Alan Weidemann

Bio: Alan Weidemann is an academic researcher from United States Naval Research Laboratory. The author has contributed to research in topics: Ocean color & Radiance. The author has an hindex of 32, co-authored 103 publications receiving 3090 citations. Previous affiliations of Alan Weidemann include United States Department of the Navy.

Quantifying absorption by aquatic particles: A multiple scattering correction for glass-fiber filters

Abstract: : Absorption spectra measured for aquatic particles concentrated onto glass-fiber filters require a correction for the increase in pathlength caused by multiple scattering in the glass-fiber filter. A multiple scattering correction was calculated from optical density spectral for 48 phytoplankton cultures of seven species representing a variety of cell sizes, pigment groups, and call-wall types. The relationship between optical density in suspensions and on filters was not wavelength-dependent. Differences between blank filters were always spectrally neutral. Small differences between relationships for single species were inconclusive. Given the absence of wavelength-dependent effects, we report a single general quadratic relationship, OD(susp)(lambda) = 0.378 OD(filt)(lambda) + 0.523 OD(filt)(lambda)2 (r2 = 0.988), for correcting glass- fiber filter spectra. For independent samples, the average error in predicting OD(susp)(lambda) with this algorithm at any wavelength was 2%. Greatest errors were in spectral regions of low absorption. Absorption spectra for particles concentrated onto glass-fiber filters can be quantitatively corrected for multiple scattering within this limit. Applicability of the algorithm to field samples of varied composition was enhanced by using a large number of spectra and a range of cell types in algorithm development. Optical oceanography, Physical oceanography, Absorption, Scattering.

Euphotic zone depth: Its derivation and implication to ocean-color remote sensing

Abstract: [1] Euphotic zone depth, z1%, reflects the depth where photosynthetic available radiation (PAR) is 1% of its surface value. The value of z1% is a measure of water clarity, which is an important parameter regarding ecosystems. Based on the Case-1 water assumption, z1% can be estimated empirically from the remotely derived concentration of chlorophyll-a ([Chl]), commonly retrieved by employing band ratios of remote sensing reflectance (Rrs). Recently, a model based on water’s inherent optical properties (IOPs) has been developed to describe the vertical attenuation of visible solar radiation. Since IOPs can be nearanalytically calculated from Rrs, so too can z1%. In this study, for measurements made over three different regions and at different seasons (z1% were in a range of 4.3–82.0 m with [Chl] ranging from 0.07 to 49.4 mg/m 3 ), z1% calculated from Rrs was compared with z1% from in situ measured PAR profiles. It is found that the z1% values calculated via Rrs-derived IOPs are, on average, within � 14% of the measured values, and similar results were obtained for depths of 10% and 50% of surface PAR. In comparison, however, the error was � 33% when z1% is calculated via Rrs-derived [Chl]. Further, the importance of deriving euphotic zone depth from satellite ocean-color remote sensing is discussed.

Characteristics, distribution and persistence of thin layers over a 48 hour period

Abstract: The biological and physical processes contributing to planktonic thin layer dynamics were examined in a multidisciplinary study conducted in East Sound, Washington, USA between June 10 and June 25, 1998. The temporal and spatial scales characteristic of thin layers were determined using a nested sampling strategy utilizing 4 major types of platforms: (1) an array of 3 moored acoustical instrument packages and 2 moored optical instrument packages that recorded distributions and inten- sities of thin layers; (2) additional stationary instrumentation deployed outside the array comprised of meteorological stations, wave-tide gauges, and thermistor chains; (3) a research vessel anchored 150 m outside the western edge of the array; (4) 2 mobile vessels performing basin-wide surveys to define the spatial extent of thin layers and the physical hydrography of the Sound. We observed numerous occur- rences of thin layers that contained locally enhanced concentrations of material; many of the layers per- sisted for intervals of several hours to a few days. More than one persistent thin layer may be present at any one time, and these spatially distinct thin layers often contain distinct plankton assemblages. The results suggest that the species or populations comprising each distinct thin layer have responded to different sets of biological and/or physical processes. The existence and persistence of planktonic thin layers generates extensive biological heterogeneity in the water column and may be important in maintaining species diversity and overall community structure.

