Remote Sensing Techniques for Shallow Water Bathymetry

Shallow water bathymetry via remote sensing encompasses both passive optical and active laser‐based methods to map seafloor topography in coastal and reef environments. Passive optical techniques infer depth from the spectral response of the water–bottom system, exploiting band ratios or polynomial relationships between multispectral reflectance and known depths. These approaches benefit from the global coverage and frequent revisit times of satellite sensors, but their accuracy is constrained by water clarity, bottom type and atmospheric effects. Active methods, including airborne or spaceborne lidar and photon‐counting altimeters, emit pulses that penetrate the water column and record seabed returns, offering high vertical accuracy and better performance in turbid waters, albeit at higher operational cost. Recent advances focus on combining active and passive datasets to extend depth retrievals, applying machine learning to delineate optically shallow versus deep waters, and deploying cloud‐computing platforms for large‐scale processing. Together, these developments are delivering metre‐scale bathymetric products over extensive coastal zones, supporting navigation safety, coastal engineering, habitat monitoring and climate‐change impact assessment worldwide.

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Remote Sensing Techniques for Shallow Water Bathymetry publication trend

The graph below shows the total number of articles in remote sensing techniques for shallow water bathymetry across all publications each year (not limited to Nature Index journals).

Technical terms

Satellite-derived bathymetry (SDB): Estimation of water depth from satellite multispectral imagery by relating surface reflectance to seabed reflectance and water optical properties.

Active remote sensing: Techniques that emit a signal (e.g. laser pulse) and measure its return, enabling direct measurement of seafloor depth irrespective of ambient light conditions.

Passive remote sensing: Observation of naturally reflected or emitted radiation from the Earth’s surface, used to infer bathymetry through spectral analysis.

Lidar: Light detection and ranging, an active method that uses laser pulses to measure distances to the water surface and seabed, providing high-accuracy bathymetric profiles.

Quadratic polynomial ratio model (QPRM): A mathematical model that fits a second-order polynomial to the ratio of multispectral bands for deriving water depth without direct in situ calibration.

Secchi depth: A measure of water transparency obtained by lowering a calibrated disc into the water, often used as a proxy for optical clarity in bathymetric studies.

References

1. Cost-efficient bathymetric mapping method based on massive active–passive remote sensing data. ISPRS Journal of Photogrammetry and Remote Sensing (2023).
2. Global deep learning model for delineation of optically shallow and optically deep water in Sentinel-2 imagery. Remote Sensing of Environment (2024).
3. Validation of ICESat-2 ATLAS Bathymetry and Analysis of ATLAS’s Bathymetric Mapping Performance. Remote Sensing (2019).