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<p>The dynamic nature of sediment transport exhibits significant variability, constantly reshaping nearshore coastal environments. Therefore, enhanced bathymetric maps play a vital role in facilitating scientific and geological research. In the present study, Sentinel 2A and 2B MSI data with 10&#xa0;m resolution have been used to create a bathymetry map of the southern regions of the Kerala and Chennai coasts. Satellite Derived Bathymetry (SDB) technique, which concurrently acquires bathymetric data from multispectral satellite imagery, facilitating a range of geological and hydrographic research, has also been utilized in this genre. We used ENVI 4.7 software to implement the Dark Object Subtraction (DOS) method for atmospheric correction of multispectral imagery. This process involved eliminating atmospheric scattering by deducting the recorded value from the pixel corresponding to the dark object. A linear regression model was developed based on the band ratio of the blue and green bands in conjunction with the bathymetric depth data from the General Bathymetric Chart of the Oceans (GEBCO), resulting in an R<sup>2</sup> value of 0.82. Additionally, we conducted regression analysis involving the Blue-Green, Green–Red, and Blue-Red bands among which the blue and green bands produce the highest R2 value. To validate this, we generated contours ranging from 0&#xa0;m to −&#xa0;20&#xa0;m along the coastline based on the derived image. The findings indicate that satellite-derived bathymetry successfully captures effective depths of up to −&#xa0;15&#xa0;m in the coastal regions.</p>

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Generation of site-specific nearshore bathymetry algorithms using remote sensing and GIS: a case study of Southern coastal regions of India

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月24日

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  • Mousumi Dey,
  • Kalyan Sundar Som,
  • Senjuti Nandy,
  • Satish B. Chavan

摘要

The dynamic nature of sediment transport exhibits significant variability, constantly reshaping nearshore coastal environments. Therefore, enhanced bathymetric maps play a vital role in facilitating scientific and geological research. In the present study, Sentinel 2A and 2B MSI data with 10 m resolution have been used to create a bathymetry map of the southern regions of the Kerala and Chennai coasts. Satellite Derived Bathymetry (SDB) technique, which concurrently acquires bathymetric data from multispectral satellite imagery, facilitating a range of geological and hydrographic research, has also been utilized in this genre. We used ENVI 4.7 software to implement the Dark Object Subtraction (DOS) method for atmospheric correction of multispectral imagery. This process involved eliminating atmospheric scattering by deducting the recorded value from the pixel corresponding to the dark object. A linear regression model was developed based on the band ratio of the blue and green bands in conjunction with the bathymetric depth data from the General Bathymetric Chart of the Oceans (GEBCO), resulting in an R2 value of 0.82. Additionally, we conducted regression analysis involving the Blue-Green, Green–Red, and Blue-Red bands among which the blue and green bands produce the highest R2 value. To validate this, we generated contours ranging from 0 m to − 20 m along the coastline based on the derived image. The findings indicate that satellite-derived bathymetry successfully captures effective depths of up to − 15 m in the coastal regions.