A practical angular spectrum method to estimate ocean surface wave directions and wavelengths using Sentinel-2 MSI imagery

High spatial-resolution Sentinel-2 Multi-Spectral Instrument (MSI) images often show image features due to surface waves, swells, fronts, internal waves, eddies, and currents under different sunglint and skyglint reflections. Here, MSI images are used to estimate wave direction and wavelength through a simple but practical method using Angular spectrum analysis (ASA). The method does not require the complex transfer function between the image domain and the physical domain, but is based on the MSI-derived Fast Fourier Transform (FFT) spectrum that reveals the wave direction, whose 180 o ambiguity is then removed by the inter-band time lag between the B04 and B08 bands (0.74 s). The wavelength of different sea waves (wind wave and swell) can also be estimated by quantifying the MSI FFT images. There is a statistically significant linear relationship between MSI-derived and buoy-measured wave direction and wavelength ( N = 144) with low bias. Further analyses according to wave age criterion show a better statistical relationship for wind waves ( N = 62) than swells ( N = 82). Comparison with the hourly wind products of the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) shows RMS differences of <1.4 m/s and 14.4 o for wind speed and direction, respectively. These results demonstrate that, under certain observing conditions, high spatial-resolution optical remote sensing images can provide relatively accurate estimates of surface wave directions and wavelengths as well as wind speeds, while operational applications still require further work. • A method is developed to characterize wave direction from Sentinel-2 MSI images. • Inter-band time lag can be used to remove the 180° ambiguity of wave direction. • The wavelength can be provided in the MSI images derived wavenumber domain. • Most (> 55.5 %) of the estimated wave directions have uncertainties <15°. • Whitecaps in the same images can be used to estimate surface winds.

Authors

Publication Details

Journal
Remote Sensing of Environment
Published
2025-09-27
DOI
https://doi.org/10.1016/j.rse.2025.115044
Citations
1
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
1.79
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article

A practical angular spectrum method to estimate ocean surface wave directions and wavelengths using Sentinel-2 MSI imagery

Chuanmin Hu, Lifeng Wang, Yingcheng Lu
1 citations
Remote Sensing of Environment
Ocean Waves and Remote Sensing
1.79
article

A practical angular spectrum method to estimate ocean surface wave directions and wavelengths using Sentinel-2 MSI imagery

Chuanmin Hu, Lifeng Wang, Yingcheng Lu
article en
1 citations

Abstract

High spatial-resolution Sentinel-2 Multi-Spectral Instrument (MSI) images often show image features due to surface waves, swells, fronts, internal waves, eddies, and currents under different sunglint and skyglint reflections. Here, MSI images are used to estimate wave direction and wavelength through a simple but practical method using Angular spectrum analysis (ASA). The method does not require the complex transfer function between the image domain and the physical domain, but is based on the MSI-derived Fast Fourier Transform (FFT) spectrum that reveals the wave direction, whose 180 o ambiguity is then removed by the inter-band time lag between the B04 and B08 bands (0.74 s). The wavelength of different sea waves (wind wave and swell) can also be estimated by quantifying the MSI FFT images. There is a statistically significant linear relationship between MSI-derived and buoy-measured wave direction and wavelength ( N = 144) with low bias. Further analyses according to wave age criterion show a better statistical relationship for wind waves ( N = 62) than swells ( N = 82). Comparison with the hourly wind products of the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) shows RMS differences of <1.4 m/s and 14.4 o for wind speed and direction, respectively. These results demonstrate that, under certain observing conditions, high spatial-resolution optical remote sensing images can provide relatively accurate estimates of surface wave directions and wavelengths as well as wind speeds, while operational applications still require further work. • A method is developed to characterize wave direction from Sentinel-2 MSI images. • Inter-band time lag can be used to remove the 180° ambiguity of wave direction. • The wavelength can be provided in the MSI images derived wavenumber domain. • Most (> 55.5 %) of the estimated wave directions have uncertainties <15°. • Whitecaps in the same images can be used to estimate surface winds.

Remote Sensing of EnvironmentVol. 331
Openalex Percentile: Top 13%
Ocean Waves and Remote Sensing
1.79
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