Search Results (4)

Accurate atmospheric correction (AC) is one fundamental and essential step for successful ocean colour remote-sensing applications. Currently, most ACs and the associated ocean colour remote-sensing applications are restricted to solar zenith angles (SZAs) lower than 70°. The ACs under high SZAs present degraded accuracy or even failure problems, rendering the satellite retrievals of water quality parameters more challenging. Additionally, the complexity of the bio-optical properties of the coastal waters and the presence of complex aerosols add to the difficulty of AC. To address this challenge, this study proposed an AC algorithm based on extreme gradient boosting (XGBoost) for optically complex waters under high SZAs. The algorithm presented in this research has been developed using pairs of Geostationary Ocean Colour Imager (GOCI) high-quality noontime remote-sensing reflectance (Rrs) and the Rayleigh-corrected reflectance (ρ_rc) derived from the Ocean Colour–Simultaneous Marine and Aerosol Retrieval Tool (OC-SMART) in the morning (08:55 LT) and at dusk (15:55 LT). The algorithm was further examined using the daily GOCI images acquired in the morning and at dusk, and the hourly (total suspended sediment) TSS concentration was also obtained based on the atmospherically corrected GOCI data. The results showed that: (i) the model produced an accurate fitting performance (R² ≥ 0.90, RMSD ≤ 0.0034 sr⁻¹); (ii) the model had a high validation accuracy with an independent dataset (R² = 0.92–0.97, MAPD = 8.2–26.81% and quality assurance (QA) score = 0.9–1); and (iii) the model successfully retrieved more valid Rrs for GOCI images under high SZAs and enhanced the accuracy and coverage of TSS mapping. This algorithm has great potential to be applied to AC for optically complex waters under high SZAs, thus increasing the frequency of available observations in a day. Full article

The Great Barrier Reef (GBR) is a marine protected area subject to natural and anthropogenic disturbances. Water quality is critical for the health and protecting resilience of GBR coral ecosystems against the synergistic and cumulative pressures of tropical cyclones, marine heat waves, and outbreaks of crown-of-thorns starfish. The concentration of Total Suspended Solids (TSS) is a key water quality parameter measured at multiple spatio-temporal scales from in situ probes to satellite observations. High TSS concentrations can adversely impact coral and seagrasses on the inshore GBR. We present diurnal TSS derived from Himawari-8 Geostationary satellite observations at 10 min frequency and demonstrate its applicability for improved monitoring of GBR water quality. Diurnal TSS obtained from Himawari-8 observations were compared to TSS computed from in situ bio-optical measurements at the Lucinda Jetty Coastal Observatory (LJCO). The coastal waters at LJCO experience diurnal variability of TSS (~7 mg L⁻¹), where magnitude peaks followed the slack tides, and the largest diurnal changes were associated with freshwater discharge residuals from the wet season. Exceedance maps revealed that TSS is above guideline thresholds in the open coastal and mid-shelf waters for ~60% of the valid monthly observations, including during dry season months. Full article

Remote sensing of ocean colour has been fundamental to the synoptic-scale monitoring of marine water quality in the Great Barrier Reef (GBR). However, ocean colour sensors onboard low orbit satellites, such as the Sentinel-3 constellation, have insufficient revisit capability to fully resolve diurnal variability in highly dynamic coastal environments. To overcome this limitation, this work presents a physics-based coastal ocean colour algorithm for the Advanced Himawari Imager onboard the Himawari-8 geostationary satellite. Despite being designed for meteorological applications, Himawari-8 offers the opportunity to estimate ocean colour features every 10 min, in four broad visible and near-infrared spectral bands, and at 1 km² spatial resolution. Coupled ocean–atmosphere radiative transfer simulations of the Himawari-8 bands were carried out for a realistic range of in-water and atmospheric optical properties of the GBR and for a wide range of solar and observation geometries. The simulated data were used to develop an inverse model based on artificial neural network techniques to estimate total suspended solids (TSS) concentrations directly from the Himawari-8 top-of-atmosphere spectral reflectance observations. The algorithm was validated with concurrent in situ data across the coastal GBR and its detection limits were assessed. TSS retrievals presented relative errors up to 75% and absolute errors of 2 mg L⁻¹ within the validation range of 0.14 to 24 mg L⁻¹, with a detection limit of 0.25 mg L⁻¹. We discuss potential applications of Himawari-8 diurnal TSS products for improved monitoring and management of water quality in the GBR. Full article

Total suspended particulate matter (TSM) in estuarine and coastal regions usually exhibits significant natural variations. The understanding of such variations is of great significance in coastal waters. The aim of this study is to investigate and assess the diurnal and seasonal variations of surface TSM distribution and its mechanisms in coastal waters based on Geostationary Ocean Color Imager (GOCI) data. As a case study, dynamic variations of TSM in the macro-tidal Yalu River estuary (YRE) of China were analysed. With regard to diurnal variability, there were usually two peaks of TSM in a tidal cycle corresponding to the maximum flood and ebb current. Tidal action appears to play a vital role in diurnal variations of TSM. Both the processes of tidal re-suspension and advection could be identified; however, the diurnal variation of TSM was mainly affected by a re-suspension process. In addition, spring-neap tides can affect the magnitude of TSM diurnal variations in the YRE. The GOCI-retrieved TSM results clearly showed the seasonal variability of surface TSM in this area, with the highest level occurring in winter and the lowest in summer. Moreover, although river discharge to the YRE was much greater in the wet season than the dry season, TSM concentrations were significantly higher in the dry season. Wind waves were considered to be the main factor affecting TSM seasonal variation in the YRE. Full article