The phytoplankton size class (PSC) plays an important role in biogeochemical processes in the ocean. In this study, a regional model of PSCs is proposed to retrieve vertical PSCs from the total minus water absorption coefficient (a_t-w(λ)) and Chlorophyll a concentration (Chla). The PSC model is developed by first reconstructing phytoplankton absorption and Chla from a_t-w(λ), and then extracting PSC from them using the support vector machine (SVM). In situ bio-optical data collected in the South China Sea from 2006 to 2013 were used to train the SVM. The proposed PSC model was subsequently validated using an independent PSC dataset from the Northeast South China Sea Cruise in 2015. The results indicate that the PSC model performed better than the three components model, with a value of r² between 0.35 and 0.66, and the absolute percentage difference between 56% and 181%. On the whole, our PSC model shows a remarkable utility in terms of inferring vertical PSCs from the South China Sea.

This study on total suspended matter (TSM) in the Pearl River Estuary established a regression analysis model using Landsat 8 reflectance and measured TSM data, crucial for environmental management and engineering projects. High coefficients of determination (>0.6) were reported for the selected models. TSM concentration was notably high in 2013, peaking at 180 mg/L during the flood season and 80 mg/L in the dry season. In contrast, 2020 saw lower concentrations. Similar spatial distribution patterns were observed during dry and flood seasons, with high nearshore and low offshore TSM concentrations. Statistical analyses revealed natural factors (precipitation and runoff) as major influencers of the TSM distribution, with human activities presenting localized, limited impacts, except under long-term and large-scale conditions. Over time, the influence of large-scale water-based construction, such as the Hong Kong–Zhuhai–Macao Bridge, on TSM distribution became significant.