Bathymetric Retrieval Selectively Using Multiangular High-Spatial-Resolution Satellite Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Shulong Zhu¹  Ruru Deng²  Bin Cao³  Longhai Xiong³  Yeheng Liang³  Yongming Liu⁴ 

[1] College of Data Sciences, Information Engineering University, Zhengzhou, China;Guangdong Engineering Research Center of Water Environment Remote Sensing Monitoring, Guangdong Provincial Key Laboratory of Urbanization and Geo-Simulation, School of Geography and Planning, SunYat-Sen University, Guangzhou, China;School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China;State Key Laboratory of Tropical Oceanography, Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China;

关键词: Digital depth model (DDM);    multiangular imagery;    multispectral imagery;    nonoptimal image data;    physics-based bathymetry;    selective bathymetric retrieval;   

DOI  :  10.1109/JSTARS.2020.3040186

来源: DOAJ

【 摘 要 】

This article introduces multiangular imagery into physics-based bathymetry in order to compensate for the shortage of bathymetric spectral bands caused by the low spectral resolution of current high-spatial-resolution satellite multispectral imagery. The focus is to propose a selective bathymetric retrieval method to eliminate the negative effect of nonoptimal image data on depth retrieval in multiangular imagery-based bathymetry. The elimination of the negative effect is implemented by excluding nonoptimal pixels in every individual image from bathymetric retrieval. An empirical criterion is designed for the determination of nonoptimal pixels. The proposed method can use multiangular image data selectively, avoiding situations where bathymetric retrieval results from the whole multiangular imagery are poorer than that from a part of the individual images. The method was tested in two typical areas within the Xisha (Paracel) Islands of the South China Sea using two-angle WorldView-2 multispectral images. The test showed that the derived depths of the method (i.e., depths derived from the selective image data) provided a better fit to the validation depths than those from the entirety of both images. The underestimation of depths derived from the entirety of both images was also improved to some extent.

【 授权许可】

Unknown