Multi-sensor approach for chlorophyll-a monitoring in the coastal waters of Japan: a case study of the Yura Estuary

Abstract

Estuaries are one of the most productive ecosystems in the world, supporting a variety of flora and fauna. Primary productivity by phytoplankton is a rich source of organic carbon, substantial for the aquatic food web. Monitoring phytoplankton (i.e., chlorophyll-a) is essential to assess the health of estuaries and other continental shelves subjected to constant anthropogenic stress (e.g., developmental activities). In this study, a three-endmember combination Spectral Decomposition Algorithm (SDA) was developed to estimate the phytoplankton in the micro-tidal Yura estuary of Japan using Landsat-8 (30 m), and Sentinel − 2A (10 m). The endmember water, phytoplankton, and submerged aquatic vegetation (SAV) yielded the best results with both the satellite sensors (R² > 0.80) owing to the limited influence of non-phytoplankton suspended solids (NPSS) in the estuary. Chlorophyll-a was used as the proxy for phytoplankton. The estimated root mean square error (RMSE) was relatively higher in Landsat-8 (RMSE = 0.187 µg/L) than the Sentinel-2A (RMSE = 0.162 µg/L). The results were validated using the ground truth data of the Yura Estuary (26 sampling points). Furthermore, the results indicate low chlorophyll-a concentration in the Yura estuary (< 2µg/L) except near the shorelines (~ 6 µg/L). A good fit (R² = 0.79) between observed chlorophyll-a and turbidity indicated phytoplankton-dominated turbidity in the tide-less estuary of Japan. The estimated maximum turbidity was 1.4 FTU using both sensors, suggesting a low anthropogenic influence on the Yura Estuary. The study demonstrates a successful application of the spectral decomposition algorithm (SDA) in the coastal waters which could further be used to assess the horizontal and temporal variability in phytoplankton in estuarine water.