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A Segmented Adaptive Filtering Method for Nearshore Bathymetry Using ICESat-2 Dataset.

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Title: A Segmented Adaptive Filtering Method for Nearshore Bathymetry Using ICESat-2 Dataset.
Authors: Chen, Yifu1,2 (AUTHOR), Wang, Ziqiang1,2 (AUTHOR), Song, Wuxing1,3 (AUTHOR), Le, Yuan1,3 (AUTHOR) leyuan@cug.edu.cn, Zhou, Liqin1,2 (AUTHOR), Guo, Haichao2,3 (AUTHOR), Wu, Lin1,2 (AUTHOR), Yi, Lin3 (AUTHOR)
Source: Remote Sensing. Feb2026, Vol. 18 Issue 4, p568. 24p.
Subjects: Bathymetry, Satellite-based remote sensing, Oceanographic maps, Photon counting, Curve fitting, Adaptive filters, Coastal mapping, Laser altimeters
Geographic Terms: Florida Keys (Fla.)
Abstract: Highlights: What are the main findings? A novel segmented adaptive filtering bathymetry method was proposed for high-precision nearshore bathymetry using ICESat-2 data. Extensive experiments across different coastal sites (Qilianyu Islands and West Island) demonstrate that our method achieves high accuracy, with a root mean square error (RMSE) as low as 0.37 m and a coefficient of determination (R2) of 0.98 when validated against airborne LiDAR bathymetry. What is the implication of the main finding? The proposed method provides a fully automated, accurate, and reliable solution for nearshore bathymetric mapping from space, effectively overcoming the challenges of varying environmental conditions and photon density. This study confirms the significant potential of ICESat-2's ATLAS data for underwater bathymetry, paving the way for its broader application in coastal zone management and marine geospatial research. The high-accuracy results coupled with robust performance across different regions demonstrate the method's strong potential for enabling operational, large-scale bathymetric surveys. Equipped with an Advanced Topographic Laser Altimeter System (ATLAS), ICESat-2 (Ice, Cloud and land Elevation Satellite-2) is a photon-counting laser altimetry mission with strong potential for nearshore bathymetry. In this study, a novel filtering and bathymetric method termed a segmented adaptive filtering bathymetry has been proposed. Sea-surface photons are identified from peaks in the elevation-density histogram, enabling separation of surface and seafloor photons. The seafloor photons are then partitioned into along-track segments, where seafloor signal photons are extracted using an adaptive elliptical kernel whose parameters and orientation are determined from local density patterns and seafloor slope. The seafloor profile is obtained by polynomial fitting, and nearshore depth is estimated from the elevations of the surface and seafloor signal photons. To ensure and improve the accuracy and reliability of the proposed method, ICESat-2 data from Qilianyu Islands at the South China Sea and West Island at the Florida Keys of the United States were adopted to perform experiments. Furthermore, the bathymetric results obtained by ICESat-2 datasets at different experimental areas were compared with the reference bathymetry obtained by the airborne light detection and ranging (LiDAR) bathymetry (ALB) system. Finally, the bathymetric accuracy validation and assessment were performed. The highest accuracy of root mean square error (RMSE) and coefficient of determination (R2) has reached 0.37 m and 98%, respectively. The accuracy validation of bathymetric results at different study areas demonstrated that the method proposed in this study can automatically and effectively achieve high-precision nearshore bathymetry and topographic surveys. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI 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.)
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  Data: A Segmented Adaptive Filtering Method for Nearshore Bathymetry Using ICESat-2 Dataset.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Yifu%22">Chen, Yifu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Ziqiang%22">Wang, Ziqiang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Song%2C+Wuxing%22">Song, Wuxing</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Le%2C+Yuan%22">Le, Yuan</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<i> leyuan@cug.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Liqin%22">Zhou, Liqin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Haichao%22">Guo, Haichao</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wu%2C+Lin%22">Wu, Lin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yi%2C+Lin%22">Yi, Lin</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Feb2026, Vol. 18 Issue 4, p568. 24p.
