Zhantang Xu

Variations in the optical scattering properties of phytoplankton cultures.

The scattering and backscattering coefficients of 15 phytoplankton species were determined in the laboratory using the acs and BB9 instruments. The spectral variability of scattering properties was investigated and the homogenous sphere model based on Mie theory was also evaluated. The scattering efficiencies at 510 nm varied from 1.42 to 2.26, and the backscattering efficiencies varied from 0.003 to 0.020. The backscattering ratios at 510 nm varied from 0.17% to 0.97%, with a mean value of 0.58%. The scattering properties were influenced by algal cell size and cellular particulate organic carbon content rather than the chlorophyll a concentration. Comparison of the measured results to the values estimated using the homogenous sphere model showed that: (1) The model could well reproduce the spectral scattering coefficient with relative deviations of 5-39%, which indicates that cell shape and internal structure have no significant effects on predicting the scattering spectra; (2) Although the homogenous sphere model generally reflected the spectral trend of backscattering spectra for most species, it severely underestimated the backscattering coefficients by 1.4-48.6 folds at 510 nm. The deviations for Chaetoceros sp. and Microcystis aeruginosa were large and might be due to algal cell chain links and intracellular gas vacuoles, respectively.

Analysis of seagrass reflectivity by using a water column correction algorithm

Seagrass in optically shallow water can generate optical signals that can be tracked remotely. Unfortunately the signals from the bottom are relatively weak and can be affected by the water column when concentrations of suspended particles, chlorophyll and coloured dissolved organic matter are high. An optical model simulating the propagation of light for retrieving the bottom reflectance was developed. Implementation of the method was found to be effective for improving the accuracy of coastal habitat maps, and essential for deriving empirical relationships between remotely sensed data and interesting features in the marine environment. The appropriate wavebands for seagrass mapping, which generally lay between 500 and 630 nm and 680 and 710 nm, were obtained by means of full visual inspection and analysis of the correct spectra. Additionally, a strong relationship between the reflectance value at 715 nm and Leaf Area Index was found, with a correlation coefficient of 0.99.

Assessment of SeaWiFS, MODIS, and MERIS ocean colour products in the South China Sea

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Medium Resolution Imaging Spectrometer (MERIS) remote-sensing radiometric and chlorophyll-a (chl-a) concentration products for the South China Sea (SCS) from October 2003 to May 2010 were assessed using in situ data. A strict spatiotemporal match-up method was used to minimize the temporal variability effects of atmosphere and seawater around the measurement site. A comparison of the remote-sensing reflectance (Rrs(λ)) of the three sensors with in situ values from the open waters of the SCS showed that the mean absolute percentage difference varied from 13% to 55% in the 412–560 nm spectral range. Generally, the MERIS radiometric products exhibited higher typical uncertainties and bias than the SeaWiFS and MODIS products. The Rrs(443) to Rrs(555/551/560) band ratios of the satellite data were in good agreement with in situ observations for these sensors. The SeaWiFS, MODIS, and MERIS chl-a products overestimated in situ values by 74%, 42%, and 120%, respectively. MODIS retrieval accuracy was better than those of the other sensors, with MERIS performing the worst. When the match-up criteria were relaxed, the assessment results degraded systematically. Therefore, strict spatiotemporal match-up is recommended to minimize the possible influences of small-scale variation in geophysical properties around the measurement site. Coastal and open-sea areas in the SCS should be assessed separately because their biooptical properties are different and the results suggest different atmospheric correction problems.

Novel method for quantifying the cell size of marine phytoplankton based on optical measurements.

Phytoplankton size is important for the pelagic food web and oceanic ecosystems. However, the size of phytoplankton is difficult to quantify because of methodological constraints. To address this limitation, we have exploited the phytoplankton package effect to develop a new method for estimating the mean cell size of individual phytoplankton populations. This method was validated using a data set that contained simultaneous measurements of phytoplankton absorption and cell size distributions from 13 phytoplankton species. Comparing with existing methods, our method is more efficient with good accuracy, and it could potentially be applied in current in situ optical instruments.

Empirical ocean color algorithm for estimating particulate organic carbon in the South China Sea

We examined regional empirical equations for estimating the surface concentration of particulate organic carbon (POC) in the South China Sea. These algorithms are based on the direct relationships between POC and the blue-to-green band ratios of spectral remotely sensed reflectance, Rrs (λB)/Rrs(555). The best error statistics among the considered formulas were produced using the power function POC (mg/m3)=262.173 [Rrs(443)/Rrs(555)]−0.940. This formula resulted in a small mean bias of approximately −2.52%, a normalized root mean square error of 31.1%, and a determination coefficient of 0.91. This regional empirical equation is different to the results of similar studies in other oceanic regions. Our validation results suggest that our regional empirical formula performs better than the global algorithm, in the South China Sea. The feasibility of this band ratio algorithm is primarily due to the relationship between POC and the green-toblue ratio of the particle absorption coefficient. Colored dissolved organic matter can be an important source of noise in the band ratio formula. Finally, we applied the empirical algorithm to investigate POC changes in the southwest of Luzon Strait.

