基于高空间分辨率遥感影像的水深反演有效性评估

卫星遥感反演水深（Satellite Derived Bathymetry, SDB）是获取浅海水深信息的有效手段。然而,其有效范围只限于光学浅水区域,在深水区域呈现“伪浅海”的失真现象。因此,如何准确识别SDB数据的有效范围对其广泛应用至关重要。本文基于高空间分辨率多光谱卫星影像,在深入分析深/浅水辐射亮度统计分布特征差异的基础上,提出一种数据驱动的水深反演有效性评价方法。该方法以卫星影像辐亮度信息的局域标准差作为特征,基于K-S检验方法对光学深水区域统计特征进行模型优选,并使用假设检验方法对深水无效区域对应的SDB进行识别。甘泉岛水域实验结果表明,该方法通过统计分布划分光学浅水与深水区域边界,可以有效识别光学深水区域产生的无效水深反演数据。在剔除无效区域数据后,光学浅水有效区域内水深反演平均绝对误差（MAE）为1.01,均方根误差（RMSE）为1.52。实验结果表明,本文提出的方法可准确识别SDB结果的有效区域,进而为浅海地形解译提供方法支撑。

Evaluation of validity of bathymetry retrieval data based on high-spatial resolution remote sensing image

Satellite derived bathymetric using multispectral imagery is an effective means to obtain shallow water depth information. However, its validity is limited to optical shallow water areas, but presents a “pseudo-shallow sea” distortion phenomenon in deep water areas. Therefore, accurately identifying the valid region of satellite derived bathymetry (SDB) data is crucial for its wide application. Based on high-spatial resolution remote sensing image, a data-driven method for evaluating the validity of SDB based on analysis of the differences in the statistical distribution of radiance in deep/shallow water regions is proposed in this paper. This method uses the local standard deviation of the radiance information of satellite images as a feature, optimizes the statistical characteristics of the optical deep water area based on the K-S test method, and uses the hypothesis test method to identify the SDB corresponding to the deep water invalid area. The experimental results in Ganquan Island region show that the method can effectively identify the invalid SDB associated with the optical deep water area by dividing the boundary between optical shallow and deep water area. After removing the invalid data, the mean absolute error (MAE) of SDB in the optical shallow region is 1.01, and the root mean square error (RMSE) is 1.52. The experimental results show that the proposed method can accurately identify the optical shallow region of SDB result, which benefits the interpretation and application of SDB results.