and mangrove changes are the main factors affecting tidal flat surface deformation. Sea-level rise is negatively related to this deformation. Precipitation and extreme-weather patterns are seasonal, while mangrove dynamics, sea-level rise, and coastal aquaculture have long-term effects.

Key words: tidal flats, remote sensing, deformation monitoring, key drivers, Maowei Sea

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