A multispectral remote sensing study of coastal waters off Vancouver Island

In March 1996, a multispectral aircraft survey of the coastal waters off Vancouver Island was carried out using a Compact Airborne Spectrographic Imager (CASI). This survey was combined with in situ measurements of water properties (phytoplankton composition, phytoplankton pigments, absorption spectra of phytoplankton, and concentration of dissolved organic carbon, or DOC). Comparison of the phytoplankton absorption data from this experiment with similar data from other regions shows that phytoplankton community has a significant impact on the spectral form and magnitude of absorption spectra, when normalized to unit chlorophyll-a. Concurrent measurements of in situ properties and aircraft data were obtained at eight stations. The in situ measurements of phytoplankton absorption and estimates of downwelling irradiance based on a clear-sky atmospheric-transmission model are used as inputs to a model of water-leaving irradiance. The modelled irradiances are compared with the remotely sensed values of water-leaving radiances. The observed differences between model and observation are used to evaluate the potential influence of DOC on water-leaving radiance. Practical difficulties of separating the phytoplankton signal from that of the coloured component of DOC (also known as yellow substance) are examined. Algorithms for estimation of the concentration of chlorophyll-a (the major phytoplankton pigment) can be based on their absorption or fluorescence properties. The distribution of chlorophyll-a in the study area is estimated using both these approaches, and possible causes for the observed discrepancies are discussed.     

Detecting photosynthetic algal pigments in natural populations using a high-spectral-resolution spectroradiometer

Reflectance data from a high spectral resolution spectroradiometer were obtained onboard a ship in Plymouth coastal waters. These data were analysed to detect algal photosynthetic accessory pigments for comparison with absorption spectra as measured in the laboratory by a spectrophotometer. The overall spectral characteristics of Plymouth waters allowed identification as to population composition. Derivative analysis of the spectra was used to resolve characteristic peaks of specific pigments. It was determined that chlorophyll pigments, a specific carotenoid and sea water absorption bands were detectable in the reflectance data. Absorption bands of photosynthetic and accessory pigments were assessed through chromatographic pigment analysis.     

Spectral absorption properties of dissolved and particulate matter in Lake Erie

Spectral absorption properties of particulate and dissolved matter were determined for Lake Erie waters in order to investigate the natural variability of the absorption coefficients required as inputs to optical models for converting satellite observations of water colour into water quality information. Particulate absorption measured using the quantitative filter technique yielded absorption spectra containing a fraction that could not be attributed to phytoplankton pigments, living heterotrophs, mineral sediments, or organic detritus but were indicative of additional absorption by a fraction of dissolved organic matter present in colloidal and/or particle-bound form. Erroneously high phytoplankton absorption coefficients measured at short wavelengths using the filter technique suggested that this particle-bound DOM is removed along with phytoplankton pigments during bleaching by sodium hypochlorite and as such is mistakenly incorporated into the phytoplankton absorption signal. Observations suggest that the selective sorption of fractions of DOM onto suspended particles may be responsible for significant variability in the absorption coefficients of particulate and dissolved matter and may be an important contributor to the total spectral absorption signals in Lake Erie waters. This reservoir of coloured organic matter, which to date has not been seriously considered in the optical properties of coastal and inland waters, may produce significant uncertainties in the parameterization of optical models and the interpretation of in situ and remotely sensed aquatic colour signals.     

Remote sensing of phytoplankton pigments: A comparison of empirical and theoretical approaches

