Back to Search Start Over

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

Authors :
Bin Cao
Ruru Deng
Shulong Zhu
Yongming Liu
Yeheng Liang
Longhai Xiong
Source :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 1060-1074 (2021)
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

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.

Details

Language :
English
ISSN :
21511535
Volume :
14
Database :
Directory of Open Access Journals
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.0176c7ab5114d689fb864235037f9c4
Document Type :
article
Full Text :
https://doi.org/10.1109/JSTARS.2020.3040186