Wayne H. Slade

Acceptance angle effects on the beam attenuation in the ocean

The beam attenuation serves as a proxy for particulate matter and is a key parameter in visibility algorithms for the aquatic environment. It is well known, however, that the beam attenuation is a function of the acceptance angle of the transmissometer used to measure it. Here we compare eight different transmissometers with four different acceptance angles using four different deployment strategies and sites, and find that their mean attenuation values differ markedly and in a consistent way with instrument acceptance angle: smaller acceptance angles provide higher beam attenuation values. This difference is due to variations in scattered light collected with different acceptance angles and is neither constant nor easy to parameterize. Variability (in space or time) in the ratios of beam attenuations measured by two different instruments correlates, in most cases, with the particle size parameter (as expected from Mie theory), but this correlation is often weak and can be the opposite of expectations based on particle size changes. We recommended careful consideration of acceptance angle in applications of beam transmission data especially when comparing data from different instruments.

Effect of particulate aggregation in aquatic environments on the beam attenuation and its utility as a proxy for particulate mass

Marine aggregates, agglomerations of particles and dissolved materials, are an important particulate pool in aquatic environments, but their optical properties are not well understood. To improve understanding of the optical properties of aggregates, two related studies are presented. In the first, an in situ manipulation experiment is described, in which beam attenuation of undisturbed and sheared suspensions are compared. Results show that in the sheared treatment bulk particle size decreases and beam attenuation increases, consistent with the hypothesis that a significant fraction of mass in suspension is contained in fragile aggregates. Interestingly, the magnitude of increase in beam attenuation is less than expected if the aggregates are modeled as solid spheres. Motivated by this result, a second study is presented, in which marine aggregates are modeled to assess how the beam attenuation of aggregates differs from that of their constituent particles and from solid particles of the same mass. The model used is based on that of Latimer [Appl. Opt. 24, 3231 (1985)] and mass specific attenuation is compared with that based on homogeneous and solid particles, the standard model for aquatic particles. In the modeling we use recent research relating size and solid fraction of aquatic aggregates. In contrast with Mie theory, this model provides a rather size-insensitive mass specific attenuation for most relevant sizes. This insensitivity is consistent with the observations that mass specific beam-attenuation of marine particles is in the range 0.2-0.6m(2)/gr despite large variability in size distribution and composition across varied aquatic environments.

Calibrated near-forward volume scattering function obtained from the LISST particle sizer

The physical nature of particles, such as size, shape, and composition govern their angular light scattering, which is described by the volume scattering function (VSF). Despite the fact that the VSF is one of the most important inherent optical properties, it has rarely been measured in aquatic environments since no commercial instrument exists to measure the full VSF in the field. The commonly used LISST (Laser In Situ Scattering and Transmissometry) particle sizer (Sequoia Scientific, http://www.sequoiasci.com) measures near-forward angular scattering of a laser source (lambda= 670 nm) at 32 logarithmically-spaced photodetectors arranged between 0.08 and 15 degrees and inverts the data to obtain particle size distribution (PSD). In order to calibrate the LISST to provide the near-forward VSF of unknown particle suspensions, we analyzed the scattering of light by polystyrene bead suspensions of known size distributions and composition, and empirically compared it with the results of Mie theory. This (1) allowed us to obtain a set of instrument specific scaling factors needed to retrieve the magnitude of the VSF and (2) provided validation that the shape of the VSF was appropriately obtained.

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-mm 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 2 5 0.77; rmse 5 0.0174 m 21 ).

Effects of particle aggregation and disaggregation on their inherent optical properties

In many environments a large portion of particulate material is contained in aggregated particles; however, there is no validated framework to describe how aggregates in the ocean scatter light. Here we present the results of two experiments aiming to expose the role that aggregation plays in determining particle light scattering properties, especially in sediment-dominated coastal waters. First, in situ measurements of particle size distribution (PSD) and beam-attenuation were made with two laser particle sizing instruments (one equipped with a pump to subject the sample to aggregate-breaking shear), and measurements from the two treatments were compared. Second, clays were aggregated in the laboratory using salt, and observed over time by multiple instruments in order to examine the effects of aggregation and settling on spectral beam-attenuation and backscattering. Results indicate: (1) mass normalized attenuation and backscattering are only weakly sensitive to size changes due to aggregation in contrast to theory based on solid particles, (2) the spectral slope of beam-attenuation is indicative of changes in PSD but is complicated by instrument acceptance angle, and (3) the spectral shape of backscattering did not provide as clear a relationship with PSD as spectral beam attenuation, as is predicted by theory for solid spheres.

