Towards a unified approach for remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters

In this study we tested the applicability of a method, originally developed for terrestrial plant leaves, to retrieve chlorophyll-a concentrations from reflectance spectra of turbid productive waters. We tuned the conceptual model according to the optical characteristics of the aquatic medium, and accurately predicted chlorophyll-a concentrations in water bodies over a wide range of optical conditions. Our results provide evidence that this technique may be considered as a general solution, independent of the type of medium, for assessing chlorophyll concentration in optically deep media using remotely sensed data

Underway spectrophotometry along the Atlantic Meridional Transect reveals high performance in satellite chlorophyll retrievals

To evaluate the performance of ocean-colour retrievals of total chlorophyll-a concentration requires direct comparison with concomitant and co-located in situ data. For global comparisons, these in situ match-ups should be ideally representative of the distribution of total chlorophyll-a concentration in the global ocean. The oligotrophic gyres constitute the majority of oceanic water, yet are under-sampled due to their inaccessibility and under-represented in global in situ databases. The Atlantic Meridional Transect (AMT) is one of only a few programmes that consistently sample oligotrophic waters. In this paper, we used a spectrophotometer on two AMT cruises (AMT19 and AMT22) to continuously measure absorption by particles in the water of the ship\u27s flow-through system. From these optical data continuous total chlorophyll-a concentrations were estimated with high precision and accuracy along each cruise and used to evaluate the performance of ocean-colour algorithms. We conducted the evaluation using level 3 binned ocean-colour products, and used the high spatial and temporal resolution of the underway system to maximise the number of match-ups on each cruise. Statistical comparisons show a significant improvement in the performance of satellite chlorophyll algorithms over previous studies, with root mean square errors on average less than half (~0.16 in log10 space) that reported previously using global datasets (~0.34 in log10 space). This improved performance is likely due to the use of continuous absorption-based chlorophyll estimates, that are highly accurate, sample spatial scales more comparable with satellite pixels, and minimise human errors. Previous comparisons might have reported higher errors due to regional biases in datasets and methodological inconsistencies between investigators. Furthermore, our comparison showed an underestimate in satellite chlorophyll at low concentrations in 2012 (AMT22), likely due to a small bias in satellite remote-sensing reflectance data. Our results highlight the benefits of using underway spectrophotometric systems for evaluating satellite ocean-colour data and underline the importance of maintaining in situ observatories that sample the oligotrophic gyres

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in‐water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

Isolation of optical signatures of phytoplankton pigments in turbid productive waters: Remote assessment of chlorophyll-a

Field-based collection of discrete measurements and laboratory analysis of water samples is the traditional methodology for monitoring the quality of turbid productive inland lakes. Despite its widespread use, this methodology can be limited by time and financial constraints when time-series of data are required over vast geographic regions. Remote sensing of lake water quality has the potential to overcome these limitations by complementing traditional monitoring techniques. The main objective of this study was to develop robust remote-sensing algorithms for estimating chlorophyll-a concentration (Chl) in turbid productive waters. A large set of reflectance and absorption spectra as well as relevant water quality parameters was collected over a period of three years in Nebraska lakes of different origins and morphometrics. A conceptual model originally developed for remote sensing of terrestrial vegetation, was tuned according to the optical characteristics of turbid productive waters and successfully used to predict Chl of independent data sets. The model relates Chl to a combination of three reflectance bands located in the red and near-infrared (NIR) spectral regions. NIR-to-red reflectance ratios can be viewed as a special case of this model. By means of simulated reflectance spectra, the sensitivity of these algorithms to variations in bio-optical parameters and reflectance uncertainties was studied. It was shown that the accuracy of Chl estimation depends strongly on the phytoplankton specific inherent optical properties as well as on reflectance uncertainties. On the other hand, the algorithms appeared to be robust with respect to variations in other bio-optical parameters such as the concentration of total suspended particles and the Chl fluorescence quantum yield. Finally, the potential of applying NIR-to-red reflectance ratios to existing ocean color sensors was demonstrated

Absorption Properties of Dissolved and Particulate Matter in Turbid Productive Inland Lakes

