Bathymetry Retrieval From Spaceborne Multispectral Subsurface Reflectance
Guoqing Zhou, Sikai Su, Jiasheng Xu, Zhou Tian, Qiaobo Cao
Abstract
A few scholars have developed the models for retrieval of water depth from subsurface reflectance of multispectral images to avoid the influences of such as sun glitter. However, the models are only suitable for case I water. For this reason, this study proposes a bathymetry retrieval model using subsurface reflectance for both case I and case II water. The model first corrects the water surface reflectance image and then converts it into a subsurface reflectance image, and the subsurface reflectance image is used as the water depth retrieval image. Landsat 8 images were taken for experiments in case 1 water and case 2 water, and two water areas, Weizhou Island, Guangxi, China, and Molokai Island, Hawaii, USA, were used to verify the proposed model. The experimental results showed that the proposed model reduced the root mean squared error (RMSE) of the retrieved water depth in the Weizhou and Molokai areas from 3.113 m to 2.903 m and 4.239 m to 3.653 m, respectively, i.e., improve accuracy of water depth at 6.75% and 13.82% for Weizhou and Molokai areas, respectively. Therefore, the results demonstrate that the proposed model using subsurface reflectance can significantly improve the accuracy of bathymetry retrieval via spaceborne multispectral images.