Imaging estuarine surface salinity using Sentinel-2: a case study in the Pearl River Estuary
DOI:
https://doi.org/10.1590/Keywords:
Estuarine surface salinity, Sentinel-2, Neutral network model, The Pearl River EstuaryAbstract
Optical remote sensing for estuarine surface salinity relies on correlation with water color parameters, facing
limitations in spectra, resolution, and hydrodynamics, particularly in multi-outlet estuaries. In this study,
Sentinel-2 images with 10m resolution were selected, and geographic coordinates, imaging date and band
combinations were incorporated as inputs for a neural network model to capture spatiotemporal salinity
distribution. By repeatedly constructing the model with varied inputs to mitigate the impact of input sample
variations and ensure robustness, the final model, N2L-3, achieved high accuracy (R2
= 0.916 and overall RMSE
below 1.5 PSU) and was chosen to estimate the estuarine surface salinity in the Pearl River Estuary. Our
results revealed high-salinity offshore water intruding the eastern estuary channel during flood tides, gradually
merging upstream with freshwater. Low-salinity water reached the Pearl River Front Channel and East River
North Branch. During ebb tides, due to estuarine outflows, low-salinity water spread through river mouths and
shifted eastward near Humen.
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