Algorithms that have been used on a routine basis for remote sensing of the phytoplankton pigment, chlorophyll- a, from ocean colour data from satellite sensors such as the CZCS (Coastal Zone Color Scanner), SeaWiFS (Sea Viewing Wide Field-of-View Sensor) and OCTS (Ocean Colour and Temperature Scanner) are all of an empirical nature. However, there exist theoretical models that allow ocean colour to be expressed as a function of the inherent optical properties of seawater, such as the absorption coefficient and the backscattering coefficient. These properties can in turn be expressed as functions of chlorophyll- a, at least for the so-called Case 1 waters in which phytoplankton may be considered to be the single, independent variable responsible for most of the variations in the marine optical properties. Here, we use such a theoretical approach to model variations in ocean colour as a function of chlorophyll- a concentration, and compare the results with some empirical models in routine use. The parameters of phytoplankton absorption necessary for the implementation of the ocean colour model are derived from our database of over 700 observations of phytoplankton absorption spectra and concurrent measurements of phytoplankton pigments by HPLC (High Performance Liquid Chromatography) techniques. Since there are reports in the literature that significant differences exist in the performance of the algorithms in polar regions compared with lower latitudes, the model is first implemented using observations made at latitudes less than 50. It is then applied to the Labrador Sea, a high-latitude environment. Our results show that there are indeed differences in the performance of the algorithm at high latitudes, and that these differences may be attributed to changes in the optical characteristics of phytoplankton that accompany changes in the taxonomic composition of their assemblages. The sensitivities of the model to assumptions made regarding absorption by coloured dissolved organic matter (or yellow substances) and backscattering by particles are examined. The importance of Raman scattering on ocean colour and its influence on the algorithms are also investigated.     

Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean

Optical measurements including remote sensing provide a potential tool for the identification of dominant phytoplankton groups and for monitoring spatial and temporal changes in biodiversity in the upper ocean. We examine the application of an unsupervised hierarchical cluster analysis to phytoplankton pigment data and spectra of the absorption coefficient and remote-sensing reflectance with the aim of discriminating different phytoplankton assemblages in open ocean environments under non-bloom conditions. This technique is applied to an optical and phytoplankton pigment data set collected at several stations within the eastern Atlantic Ocean, where the surface total chlorophyll-a concentration (TChla) ranged from 0.11 to 0.62 mg m^− 3. Stations were selected on the basis of significant differences in the ratios of the two most dominant accessory pigments relative to TChla, as derived from High Performance Liquid Chromatography (HPLC) analysis. The performance of cluster analysis applied to absorption and remote-sensing spectra is evaluated by comparisons with the cluster partitioning of the corresponding HPLC pigment data, in which the pigment-based clusters serve as a reference for identifying different phytoplankton assemblages. Two indices, cophenetic and Rand, are utilized in these comparisons to quantify the degree of similarity between pigment-based and optical-based clusters. The use of spectral derivative analysis for the optical data was also evaluated, and sensitivity tests were conducted to determine the influence of parameters used in these calculations (spectral range, smoothing filter size, and band separation). The results of our analyses indicate that the second derivative calculated from hyperspectral (1 nm resolution) data of the phytoplankton absorption coefficient, a_ph(λ), and remote-sensing reflectance, R_rs(λ), provide better discrimination of phytoplankton pigment assemblages than traditional multispectral band-ratios or ordinary (non-differentiated) hyperspectral data of absorption and remote-sensing reflectance. The most useful spectral region for this discrimination extends generally from wavelengths of about 425-435 nm to wavelengths within the 495-540 nm range, although in the case of phytoplankton absorption data a broader spectral region can also provide satisfactory results.     

Estimation of optical properties of nearshore water

Most of the existing satellite sensors lack the spectral capabilities to discriminate phytoplankton pigments in water bodies. New satellite sensors (i.e. SeaWIFS) and future sensors on board EOS withnarrow bandwidths will provide fine spectral resolution necessary to distinguish optical properties of nearshore waters provided sea data are available. This will enable spaceborne water color sensors to discriminate bloom forming phytoplankton species. The objective was to develop a library of absorption spectra for the most common phytoplankton species found within the Hudson/Raritan Estuary and coastal waters of New Jersey. Both culture-grown and field samples of phytoplankton were concentrated and analyzedusing chemical and spectrometric techniques. Using spectral derivative and polynomial regression analysis, it was possible to identify wavelengths that could be used to characterize the pigment compositions of phytoplankton species in the estuary.     