Comparison of MERIS, MODIS, SeaWiFS-derived particulate organic carbon, and in situ measurements in the South China Sea

ABSTRACT Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) particulate organic carbon (POC) concentration products for the South China Sea (SCS) were compared with in situ data collected from October 2007 to December 2013. Spectral remote-sensing reflectance (Rrs,λ) was also measured to help understand POC algorithm performance. A strict comparison of the satellite-derived POC and in situ measurements showed that MERIS, MODIS, and SeaWiFS underestimated in situ values by 29.1, 11.7, and 31.5%, respectively. Similar results were obtained with a relaxed matching criterion. Through analysis of the causes of product uncertainty, the results suggested that satellite retrieval of Rrs,λ and the global POC algorithm both have an impact on inversion accuracy. However, the formulation of the POC algorithm seems to be more critical. When a regional algorithm was developed to obtain satellite-derived POC, both the strict and relaxed comparison results showed significant improvement, but for coastal waters, both algorithms had larger errors. Other factors affecting the comparison are also discussed.

A bio-optical inversion model to retrieve absorption contributions and phytoplankton size structure from total minus water spectral absorption using genetic algorithm

We propose a bio-optical inversion model that retrieves the absorption contributions of phytoplankton and colored detrital matter (CDM), as well as the phytoplankton size classes (PSCs), from total minus water absorption spectra. The model is based on three-component separation of phytoplankton size structure and a genetic algorithm. The model performance was tested on two independent datasets (the NASA bio-Optical Marine Algorithm Dataset (NOMAD) and the northern South China Sea (NSCS) dataset). The relationships between the estimated and measured values were strongly linear, especially for aCDM (412), and the Root Mean Square Error (RMSE) of the CDM exponential slope (SCDM) was relatively low. Next, the inversion model was directly applied to in-situ total minus water absorption spectra determined by an underwater meter during a cruise in September 2008, to retrieve the phytoplankton size structure in the seawater. By comparing the measured and retrieved chlorophyll a concentrations, we demonstrated that total and size-specific chlorophyll a concentrations could be retrieved by the model with relatively high accuracy. Finally, we applied the bio-optical inversion model to investigate changes in phytoplankton size structure induced by an anti-cyclonic eddy in the NSCS.

Estimating the Augmented Reflectance Ratio of the Ocean Surface When Whitecaps Appear

The presence of foam influences the accuracy of satellite-derived water-leaving radiance. A model has been developed to estimate the augmented reflectance ratio (A(λ,U)) due to differences in the fraction of whitecap coverage (w) on the ocean surface. A(λ,U) can be calculated from the product of w and ρ(λ,U), where ρ(λ,U) is the augmented ratio of the reflectance of background water (Rb(λ)) caused by the presence of whitecaps. Our results showed that the average A(400~700,U) in the visible region was approximately 1.3% at U = 9 m∙s−1, 2.2% at U = 10 m∙s−1, 4.4% at U = 12 m∙s−1, 7.4% at U = 14 m∙s−1, 19% at U = 19 m∙s−1 and 37.9% at U = 24 m∙s−1, making it is necessary to consider the augmented reflectance ratio for remote sensing applications. By estimating remote sensing augmented reflectance using A(λ,U), it was found that the result was in good agreement with previous studies conducted in other areas with U from 9 to 12 m∙s−1. Since Rb(λ) is temporally and spatially variable, our model considered the variation of Rb(λ), whereas existing models have assumed that Rb(λ) is constant. Therefore, the proposed model is more suitable for estimating the augmented reflectance ratio due to whitecaps.

Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea

Ocean colour remote sensing is used as a tool to detect phytoplankton size classes (PSCs). In this study, the Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) phytoplankton size classes (PSCs) products were compared with in-situ High Performance Liquid Chromatography (HPLC) data for the South China Sea (SCS), collected from August 2006 to September 2011. Four algorithms were evaluated to determine their ability to detect three phytoplankton size classes. Chlorophyll-a (Chl-a) and absorption spectra of phytoplankton (aph(λ)) were also measured to help understand PSC’s algorithm performance. Results show that the three abundance-based approaches performed better than the inherent optical property (IOP)-based approach in the SCS. The size detection of microplankton and picoplankton was generally better than that of nanoplankton. A three-component model was recommended to produce maps of surface PSCs in the SCS. For the IOP-based approach, satellite retrievals of inherent optical properties and the PSCs algorithm both have impacts on inversion accuracy. However, for abundance-based approaches, the selection of the PSCs algorithm seems to be more critical, owing to low uncertainty in satellite Chl-a input data

Retrieval of phytoplankton cell size from chlorophyll a specific absorption and scattering spectra of phytoplankton

Phytoplankton cell size is an important property that affects diverse ecological and biogeochemical processes, and analysis of the absorption and scattering spectra of phytoplankton can provide important information about phytoplankton size. In this study, an inversion method for extracting quantitative phytoplankton cell size data from these spectra was developed. This inversion method requires two inputs: chlorophyll a specific absorption and scattering spectra of phytoplankton. The average equivalent-volume spherical diameter (ESDv) was calculated as the single size approximation for the log-normal particle size distribution (PSD) of the algal suspension. The performance of this method for retrieving cell size was assessed using the datasets from cultures of 12 phytoplankton species. The estimations of a(λ) and b(λ) for the phytoplankton population using ESDv had mean error values of 5.8%-6.9% and 7.0%-10.6%, respectively, compared to the a(λ) and b(λ) for the phytoplankton populations using the log-normal PSD. The estimated values of CiESDv were in good agreement with the measurements, with r2=0.88 and relative root mean square error (NRMSE)=25.3%, and relatively good performances were also found for the retrieval of ESDv with r2=0.78 and NRMSE=23.9%.