Computational Intelligence and its Applicationin Remote Sensing

Remote sensing observations provide a new global perspective of the Earth environment. Measurements from airborne and space borne sensor systems help scientists gain a better understanding of the complex interactions between the Earth’s atmosphere, oceans, ice regions and land surfaces, as well as human-induced change due to population growth and human activities. These remote sensing measurements are widely used in geographical, meteorological, and environmental studies. Technological advancements have resulted in an increase in the number of observation platforms and sensor capabilities (e.g., spectral and spatial resolution). This trend will continue and soon will produce an unprecedented volume of data. Information extracted from these datasets will support national research agendas and national applications that will exert an ever-increasing requirement for shorter processing times and greater data and algorithm accuracies. Hence, advanced mathematical techniques are needed to effectively analyze data generated from the rapidly growing remote sensing technology. For most geophysical retrieval algorithms, adding additional information to improve the measurement of in situ properties is not a simple task because of the nonlinear nature of the problem as well as computational difficulties. Moreover, most current mathematical techniques generally require a high level of scientific knowledge of the physical system to accurately analyze remotely sensed data. In contrast, computational intelligence (CI) techniques such as artificial neural networks, genetic algorithms, and fuzzy logic systems, provide the capability to better examine complex data without requiring detailed knowledge about the underlying physical system. For example, CI techniques have been used to accurately estimate bio-optical parameters in complex coastal aquatic environments from remotely sensed data by employing special features such as the ability to learn from data, adaptive behavior, handling of non-linear systems, flexibility towards the choice of inputs, and resilience against noise. For example, in satellite remote sensing of ocean color, most algorithms are based on regression (or empirical) models that use power and/or cubic polynomials to relate ratios of remotely sensed reflectance to bio-optical parameters such as chlorophyll

Ensemble neural network methods for satellite-derived estimation of chlorophyll /spl alpha/

In this paper, neural network-based methods incorporating ensemble learning techniques are presented that estimate chlorophyll /spl alpha/ (chl /spl alpha/) concentration in the coastal waters of the Gulf of Maine (GOM). A dataset was constructed consisting of in situ chl measurements from the GOM matched with satellite data from the sea-viewing wide-field-of-view sensor (SeaWiFS). These data were used to develop models using diverse neural network ensembles for estimation of chl /spl alpha/ concentration from satellite-retrieved ocean reflectances. Results indicate that the models are able to generalize across geographical and temporal variation, and are resilient to uncertainty such as that introduced by poor atmospheric correction, or radiance contributions from non-chl /spl alpha/ components in case 2 waters.

Characterizing the phytoplankton soup: pump and plumbing effects on the particle assemblage in underway optical seawater systems.

Many optical and biogeochemical data sets, crucial for algorithm development and satellite data validation, are collected using underway seawater systems over the course of research cruises. Phytoplankton and particle size distribution (PSD) in the ocean is a key measurement, required in oceanographic research and ocean optics. Using a data set collected in the North Atlantic, spanning different oceanic water types, we outline the differences observed in concurrent samples collected from two different flow-through systems: a permanently plumbed science seawater supply with an impeller pump, and an independent system with shorter, clean tubing runs and a diaphragm pump. We observed an average of 40% decrease in phytoplankton counts, and significant changes to the PSD in 10-45 µm range, when comparing impeller and diaphragm pump systems. Change in PSD seems to be more dependent on the type of the phytoplankton, than the size, with photosynthetic ciliates displaying the largest decreases in cell counts (78%). Comparison of chlorophyll concentrations across the two systems demonstrated lower sensitivity to sampling system type. Observed changes in several measured biogeochemical parameters (associated with phytoplankton size distribution) using the two sampling systems, should be used as a guide towards building best practices when it comes to the deployment of flow-through systems in the field for examining optics and biogeochemistry. Using optical models, we evaluated potential impact of the observed change in measured phytoplankton size spectra onto scattering measurements, resulting in significant differences between modeled optical properties across systems (~40%). Researchers should be aware of the methods used with previously collected data sets, and take into consideration the potentially significant and highly variable ecosystem-dependent biases in designing field studies in the future.

Remote identification of the invasive tunicate Didemnum vexillum using reflectance spectroscopy

Benthic coverage of the invasive tunicate Didemnum vexillum on Georges Bank is largely unknown. Monitoring of D. vexillum coverage is vital to understanding the impact this invasive species will have on the productive fishing grounds of Georges Bank. Here we investigate using reflectance spectroscopy as a method for remote identification of D. vexillum. Using two different systems, a NightSea Dive-Spec and a combination of LED light sources with a hyperspectral radiometer, we collected in-situ measurements of reflectance from D. vexillum colonies. In comparison to reflectance spectra of other common benthic substrates, D. vexillum appears to have a unique spectral signature between 500 and 600 nm. Measuring the slope of the spectrum between these wavelengths appears to be the most robust method for spectral identification. Using derivative analysis or principal component analysis, the reflectance spectra of D. vexillum can be identified among numerous other spectra of common benthic substrates. An optical system consisting of a radiometer, light source, and camera was deployed on a remotely operated vehicle to test the feasibility of using reflectance to assess D. vexillum coverage. Preliminary results, analyzed here, prove the method to be successful for the areas we surveyed and open the way for its use on large-scale surveys.