Bangyi Tao

Influence of bio-optical parameter variability on the reflectance peak position in the red band of algal bloom waters

article i nfo On the basis of field measurements, the quantitatively different relationships of peak position in the red band of the remote sensing reflectance vs. Chl concentration are found in the bloom waters of the diatom Skeletonema costatum and the dinoflagellate Prorocentrum donghaiense in coastal areas of the East China Sea. Model simulations of remote sensing reflectance, Rrs, accounting for the influence of variations in the bio-optical parameters such as chlorophyll fluorescence quantum efficiency, Φ, and specific absorption coef- ficient, aph , are carried out to analyze the characteristics of this spectral peak. The strong effect of fluorescence on the magnitude of Rrs results in the inhibition of the shift of the peak to longer wavelengths, increasing Φ enhances this effect. Increasing aph , specifically in the red-wavelength band, causes a sharper shift in the red peak position by decreasing the effect of the fluorescence. The dominant parameter governing the slope of the shift is aph . The analysis indicates that the higher aph of S. costatum in the red region is primarily respon- sible for the much higher slope of the peak shift than for that of P. donghaiense. We show that the relationship between the peak position and Chl concentration may be useful for discriminating S. costatum blooms from those due to P. donghaiense, although information about chlorophyll fluorescence quantum efficiency should be included. Finally, we show that using the band ratio Rrs(708 nm)/Rrs(665 nm) instead of Chl in the relation- ship with peak position can be useful for the practical identification of S. costatum blooms from hyperspectral measurements of remote sensing reflectance.

Optical detection of Prorocentrum donghaiense blooms based on multispectral reflectance

Prorocentrum donghaiense is one of the most common red tide causative dinoflagellates in the Changjiang (Yangtze) River Estuary and the adjacent area of the East China Sea. It causes large-scale blooms in late spring and early summer that lead to widespread ecologic and economic damage. A means for distinguishing dinoflagellate blooms from diatom(Skeletonema costatum) blooms is desired. On the basis of measurements of remote sensing reflectance [Rrs(λ)] and inherent optical parameters, the potential of using a multispectral approach is assessed for discriminating the algal blooms due to P. donghaiense from those due to S. costatum. The behavior of two reflectance ratios [R1 = Rrs(560)/Rrs (532) and R2 = Rrs(708)/Rrs(665)], suggests that differentiation of P. donghaiense blooms from diatom bloom types is possible from the current band setup of ocean color sensors. It is found that there are two reflectance ratio regimes that indicate a bloom is dominated by P. donghaiense: (1) R1 > 1.55 and R2 < 1.0 or (2) R1 > 1.75 and R2 ⩾ 1.0. Various sensitivity analyses are conducted to investigate the effects of the variation in varying levels of chlorophyll concentration and colored dissolved organicmatter (CDOM) as well as changes in the backscattering ratio (bbp/bp) on the efficacy of this multispectral approach. Results indicate that the intensity and inherent optical properties of the algal species explain much of the behavior of the two ratios. Although backscattering influences the amplitude of Rrs(λ), especially in the 530 and 560 nm bands, the discrimination between P. donghaiense and diatoms is not significantly affected by the variation of bbp/bp. Since aCDOM(440) in coastal areas of the ECS is typically lower than 1.0 m−1 in most situations, the presence of CDOM does not interfere with this discrimination, even as SCDOM varies from 0.01 to 0.026 nm−1. Despite all of these effects, the discrimination of P. donghaiense blooms from diatom blooms based on multispectral measurements of Rrs(λ) is feasible.

Detection of water quality parameters in Hangzhou Bay using a portable laser fluorometer

A field, light-weight laser fluorometer based on the method of laser induced fluorescence was developed for water quality monitoring. The basic instrument configuration uses a high pulse repetition frequency microchip laser, a confocal reflective fluorescent probe and a broadband hyperspectral micro spectrometer; it weights only about 1.7 kg. Simultaneous estimates of three important water quality parameters, namely, chlorophyll a (chl-a), colored dissolved organic matter (CDOM), and total suspended matter (TSM) measured by the laser fluorometer were observed to agree well with those measured by traditional methods (0.27-0.84 μg L(-3) chl-a, R(2)=0.88; 0.104-0.295 m(-)(1) CDOM absorption, R(2)=0.90; and 59.8-994.9 mg L(-)(3) TSM, R(2)=0.86) in Hangzhou Bay water. Subsequently, distribution and characteristics of CDOM and chl-a laser fluorescence in Hangzhou Bay were analyzed, which will enhance our understanding of biogeochemical processes in this complex estuarine system at high-resolution, high-frequency and long-term scale.