Phytoplankton spectral absorption as influenced by community size structure and pigment composition

Abstract: Assessments were made of the relative importance of package effects and pigment composition in contributing to variations in spectral absorption in shelf waters off North Carolina during May 1997 and off west Florida during October 1998. Measurements of spectral absorption of size-fractionated particulate material on glass fibre filters were made using two methods, the transmittance-reflectance (T-R) method and the quantitative filter technique (QFT). Spectral absorption of phytoplankton pigments was decomposed into a series of 13 Gaussian absorption bands, and absorption band peak heights were related to concentrations of major pigment classes. Maximum weight-specific pigment absorption coefficients for individual absorption bands (p* m ) derived from the fit of a hyperbolic tangent function to the data were found to be similar for North Carolina and west Florida shelf waters. The values were used to reconstruct spectral absorption in the absence of pigment packaging, which was then compared to measured absorption to provide an assessment of pigment packaging. Package effects were found to be responsible for up to a 62% reduction in the amplitude of major absorption bands, particularly for samples from low-salinity waters and for populations dominated by larger (>3 μm) phytoplankton. Variations in pigment composition were also found to have an impact, although it was smaller (10-28%), on variations in total absorption. Potential bio-optical applications of the Gaussian decomposition approach include the estimation of pigment concentrations from in situ or remotely sensed ocean colour observations. Alternatively, where pigment concentrations are known, it may be possible to estimate absorption. Successful application of such techniques may necessitate characterizations of coefficients specific to a given region and time.

Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters

Abstract: For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.

Underwater Optical Wireless Communication

Abstract: Underwater wireless information transfer is of great interest to the military, industry, and the scientific community, as it plays an important role in tactical surveillance, pollution monitoring, oil control and maintenance, offshore explorations, climate change monitoring, and oceanography research. In order to facilitate all these activities, there is an increase in the number of unmanned vehicles or devices deployed underwater, which require high bandwidth and high capacity for information transfer underwater. Although tremendous progress has been made in the field of acoustic communication underwater, however, it is limited by bandwidth. All this has led to the proliferation of underwater optical wireless communication (UOWC), as it provides higher data rates than the traditional acoustic communication systems with significantly lower power consumption and simpler computational complexities for short-range wireless links. UOWC has many potential applications ranging from deep oceans to coastal waters. However, the biggest challenge for underwater wireless communication originates from the fundamental characteristics of ocean or sea water; addressing these challenges requires a thorough understanding of complex physio-chemical biological systems. In this paper, the main focus is to understand the feasibility and the reliability of high data rate underwater optical links due to various propagation phenomena that impact the performance of the system. This paper provides an exhaustive overview of recent advances in UOWC. Channel characterization, modulation schemes, coding techniques, and various sources of noise which are specific to UOWC are discussed. This paper not only provides exhaustive research in underwater optical communication but also aims to provide the development of new ideas that would help in the growth of future underwater communication. A hybrid approach to an acousto-optic communication system is presented that complements the existing acoustic system, resulting in high data rates, low latency, and an energy-efficient system.

An Underwater Image Enhancement Benchmark Dataset and Beyond

Abstract: Underwater image enhancement has been attracting much attention due to its significance in marine engineering and aquatic robotics. Numerous underwater image enhancement algorithms have been proposed in the last few years. However, these algorithms are mainly evaluated using either synthetic datasets or few selected real-world images. It is thus unclear how these algorithms would perform on images acquired in the wild and how we could gauge the progress in the field. To bridge this gap, we present the first comprehensive perceptual study and analysis of underwater image enhancement using large-scale real-world images. In this paper, we construct an Underwater Image Enhancement Benchmark (UIEB) including 950 real-world underwater images, 890 of which have the corresponding reference images. We treat the rest 60 underwater images which cannot obtain satisfactory reference images as challenging data. Using this dataset, we conduct a comprehensive study of the state-of-the-art underwater image enhancement algorithms qualitatively and quantitatively. In addition, we propose an underwater image enhancement network (called Water-Net) trained on this benchmark as a baseline, which indicates the generalization of the proposed UIEB for training Convolutional Neural Networks (CNNs). The benchmark evaluations and the proposed Water-Net demonstrate the performance and limitations of state-of-the-art algorithms, which shed light on future research in underwater image enhancement. The dataset and code are available at https://li-chongyi.github.io/proj_benchmark.html .

Chlorophyll aalgorithms for oligotrophic oceans: A novel approach based on three‐band reflectance difference

Abstract: A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

Human-Visual-System-Inspired Underwater Image Quality Measures

Abstract: Underwater images suffer from blurring effects, low contrast, and grayed out colors due to the absorption and scattering effects under the water. Many image enhancement algorithms for improving the visual quality of underwater images have been developed. Unfortunately, no well-accepted objective measure exists that can evaluate the quality of underwater images similar to human perception. Predominant underwater image processing algorithms use either a subjective evaluation, which is time consuming and biased, or a generic image quality measure, which fails to consider the properties of underwater images. To address this problem, a new nonreference underwater image quality measure (UIQM) is presented in this paper. The UIQM comprises three underwater image attribute measures: the underwater image colorfulness measure (UICM), the underwater image sharpness measure (UISM), and the underwater image contrast measure (UIConM). Each attribute is selected for evaluating one aspect of the underwater image degradation, and each presented attribute measure is inspired by the properties of human visual systems (HVSs). The experimental results demonstrate that the measures effectively evaluate the underwater image quality in accordance with the human perceptions. These measures are also used on the AirAsia 8501 wreckage images to show their importance in practical applications.