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  Data: <searchLink fieldCode="DE" term="%22Bathymetry%22">Bathymetry</searchLink><br /><searchLink fieldCode="DE" term="%22Satellite-based+remote+sensing%22">Satellite-based remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Oceanographic+maps%22">Oceanographic maps</searchLink><br /><searchLink fieldCode="DE" term="%22Photon+counting%22">Photon counting</searchLink><br /><searchLink fieldCode="DE" term="%22Curve+fitting%22">Curve fitting</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+filters%22">Adaptive filters</searchLink><br /><searchLink fieldCode="DE" term="%22Coastal+mapping%22">Coastal mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+altimeters%22">Laser altimeters</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Florida+Keys+%28Fla%2E%29%22">Florida Keys (Fla.)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights: What are the main findings? A novel segmented adaptive filtering bathymetry method was proposed for high-precision nearshore bathymetry using ICESat-2 data. Extensive experiments across different coastal sites (Qilianyu Islands and West Island) demonstrate that our method achieves high accuracy, with a root mean square error (RMSE) as low as 0.37 m and a coefficient of determination (R2) of 0.98 when validated against airborne LiDAR bathymetry. What is the implication of the main finding? The proposed method provides a fully automated, accurate, and reliable solution for nearshore bathymetric mapping from space, effectively overcoming the challenges of varying environmental conditions and photon density. This study confirms the significant potential of ICESat-2's ATLAS data for underwater bathymetry, paving the way for its broader application in coastal zone management and marine geospatial research. The high-accuracy results coupled with robust performance across different regions demonstrate the method's strong potential for enabling operational, large-scale bathymetric surveys. Equipped with an Advanced Topographic Laser Altimeter System (ATLAS), ICESat-2 (Ice, Cloud and land Elevation Satellite-2) is a photon-counting laser altimetry mission with strong potential for nearshore bathymetry. In this study, a novel filtering and bathymetric method termed a segmented adaptive filtering bathymetry has been proposed. Sea-surface photons are identified from peaks in the elevation-density histogram, enabling separation of surface and seafloor photons. The seafloor photons are then partitioned into along-track segments, where seafloor signal photons are extracted using an adaptive elliptical kernel whose parameters and orientation are determined from local density patterns and seafloor slope. The seafloor profile is obtained by polynomial fitting, and nearshore depth is estimated from the elevations of the surface and seafloor signal photons. To ensure and improve the accuracy and reliability of the proposed method, ICESat-2 data from Qilianyu Islands at the South China Sea and West Island at the Florida Keys of the United States were adopted to perform experiments. Furthermore, the bathymetric results obtained by ICESat-2 datasets at different experimental areas were compared with the reference bathymetry obtained by the airborne light detection and ranging (LiDAR) bathymetry (ALB) system. Finally, the bathymetric accuracy validation and assessment were performed. The highest accuracy of root mean square error (RMSE) and coefficient of determination (R2) has reached 0.37 m and 98%, respectively. The accuracy validation of bathymetric results at different study areas demonstrated that the method proposed in this study can automatically and effectively achieve high-precision nearshore bathymetry and topographic surveys. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Remote Sensing is the property of MDPI 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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      – Type: doi
        Value: 10.3390/rs18040568
    Languages:
      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 568
    Subjects:
      – SubjectFull: Bathymetry
        Type: general
      – SubjectFull: Satellite-based remote sensing
        Type: general
      – SubjectFull: Oceanographic maps
        Type: general
      – SubjectFull: Photon counting
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      – SubjectFull: Curve fitting
        Type: general
      – SubjectFull: Adaptive filters
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      – SubjectFull: Coastal mapping
        Type: general
      – SubjectFull: Laser altimeters
        Type: general
      – SubjectFull: Florida Keys (Fla.)
        Type: general
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      – TitleFull: A Segmented Adaptive Filtering Method for Nearshore Bathymetry Using ICESat-2 Dataset.
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              Text: Feb2026
              Type: published
              Y: 2026
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