The extremely high concentration of suspended particulate matter in Changjiang Estuary detected by MERIS data

The Changjiang River is the third largest river of the annual flux around the world, which has a great impact on the ecosystem of the East China Sea and adjacent areas. Because of the shallow water, tide mixing and the runoff of the Changjiang River and Qiantang River, the suspended particulate matter (SPM) concentration is extremely high in the Changjiang Estuary, which is ever up to 2000mg/L. Due to the large water-leaving radiance at the near-infrared wavelength, the operational atmospheric correction algorithm for the open ocean can not be applied to this region, and the existing remote sensing algorithms for SPM may not be applicable for this extremely high turbidity waters. In this paper, we firstly apply the blue wavelength atmospheric correction algorithm to MERIS Level-1 data to get the reasonable spectral water-leaving radiances in the Changjiang Estuary. Based on the winter cruise data in 2007, a regional SPM algorithm was developed using the bands ratio of the normalized water-leaving radiances between 779nm and 560nm. This algorithm was validated by the summer cruise data in 2006, and the results show that the performance of the algorithm was very well, and there was good agreement between the retrieved data and in-situ measured concentrations of the SPM in the Changjiang Estuary, with the correlation coefficient of 0.98 in the logarithm form and the averaged absolute relative error of 27.2%, and the standard deviation of 20.8mg/l in the linear form. Finally, the seasonal variations of the SPM in the Changjiang Estuary were analyzed by the MERIS SPM maps retrieved by the algorithms developed in this paper.

A new algorithm based on the background field for red tide monitoring in the East China Sea

Remote sensing has been proven to be an effective means of monitoring red tides. The spectral information is an important basis for establishing a model to monitor red tides. The spectral curves of red tide events are analyzed and compared with multiyear monthly averaged spectral curves based on MODIS data from July 2002 to June 2012, as well as spectral differences at the same location during red tide presence and absence. A red tide monitoring algorithm is developed based on the background field to extract the red tide information of the East China Sea (ECS). With the application of the algorithm in the ECS, the results reveal that the developed model can effectively determine the location of red tides, with good correspondence to the results from an official bulletin. This demonstrates that the algorithm can effectively extract the red tide information.

A dynamic sediment model based on satellite‐measured concentration of the surface suspended matter in the East China Sea

The concentration of total suspended matter (TSM) at the sea surface is derived from satellite data using a complex proxy TSM model in East China Sea from 1997 to 2008. The structure of the mean TSM image is similar to that of the topography, indicating that the distribution of the surface concentration is strongly related to the water depth. A dynamic sediment model (DSM) is constructed to relate the TSM concentration at the sea surface with suspended sediment at the benthic boundary layer, the Rouse number, and the water depth. The DSM model is improved through iteration with a convergence identified by the mean relative difference between two adjacent bottom TSM images which becomes smaller with the more iterations and the value is less than 1% after 50 iterations. The performance of the DSM model is validated by satellite-measured concentration with a mean relative error of 5.2% for the monthly mean images. The DSM model is used to deduce the bottom TSM concentration at the benthic boundary layer and the distribution of the Rouse number. The spatial distribution of the sea surface TSM concentration is determined predominately by both the bottom suspended sediment concentration and water depth. The temporal variation of the sea surface concentration mainly depends upon the Rouse number in the water column. Our result shows that the discharge of the Changjiang River can change the distribution of the Rouse number to form a band-shaped region in the Changjiang Estuary. The DSM model provides a framework for understanding some of the mechanisms of the formation and variation of the primary TSM plume and the secondary plume in the ECS. The primary TSM plume corresponds approximately to the region with depth shallower than 20 m and the secondary plume corresponds to the region with depths between 20 and 50 m.

