Extracting remotely sensed water quality parameters from shallow intertidal estuaries
Permanent link to Research Commons versionhttps://hdl.handle.net/10289/15499
Sentinel-2 imagery is potentially ideal for providing a rapid assessment of the ecological condition of estuarine water due to its high temporal and spatial resolution and coverage. However, for optically shallow waters, the problem of isolating the effect of seabed reflectance from the influence of water properties makes it difficult to use the observed surface reflectance to monitor water quality. In this study, we adopt a methodology based on Lyzenga’s model to estimate water quality properties such as the dominant wavelength and diffuse attenuation coefficient (Kd) of shallow estuarine waters. Lyzenga models the observed reflectance (R) using four parameters: total water depth (z), sea-bed reflectance (Rb), water reflectance (Rw) and Kd. If Rb is known a priori and multiple observations of R are available from different total water depths, we show that Lyzenga’s model can be used to estimate the values of the remaining two parameters, Kd and Rw. Observations of R from different water depths can either be taken from the same image at different proximal locations in the estuary (“spatial method”) or from the same pixel observed at different tidal stages (“temporal method”), both assuming homogeneous seabed and water reflectance properties. Tests in our case study estuary show that Kd and Rw can be estimated at water depths less than 6.4 m. We also show that the proximity restriction for the reflectance correction with the temporal method limits outcomes to monthly or seasonal resolution, and the correction with the spatial method performs best at a spatial resolution of 60 m. The Kd extracted from the blue band correlates well with the observed Kd for photosynthetically active radiation (PAR) (r2 = 0.66) (although the relationship is likely to be estuary-specific). The methodology provides a foundation for future work assessing rates of primary production in shallow estuaries on large scales.
© 2022 by the Authors. This work is licensed under a CC BY 4.0 license.