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Review of near-shore satellite derived bathymetry: Classification and account of five decades of coastal bathymetry research

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JOURNAL OF OCEAN ENGINEERING AND SCIENCE
卷 6, 期 4, 页码 340-359

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ELSEVIER
DOI: 10.1016/j.joes.2021.02.006

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Satellite derived bathymetry; Hydrography; Bio-optical model; Physio-optical model

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Accurate knowledge of coastal bathymetry is essential for various applications, with traditional surveying methods requiring high-cost resources. Space technology offers a cost-effective alternative, with optical satellite data providing potential solutions in near-shore regions after decades of research and algorithm development for Satellite Derived Bathymetry (SDB).
The number of civilian, commercial and military applications are dependant on accurate knowledge of bathymetry of coastal regions. Conventionally, hydrographic surveying methods are used for bathymetric surveys carried by ship-based acoustic systems, but needs high cost resources. Space technology has provided a cost-effective alternate means for charting near shore and inaccessible waters. The optical satellite data have capabilities to offer alternate solution in near-shore region, which has been researched for past 50 years, using evolving algorithms to estimate Satellite Derived Bathymetry (SDB). However, there is no agreement on use of terms like approach, model, method and techniques, which have been used varyingly and interchangeably as per context of SDB research. This paper suggests a classification scheme for SDB algorithms which is also applicable to other Marine Remote Sensing studies. In this paper, based on literature available on SDB for the past five decades, an insight on SDB classification has been offered grounded in research philosophy. The SDB approaches, models, methods and techniques have been elaborated with chronological development, along with SDB studies based on them, their accuracy and errors in SDB retrieval. We have suggested a matrix of prerequisite satellite data, in-situ data resolution, methods and algorithms of SDB based on level of accuracy needs to be achieved, which will guide future researchers to select one as per their context of research. (c) 2021 Shanghai Jiaotong University. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

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