Detecting the red tide based on remote sensing data in optically complex East China Sea

Red tide not only destroys marine fishery production, deteriorates the marine environment, affects coastal tourist industry, but also causes human poison, even death by eating toxic seafood contaminated by red tide organisms. Remote sensing technology has the characteristics of large-scale, synchronized, rapid monitoring, so it is one of the most important and most effective means of red tide monitoring. This paper selects the high frequency red tides areas of the East China Sea as study area, MODIS/Aqua L2 data as the data source, analysis and compares the spectral differences in the red tide water bodies and non-red tide water bodies of many historical events. Based on the spectral differences, this paper develops the algorithm of Rrs555/Rrs488> 1.5 to extract the red tide information. Apply the algorithm on red tide event happened in the East China Sea on May 28, 2009 to extract the information of red tide, and found that the method can determine effectively the location of the occurrence of red tide; there is a good corresponding relationship between red tide extraction result and chlorophyll a concentration extracted by remote sensing, shows that these algorithm can determine effectively the location and extract the red tide information.

A semianalytical MERIS green‐red band algorithm for identifying phytoplankton bloom types in the East China Sea

A new bio-optical algorithm based on the green and red bands of the Medium Resolution Imaging Spectrometer (MERIS) is developed to differentiate the harmful algal blooms of Prorocentrum donghaiense Lu (P. donghaiense) from diatom blooms in the East China Sea (ECS). Specifically, a novel green-red index (GRI), actually an indicator for a(510) of bloom waters, is retrieved from a semi-analytical bio-optical model based on the green and red bands of phytoplankton-absorption and backscattering spectra. In addition, a MERIS-based diatom index (DIMERIS) is derived by adjusting a Moderate Resolution Imaging Spectroradiometer (MODIS) diatom index algorithm to the MERIS bands. Finally, bloom types are effectively differentiated in the feature spaces of the green-red index and DIMERIS. Compared with three previous MERIS-based quasi-analytical algorithm (QAA) algorithms and three existing classification methods, the proposed GRI and classification method have the best discrimination performance when using the MERIS data. Further validations of the algorithm by using several MERIS image series and near-concurrent in-situ observations indicate that our algorithm yields the best classification accuracy and thus can be used to reliably detect and classify P. donghaiense and diatom blooms in the ECS. This is the first time that the MERIS data have been used to identify bloom types in the ECS. Our algorithm can also be used for the successor of the MERIS, the Ocean and Land Color Instrument, which will aid the long-term observation of species succession in the ECS. This article is protected by copyright. All rights reserved.

An improved profiling method for the measurement of hyperspectral diffuse attenuation coefficents in shallow turbid waters

The measurement of hyperspectral diffuse attenuation coefficients (Kd(λ)) in shallow turbid waters cannot be successfully achieved by the original Satlantic profiling system, because of less data available in the near-surface waters due to the rapid decrease of light intensity. In this paper, an improved profiling system and processing method are proposed. Firstly, a convenient buoyancy device is designed and mounted on the Satlantic Profiler II to allow the profiler to loiter close to the sea surface, thereby significantly improving the vertical sampling resolution to 1cm/s in near-surface waters, particularly in the depth between 0 and 1 meter. In addition, customized processing software CProSoft is developed to subjectively select the depths for various wavelengths that meet their different requirement for regression analysis. Comparison with original system results shows that our novel method can significantly improve the accuracy of Kd(λ) measurements especially in the short blue and red spectral range, and can even effectively derive near-surface Kd values in the extremely turbid waters with attenuation coefficients greater than 30 m-1, which dramatically enlarge the Kd(λ) measuring range

A new algorithm based on spectral differences for red tide monitoring in the East China Sea

Red tide not only destroys marine fishery production and deteriorates the marine environment, it also causes human health problems. In China, the East China Sea has a high incidence of red tide disasters. Remote sensing technology has been proven an effective means of monitoring red tides. Spectral information of red tide water is an important basis for establishing red tide remote sensing monitoring models. This paper analyzes and compares the differences between red tide event spectral curves and multiyear monthly averaged spectral curves of MODIS data from July 2002 to June 2012, and develops a red tide monitoring algorithm based on the background field, to extract red tide information of the East China Sea. With the application of the algorithm in the East China Sea, it reveals that it can effectively determine the location of red tide and extract red tide information.