Remote sensing of phytoplankton community composition along the northeast coast of the United States

Satellite imagery has proven to be a powerful tool for measuring chlorophyll a in surface waters. While this provides an estimate of total phytoplankton biomass, it does not distinguish between phytoplankton groups, many of which have functional differences and therefore affect biogeochemical cycles differently. Phytoplankton pigment analysis has been used to quantify a wide range of photosynthetic and accessory pigments, and chemotaxonomic analysis (e.g. CHEMTAX) has been used to successfully quantify functional taxonomic groups in nature based on pigment distributions. Here, we combine CHEMTAX analysis with satellite-derived distributions of specific phytoplankton pigments to describe the distributions of particular components of the phytoplankton community in the northeast coast of the United States from space. The spatial and seasonal variations in phytoplankton community structure elucidated through satellite remote sensing methods generally agreed with observations of abundance estimates of cell counts. Diatoms were generally the most abundant phytoplankton in this region, especially during Winter-Spring and in the inner shelf, but phytoplankton populations shifted to increasing abundance of other taxa during Summer, especially offshore. While still preliminary, satellite-derived taxa-specific information with proper regional controls holds promise for providing information on phytoplankton abundance to a taxonomic group level which would greatly improve our understanding of the impacts of human activity and climate change on ecosystems.     

Absorption spectrum of phytoplankton pigments derived from hyperspectral remote-sensing reflectance

For a data set collected around Baja California with chlorophyll-a concentration ((chl-a)) ranging from 0.16 to 11.3 mg/m³, hyperspectral absorption spectra of phytoplankton pigments were independently inverted from hyperspectral remote-sensing reflectance using a newly developed ocean-color algorithm. The derived spectra were then compared with those measured from water samples using the filter-pad technique, and an average difference of 21.4% was obtained. These results demonstrate that the inversion algorithm worked quite well for the coastal waters observed and suggest a potential of using hyperspectral remote sensing to retrieve both chlorophyll-a and other accessory pigments.     

Remote sensing of phytoplankton pigment distribution in the United States northeast coast

Phytoplankton pigments constitute many more compounds than chlorophyll a that can be applied to study phytoplankton diversity, populations, and primary production. In this study, field measurements were applied to develop ocean color satellite algorithms of phytoplankton pigments from in-water radiometry measurements. The match-up comparisons showed that the satellite-derived pigments from our algorithms agree reasonably well (e.g. 30-55% of uncertainty for SeaWiFS and 37-50% for MODIS-Aqua) to field data, with better agreement (e.g. 30-38% of uncertainty for SeaWiFS and 39-44% for MODIS-Aqua) for pigments abundant in diatoms. The seasonal and spatial variations of satellite-derived phytoplankton biomarker pigments, such as fucoxanthin, which is abundant in diatoms, peridinin, which is found only in peridinin-containing dinoflagellates, and zeaxanthin, which is primarily from cyanobacteria in coastal waters, revealed that higher densities of diatoms are more likely to occur on the inner shelf and during winter-spring and obscure other abundant phytoplankton groups. However, relatively higher densities of other phytoplankton, such as dinoflagellates and cyanobacteria, are likely to occur on the mid- to outer-continental shelf and during summer. Seasonal variation of riverine discharge may play an important role in stimulating algal blooms, in particular diatoms, while higher abundances of cyanobacteria coincide with warmer water temperatures and lower nutrient concentrations.     

Interpretation of the 685nm peak in water-leaving radiance spectra in terms of fluorescence,absorption and scattering,and its observation by MERIS

One of the major design goals of the Medium Resolution Imaging Spectrometer (MERIS) was the capability to use the signal from chlorophyll fluorescence stimulated by ambient sunlight to detect and map phytoplankton. This is considered tobe especially useful in coastal waters, where the determination of chlorophyll from water-leaving radiance spectra using the conventional blue/green ratio method is often complicated by high concentrations of gelbstoff and suspended matter. Based on a variety of studies, three spectral channels centred at 665, 681.25 and 705nm were included in the design of MERIS for retrieving the fluorescence signal. This paper presents observations with highresolution spectrometers which demonstrate the main factors affecting the observed signal in the red part of the spectrum. These factors are absorption by pure water, scattering by suspended particles, absorption and fluorescence of chlorophyll and the influence of submerged macrophyta. The influence of exceptional blooms such as 'red tides' on radiance spectra is also discussed. The paper shows how the combination of these effects can be understood using simple and easy-to-use radiative transfer models, and can be exploited by MERIS for improved mapping of phytoplankton, red tides and coastal, submerged and tidal flat vegetation.     

