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Normalized Scalar Product Approach for Nearshore Bathymetric Estimation From X-Band Radar Images: An Assessment Based on Simulated and Measured Data.

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Title: Normalized Scalar Product Approach for Nearshore Bathymetric Estimation From X-Band Radar Images: An Assessment Based on Simulated and Measured Data.
Authors: Ludeno, Giovanni1, Postacchini, Matteo2, Natale, Antonio1, Brocchini, Maurizio2, Lugni, Claudio3, Soldovieri, Francesco1, Serafino, Francesco4
Source: IEEE Journal of Oceanic Engineering. Jan2018, Vol. 43 Issue 1, p221-237. 17p.
Subjects: Bathymetric maps, Remote sensing by radar, Bistatic radar, Simulation methods & models, Data analysis
Abstract: This paper investigates the capability of X-band radar systems to estimate nearshore bathymetry fields by considering both simulated and measured radar data. For the first time, a sensitivity analysis is performed to evaluate how sea-state conditions affect bathymetric estimates. For this purpose, sea wave fields generated by means of a numerical model, based on a nonlinear shallow-water equation solver, are used. Starting from the synthetic radar data, which represent the input of the bathymetric estimation algorithm, the bathymetric reconstruction is performed through the normalized scalar product (NSP) estimation strategy, exploiting a spatial partitioning of the radar data. In this way, it is possible to improve the accuracy of the estimates in nearshore areas, where the space-varying behavior of the sea depth and the presence of coastlines or coastal structures typically leads to a spatial inhomogeneity of the wave motion. In this regard, it is shown how the choice of the partitioning settings affects the bathymetric estimates obtained from high-resolution X-band radar images by using the NSP strategy. In addition, an adaptive partitioning strategy that takes into account the wave evolution in nearshore shallow waters is devised. Based on both simulated and measured radar data, the accuracy of the bathymetric estimates achievable through the proposed adaptive partitioning process and that obtained by exploiting the approach using uniform spatial partitioning are compared. The results obtained confirm the robustness of the NSP technique with respect to sea conditions and, moreover, demonstrate that the proposed adaptive partitioning strategy provides more accurate bathymetric estimates than those obtained with the space-invariant partitioning procedure. [ABSTRACT FROM PUBLISHER]
Copyright of IEEE Journal of Oceanic Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 127252227
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PubTypeId: academicJournal
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  Data: Normalized Scalar Product Approach for Nearshore Bathymetric Estimation From X-Band Radar Images: An Assessment Based on Simulated and Measured Data.
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  Data: <searchLink fieldCode="JN" term="%22IEEE+Journal+of+Oceanic+Engineering%22">IEEE Journal of Oceanic Engineering</searchLink>. Jan2018, Vol. 43 Issue 1, p221-237. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Bathymetric+maps%22">Bathymetric maps</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing+by+radar%22">Remote sensing by radar</searchLink><br /><searchLink fieldCode="DE" term="%22Bistatic+radar%22">Bistatic radar</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink>
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  Data: This paper investigates the capability of X-band radar systems to estimate nearshore bathymetry fields by considering both simulated and measured radar data. For the first time, a sensitivity analysis is performed to evaluate how sea-state conditions affect bathymetric estimates. For this purpose, sea wave fields generated by means of a numerical model, based on a nonlinear shallow-water equation solver, are used. Starting from the synthetic radar data, which represent the input of the bathymetric estimation algorithm, the bathymetric reconstruction is performed through the normalized scalar product (NSP) estimation strategy, exploiting a spatial partitioning of the radar data. In this way, it is possible to improve the accuracy of the estimates in nearshore areas, where the space-varying behavior of the sea depth and the presence of coastlines or coastal structures typically leads to a spatial inhomogeneity of the wave motion. In this regard, it is shown how the choice of the partitioning settings affects the bathymetric estimates obtained from high-resolution X-band radar images by using the NSP strategy. In addition, an adaptive partitioning strategy that takes into account the wave evolution in nearshore shallow waters is devised. Based on both simulated and measured radar data, the accuracy of the bathymetric estimates achievable through the proposed adaptive partitioning process and that obtained by exploiting the approach using uniform spatial partitioning are compared. The results obtained confirm the robustness of the NSP technique with respect to sea conditions and, moreover, demonstrate that the proposed adaptive partitioning strategy provides more accurate bathymetric estimates than those obtained with the space-invariant partitioning procedure. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of IEEE Journal of Oceanic Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/JOE.2017.2758118
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        Text: English
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        PageCount: 17
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      – SubjectFull: Bathymetric maps
        Type: general
      – SubjectFull: Remote sensing by radar
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      – SubjectFull: Bistatic radar
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      – SubjectFull: Simulation methods & models
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      – SubjectFull: Data analysis
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      – TitleFull: Normalized Scalar Product Approach for Nearshore Bathymetric Estimation From X-Band Radar Images: An Assessment Based on Simulated and Measured Data.
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            NameFull: Ludeno, Giovanni
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              Text: Jan2018
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              Y: 2018
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