主被动光学卫星遥感数据融合浅海水深测量

Shallow water depth measurement based on fusion of active and passive optical satellite remote sensing data

针对双介质立体摄影测量中水面高程不确定性带来的测深误差,本文提出了主被动光学卫星遥感数据融合浅海水深测量的技术路线,探讨了主动ICESat-2激光测高数据与被动WorldView-3立体像对数据融合的测深模型。首先通过ICESat-2激光测高数据提取海面高程作为WorldView-3立体像对数据水面高程纠正的起算位置,然后利用区域网平差的二次多项式加入适当的水深改正量。在我国南海岛礁开展了主被动光学卫星遥感数据融合进行浅海水深测量试验。结果表明,主被动融合测深模型的均方根误差(RMSE)小于0.70 m,实现了高精度、无实测控制点的浅海水深测量。

Aiming at the bathymetric error caused by the uncertainty of water surface elevation in dual-medium stereo photogrammetry,a technical route of shallow water depth measurement based on fusion of active and passive optical satellite remote sensing data is proposed,and the bathymetric model of integrating active ICESat-2 laser altimetry data and passive WorldView-3 stereo image pair data is studied.Firstly,the sea surface elevation is extracted from ICESat-2 laser altimetry data as the starting position for water surface elevation correction of WorldView-3 stereo image pair data.Then the appropriate water depth correction is added using the quadratic polynomial of the area network parity.A shallow water bathymetry experiment is carried out on the fusion of active and passive optical satellite remote sensing data in South China Sea.The results show that the root mean square error(RMSE) of the active and passive fusion bathymetry model is less than 0.70 m.The active-passive fusion bathymetric model realizes high-precision shallow water bathymetry without measured control points.