联用色谱完全重叠峰的解析方法

基于正交投影技术和约束峰形条件,本文提出了三种完全重叠色谱峰的解析方法,峰形约束曲线拟合解析（ＣＰＳＣＦ）,交替正交投影（ＩＯＰ）和秩消失因子分析（ＲＡＦＡ）。对联用色谱数据阵如果约束条件得到满足,谤些方法能被证明用于被嵌人组分的浓度曲线分放是完全可能地。     

运动模糊图像点扩散函数尺度鉴别

运动模糊图像的运动模糊方向被高精度地鉴别出来后,将之旋转到水平轴,则二维问题可简化为一维问题来处理。将旋转后的模糊图像在水平方向上进行一阶微分,然后在水平方向上求微分图像的自相关,并将自相关图像的各列加起来,得到一条鉴别曲线,在鉴别曲线上的零频尖峰两侧,会对称地出现一对共轭的负相关峰,两负相关峰间的距离等于运动模糊点扩散函数尺度的两倍。这一新的运动模糊点扩散函数尺度鉴别方法,不仅适用于匀速运动模糊尺度鉴别,也适用于振动、加速运动等变速直线运动的模糊尺度鉴别,而且具有很强的抗噪声干扰能力,鉴别精度高。文中借用信息光学中用于目标识别的光学联合变换相关器JTC概念,给出了该新鉴别方法的解析理论分析。     

Interference of salt and moisture on soil reflectance spectra

This article portrays the effects of salt and moisture on soil reflectance spectra and their consequent influences on the estimation of soil salinity and soil moisture contents (SMC). It is amid to demonstrate and discuss how the interference of salt and moisture, as soil constituents, on soil spectra can affect the estimation of either soil salinity or SMC when spectral variabilities are used as predictive variables. To achieve this objective, a data set was obtained from a test area where soil salinity and SMC were largely varied. Furthermore, the Inverted Gaussian (IG) modelling approach, which has been successfully used for the estimation of soil salinity under laboratory conditions and for the estimation of SMC for non-saline soil, is used in this study. Using the IG function, the near-infrared (NIR) and the shortwave infrared (SWIR) regions of the salt-affected soil spectra, with various amount of moisture, were fitted to an IG curve. Parameters of the fitted curve such as functional depth, distance to the inflection point and area under the curve were then used as predictors in a multi-regression analysis to quantify the effect of soil salinity and SMC on soil spectra. The results suggest that a combination of salt and moisture in soil causes anomalies and therefore variations in neither salt nor moisture contents can be modelled accurately on the basis of quantification of soil reflectance. These results suggest that further studies are required to determine a set of calibrating coefficients that can be used to eliminate the background spectral effects caused by either soil salinity or SMC.     

Sea surface colour in the field of biological oceanography

Abstract

Variations of marine surface optical properties (generally grouped under the term ‘sea surface colour’) are due to dissolved and suspended materials, with different absorption and scattering characteristics, present in sea water. Remote assessments of sea surface colour, therefore, can be used to determine the presence and abundance of water constituents such as biological pigments, suspended sediments or other products of organic matter degradation (the so-called yellow substance). In open sea waters, the pigments due to biological activities, and particularly phytoplankton chlorophyll-like pigments, are the main contributors to surface colour. Hence, observations in the visible spectrum can provide synoptic and repetitive information on parameters linked to biological production and patchiness, or bio-geo-chemical cycles in general. Since water constituents act as tracers of various marine processes, bio-optical patterns on the sea surface can also provide indications about the relationships existing between forcing mechanisms and biological response in the marine environment. These capabilities render optical remote sensing an invaluable tool in the field of biological oceanography, although atmospheric processes and signal ambiguities in the water column may pose severe limitations on this technique. The feasibility and potential of passive remote sensing in the visible spectrum have been demonstrated primarily by the Coastal Zone Color Scanner (CZCS) experiment. Important results of this experiment have been reported in the study of coastal phenomena, sediment transport, frisheries, upwelling, climatic events, and factors controlling the distribution, growth and fate of phytoplankton. On these latter topics, indications of a strong coupling between dynamical and bio-optical conditions of the marine environment are emerging from the analysis of CZCS image series, for open ocean, near-coastal and enclosed basin conditions. Examples of such studies, covering regions of both the North Atlantic and North Pacific Oceans and of the Mediterranean Sea, provide clues on the promises of large-scale sea surface colour assessments in the field of biological oceanography.     