The objective of this study is to extend the knowledge on the absorption properties of turbid productive lakes by describing the spectral characteristics of aCDOM, anap and aφ spectra measured in an agriculturally dominated region of North America (Nebraska, USA)

Effect of Bio-Optical Parameter Variability and Uncertainties in Reflectance Measurements on the Remote Estimation of Chlorophyll-a Concentration in Turbid Productive Waters: Modeling Results

Most algorithms for retrieving chlorophyll-a concentration (Chla) from reflectance spectra assume that bio-optical parameters such as the phytoplankton specific absorption coefficient (aφ*) or the chlorophyll-a fluorescence quantum yield (η) are constant. Yet there exist experimental data showing large ranges of variability for these quantities. The main objective of this study was to analyze the sensitivity of two Chla algorithms to variations in bio-optical parameters and to uncertainties in reflectance measurements. These algorithms are specifically designed for turbid productive waters and are based on red and near-infrared reflectances. By means of simulated data, it is shown that the spectral regions where the algorithms are maximally sensitive to Chla overlap those of maximal sensitivity to variations in the above bio-optical parameters. Thus, to increase the accuracy of Chla retrieval, we suggest using spectral regions where the algorithms are less sensitive to Chla, but also less sensitive to these interferences. aφ* appeared to be one of the most important sources of error for retrieving Chla. However, when the phytoplankton backscattering coefficient (bb,φ) dominates the total backscattering, as is likely during algal blooms, variations in the specific (bb,φ) may introduce large systematic uncertainties in Chla estimation. Also, uncertainties in reflectance measurements, which are due to incomplete atmospheric correction or reflected skylight removal, seem to affect considerably the accuracy of Chla estimation. Instead, variations in other bio-optical parameters, such as η or the specific backscattering coefficient of total suspended particles, appear to have minor importance. Suggestions regarding the optimal band locations to be used in the above algorithms are finally provided

Effect of Bio-Optical Parameter Variability on the Remote Estimation of Chlorophyll-a Concentration in Turbid Productive Waters: Experimental Results

The analytical development and underlying hypothesis of a three-band algorithm for estimating chlorophyll-a concentration ([Chla]) in turbid productive waters are presented. The sensitivity of the algorithm to the spectral location of the bands used is analyzed. A large set of experimental observations ([Chla] varied between 4 and 217 mg m-3 and turbidity between 2 and 78 nephelometric turbidity units) was used to calibrate and validate the algorithm. It was found that the variability of the chlorophyll-a fluorescence quantum yield and of the chlorophyll-a specific absorption coefficient can reduce considerably the accuracy of remote predictions of [Chla]. Instead of parameterizing these interferences, their effects were minimized by tuning the spectral regions used in the algorithm. This allowed us to predict [Chla] with a relative root-mean-square error of less than 30%

Underway and moored methods for improving accuracy in measurement of spectral particulate absorption and attenuation

Optical sensors have distinct advantages when used in ocean observatories, autonomous platforms, and on vessels of opportunity, because of their high-frequency measurements, low power consumption, and the numerous established relationships between optical measurements and biogeochemical variables. However, the issues of biofouling and instrument stability over time remain complicating factors when optical instruments are used over periods longer than several days. Here, a method for obtaining calibration-independent measurements of spectral particle absorption and attenuation is presented. Flow-through optical instrumentation is routinely diverted through a large-surface area 0.2-μm cartridge filter, allowing for the calculation of particle optical properties by differencing temporally adjacent filtered and whole water samples. This approach yields measurements that are independent of drift in instrument calibration. The method has advantages not only for coastally moored deployments, but also for applications in optically clear waters where uncertainties in instrument calibration can be a significant part of the signal measured. The differencing technique is demonstrated using WET Labs (Philomath, Oregon) ac-9 and ac-s multi- and hyperspectral absorption and attenuation meters. For the ac-s sensor, a correction scheme is discussed that utilizes the spectral shape of water absorption in the near-infrared to improve the accuracy of temperature and scattering-corrected spectra. Flow-through particulate absorption measurements are compared with discrete filter-pad measurements and are found to agree well (R = 0.77; rmse = 0.0174 m ). © 2010 American Meteorological Society. 2 -