Shallow water bathymetry using remote sensing based on spectral stratification
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摘要: 卫星水深反演是水深测量的一种重要手段，其中Stumpf比值算法和Lyzenga多项式算法应用广泛并诞生了大量改进算法，但这些算法没有顾及不同光谱的测深极限与适用范围，为此本文提出一种基于光谱分层的水深反演方法。首先，根据红、绿、蓝光谱对水体的穿透能力差异，提出一种基于影像本身的无参数光谱分层策略，提取红光层、绿光层、蓝光层；然后，根据不同光谱层的波段测深性能，分光谱层构建水深反演优化模型，获取浅海水深反演结果。以我国南沙海域长线礁和美属维尔京群岛巴克岛为实验区，本文方法对经典Stumpf比值算法和Lyzenga多项式算法进行改进后，水深均方根误差、平均绝对误差、平均相对误差分别降低了0.41～0.89 m、0.35～0.65 m、4%～19%，尤其在红光层，即水深较浅区域，平均相对误差降低了58%～149%，精度提升明显。因此，改进算法在提高卫星水深反演效果方面具有可行性和有效性。Abstract: Shallow water bathymetry using remote sensing is an important technology in marine geodesy. The Stumpf ratio and Lyzenga polynomial methods, as classic representative algorithms, are widely used and many improved algorithms have been developed. However, these methods do not take into account the bathymetry ability of different spectra. In this study, we propose a bathymetry method based on spectral stratification. Firstly, according to the difference in the penetration ability of red, green and blue spectra to the waterbody, an image-based nonparametric spectral layering strategy is proposed to extract the red, green and blue layers. Then, based on the band bathymetric performance of different spectral layers, we constructed a bathymetric inversion optimization model by spectral layers and further obtained the shallow water bathymetry. The Changxian Reef in the Nansha sea area and Buck Island Reef in U.S. Virgin Islands are selected as test cases to validate the proposed method. Compared with the classical Stumpf ratio and Lyzenga polynomial methods, the root-mean-square error (RMSE), mean absolute error (MAE) and mean relative error (MRE) of the proposed method have decreased by 0.41−0.89 m, 0.35−0.65 m, and 4%−19% respectively. Particularly, the accuracy of the red light layer (i.e., the shallow water depth) is significantly improved, and the MRE is reduced by 58%−149%. Our findings suggest that the proposed bathymetry method based on spectral stratification is feasible and effective in improving the accuracy of the shallow water depth estimation and has good potential for future applications.
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Key words:
- multispectral /
- shallow water /
- water depth retrieval /
- Sentinel-2 /
- Stumpf method /
- Lyzenga method /
- multispectral bathymetry
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图 1 实验区与水深数据
a. 长线礁遥感影像和声呐测深数据；b. 巴克岛遥感影像；c. 巴克岛激光测深数据；d. 巴克岛水下地形图；左下方世界地图从自然资源部标准地图服务网站下载，审图号为GS（2016）2957号
Fig. 1 Study areas and depth data
a. Remote sensing imagery and sonar bathymetric data for the Changxian Reef; b. remote sensing imagery for the Buck Island Reef; c. airborne laser bathymetric data for the Buck Island Reef; d. underwater topographic map of Buck Island Reef; the world map at bottom left was downloaded from the standard map service website of the Ministry of Natural Resources, the drawing review number is GS (2016) 2957
图 4 长线礁水深反演结果图
a. Stumpf比值算法结果；b. 基于光谱分层的Stumpf比值算法结果；c. Lyzenga多项式算法结果；d. 基于光谱分层的Lyzenga多项式算法结果
Fig. 4 Bathymetric maps of the Changxian Reef produced by inversion
a. Result of Stumpf ratio method; b. result of Stumpf ratio method based on spectral stratification; c. result of Lyzenga polynomial method; d. result of Lyzenga polynomial method based on spectral stratification
图 5 长线礁反演水深与实测水深值误差分布
正值表示反演水深值比实测水深值深
Fig. 5 Distribution of differences obtained by subtracting the measured values from the inversion water depth for the Changxian Reef
Positive value indicates that the inversion water depth is deeper than that of the measured values
图 6 巴克岛水深反演结果图
a. Stumpf比值算法结果；b. 基于光谱分层的Stumpf比值算法结果；c. Lyzenga多项式算法结果；d. 基于光谱分层的Lyzenga多项式算法结果
Fig. 6 Bathymetric maps of the Buck Island Reef produced by inversion
a. Result of Stumpf ratio method; b. result of Stumpf ratio method based on spectral stratification; c. result of Lyzenga polynomial method; d. result of Lyzenga polynomial method based on spectral stratification
图 7 巴克岛反演水深与实测水深值误差分布图
正值表示反演水深值比实测水深值深
Fig. 7 Distribution of differences obtained by subtracting the measured values from the inversion water depth for the Buck Island Reef
Positive value indicates that the inversion water depth is deeper than that of the measured values
图 8 长线礁实验区训练样本数量对反演精度的影响
Fig. 8 Effects of the number of training samples on the accuracy of bathymetric inversion for the Changxian Reef experimental area
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