An evaluation of algorithms for the remote sensing of cyanobacterial biomass

Most remote sensing algorithms for phytoplankton in inland waters aim at the retrieval of the pigment chlorophyll a (Chl a), as this pigment is a useful proxy for phytoplankton biomass. More recently, algorithms have been developed to quantify the pigment phycocyanin (PC), which is characteristic of cyanobacteria, a phytoplankton group of relative importance to inland water management due to their negative impact on water quality in response to eutrophication.We evaluated the accuracy of three published algorithms for the remote sensing of PC in inland waters, using an extensive database of field radiometric and pigment data obtained in the Netherlands and Spain in the period 2001–2005. The three algorithms (a baseline, single band ratio, and a nested band ratio approach) all target the PC absorption effect observed in reflectance spectra in the 620 nm region. We evaluated the sensitivity of the algorithms to errors in reflectance measurements and investigated their performance in cyanobacteria-dominated water bodies as well as in the presence of other phytoplankton pigments.All algorithms performed best in moderate to high PC concentrations (50–200 mg m^? 3) and showed the most linear response to increasing PC in cyanobacteria-dominated waters. The highest errors showed at PC < 50 mg m^? 3. In eutrophic waters, the presence of other pigments explained a tendency to overestimate the PC concentration. In oligotrophic waters, negative PC predictions were observed. At very high concentrations (PC > 200 mg m^? 3), PC underestimations by the baseline and single band ratio algorithms were attributed to a non-linear relationship between PC and absorption in the 620 nm region. The nested band ratio gave the overall best fit between predicted and measured PC. For the Spanish dataset, a stable ratio of PC over cyanobacterial Chl a was observed, suggesting that PC is indeed a good proxy for cyanobacterial biomass. The single reflectance ratio was the only algorithm insensitive to changes in the amplitude of reflectance spectra, which were observed as a result of different measurement methodologies.     

A robust baseline elimination method based on community information

Baseline correction is an important pre-processing technique used to separate true spectra from interference effects or remove baseline effects. In this paper, an adaptive iteratively reweighted genetic programming based on excellent community information (GPEXI) is proposed to model baselines from spectra. Excellent community information which is abstracted from the present excellent community includes an automatic common threshold, normal global and local slope information. Significant peaks can be firstly detected by an automatic common threshold. Then based on the characteristic that a baseline varies slowly with respect to wavelength, normal global and local slope information are used to further confirm whether a point is in peak regions. Moreover the slope information is also used to determine the range of baseline curve fluctuation in peak regions. The proposed algorithm is more robust for different kinds of baselines and its curvature and slope can be automatically adjusted without prior knowledge. Experimental results in both simulated data and real data demonstrate the effectiveness of the algorithm.     

小波分析在活体浮游植物离散三维荧光光谱特征提取及识别中的应用研究

为了区分和识别不同属的浮游植物,选择了Daubechies-3小波的二阶低频分量对10种浮游植物的离散三维光谱进行了特征提取.Bayes判别分析结果表明此类特征谱对不同属间浮游植物的正确判别率可达96.75%.利用非负最小二乘法,依据此类特征谱建立的标准谱库可对加入不同噪声的某些藻进行100%的定性识别.可对绝大多数混合样中优势种进行定性识别;并可使某些优势种的识别量达到真实量的75% 以上.小波分析可对浮游植物在属的层次上进行有效的特征提取.     

紫外可见光谱结合主成分分析对文物颜料光致变色的评价研究

通过模拟博物馆馆藏环境搭建了颜料光致变色研究的实验装置,采用漫反射紫外可见光谱技术对古书画、壁画等常用的朱砂、朱磦、胭脂、三绿、三青颜料在365nm紫外光照射下的变色规律进行了考察,并利用主成分分析对光谱数据进行分析,进一步对其变色规律进行研究。结果显示,朱砂、朱磦、胭脂三种颜料的光谱呈"S"型,它们对365nm紫外光的稳定性依次为朱磦、朱砂、胭脂;三绿和三青的光谱呈"钟"型,三绿的稳定性好于三青。所建立的漫反射紫外可见光谱方法为颜料光致褪色的规律及机理研究提供了新的无损分析手段。     

The effect of phytoplankton pigment composition and packaging on the retrieval of chlorophyll-a concentration from satellite observations in the Southern Ocean

The Antarctic waters are known to be optically unique and the standard empirical ocean colour algorithms applied to these waters may not address the regional bio-optical characteristics. This article sheds light on the performance of current empirical algorithms and a regionally optimized algorithm (ROA) for the retrieval of chlorophyll-a (chl-a) concentration from Aqua-Moderate Resolution Imaging Spectroradiometer (Aqua-MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) in the Indian Ocean Sector of Southern Ocean (IOSO). Analysis indicated that empirical algorithms used for the retrieval of chl-a concentration from Aqua-MODIS and SeaWiFS underestimate by a factor varying from 2 to 2.9, resulting in underestimation when in situ chl-a exceeds about 0.3 mg m^?3. To explain these uncertainties, a study was carried out to understand the effect of phytoplankton pigment composition and pigment packaging on remote-sensing reflectance (R_rs,λ), from the analysis of phytoplankton-specific absorption coefficient (a_ph,*_λ). The spatial variation of phytoplankton groups analysed using diagnostics pigments (DP) indicated shifting of the phytoplankton community structure from offshore to coastal Antarctic, with a significant increasing trend for diatoms and a decreasing trend for haptophytes population. The diatom-dominated population exhibits lower a_ph,*_λ in the 405–510 nm region (with relative flattening in 443–489 nm) compared with the a_ph,*_λ spectra of the haptophytes-dominated population that peaks near 443 nm. The flattening of a_ph,*_λ spectra for the diatom-dominated population was attributed to its larger cell size, which leads to pigment packaging (intracellular shading) and in turn results in higher R_rs,λ. The relationship between pigment composition (normalized by chl-a) and blue:green absorption band ratios (a_ph,*₄₄₃:a_ph,*₅₅₅ and a_ph,*₄₈₉:a_ph,*₅₅₅) corresponding to the Aqua-MODIS and SeaWiFS bands showed in-phase associations with most of the pigments such as 19?-hexanoyloxyfucoxanthin, 19?-butanoyloxyfucoxanthin, peridinin, and zeaxanthin. In contrast, the out-of-phase association observed between the blue:green absorption ratios and fucoxanthin indicated apparent deviations from the general pigment retrieval algorithms, which assumes that blue:green ratios vary in a systematic form with chl-a. The out-of-phase correspondence suggests that the increasing trend of fucoxanthin pigments towards the Antarctic coast was associated with the decreasing trend of blue:green absorption ratios and in turn results in higher R_rs,λ. Therefore, an increase in R_rs,λ leads to underestimation of chl-a from Aqua-MODIS and SeaWiFS in the IOSO region.     

An absorption model to determine phytoplankton size classes from satellite ocean colour

We have developed a model linking phytoplankton absorption to phytoplankton size classes (PSCs) that uses a single variable, the optical absorption by phytoplankton at 443 nm, a_ph(443), which can be derived from the inversion of ocean colour data. The model is based on the observation that the absolute value of a_ph(443) co-varies with the spectral slope of phytoplankton absorption in the range of 443-510 nm, which is also a characteristic of phytoplankton size classes. The model when used for analysis of SeaWiFS global data, showed that picoplankton dominated ~ 79.1% of surface waters, nanoplankton ~ 18.5% and microplankton the remainder (2.3%). The N. and S. Atlantic and the N. and S. Pacific Oceans showed seasonal cycles with both micro and nanoplankton increasing in spring and summer in each hemisphere, while picoplankton, dominant in the oligotrophic gyres, decreased in the summer. The PSCs derived from SeaWiFS data were verified by comparing contemporary 8-day composites with PSCs derived from in situ pigment data from quasiconcurrent Atlantic Meridional Transect cruises.