Derivation of immersion factors for the hyperspectral TriOS radiance sensor

Pixelwise immersion factor calibration for underwater hyperspectral imaging instruments

In situ spectral reflectance initially captured at high spatial resolution with underwater hyperspectral imaging (UHI) is effective for classification and quantification in oceanic biogeochemical studies; however, the measured spectral radiance is rarely used as an absolute quantity due to challenges in calibration of UHI instruments. In this paper, a commercial UHI instrument was calibrated for radiometric flat field response and pixelwise immersion effect to support in situ measurement of absolute spectral radiance. The radiometric and immersion factor calibrations of the UHI instrument were evaluated quantitatively through comparative experiments with a spectroradiometer and a spectrometer. Results show that the immersion factor of the center pixel of the tested UHI instrument was 1.763 in pure water at 600 nm, and the averaged difference in immersion factor between the center and edge pixel of the UHI instrument in the visible light band was only 1∼3% across its half angle field of view of 35° in air. The new calibration coefficients were further used to calculate the spectral radiance of transmitted sunlight through ice algae clusters in sea ice measured by the UHI instrument during an Arctic under-ice bio-optical survey.

Application of a PLS-Augmented ANN Model for Retrieving Chlorophyll-a from Hyperspectral Data in Case 2 Waters of the Western Basin of Lake Erie

We present results that demonstrate the utility of machine learning techniques that are based on partial least squares (PLS) and artificial neural networks (ANNs) for estimating low-moderate chlorophyll-a (chl-a) concentrations in the western basin of Lake Erie (WBLE). Previous ocean color studies have resulted in a large number of algorithms that are based on spectral indices to estimate water quality parameters (WQPs) such as chl-a concentration from remote sensing reflectance. However, these spectral index algorithms are based on reflectance features at specific wavelengths and do not take advantage of the wealth of spectral information that is contained in hyperspectral data, and are often not easily adaptable to waters with conditions that are different from those in the datasets that were used to originally calibrate the indices. Recently, there have been efforts to use machine learning techniques that are based on ANNs and PLS regression to exploit the spectral richness contained in hyperspectral data and retrieve WQPs. In this study, we have combined an ANN model with output from PLS regression to retrieve chl-a concentration from hyperspectral data in the WBLE. We compared the results from the PLS-ANN method to those that were obtained from a band-ratio algorithm that is based on reflectances in the blue and green spectral regions, a band ratio algorithm that is based on reflectances in the red and near-infrared (NIR) spectral regions, and a PLS-only approach. For a dataset that was collected in 2012, with chl-a concentrations ranging from 0.48 to 21.2 µg/L, the PLS-ANN method yielded a root mean square error (RMSE) of 1.22 µg/L, whereas the blue-green ratio algorithm yielded an RMSE of 1.75 µg/L, the NIR-red ratio algorithm yielded an RMSE of 1.95 µg/L, and the PLS-only approach yielded an RMSE of 1.95 µg/L. The PLS-ANN method takes advantage of the PLS regression to identify specific wavelengths that contain most information about the variation in chl-a concentration, minimize spectral collinearity and redundancy in the data, and simplify the neural network’s input structure. The better performance of the PLS-ANN method can also be attributed to the neural network’s ability to account for nonlinearity in the relationship between chl-a concentration and spectral reflectance. The results indicate that the PLS-ANN method can be reliably used to estimate and monitor low-moderate chl-a concentrations in optically complex waters.

Immersion Coefficient for the Marine Optical Buoy (MOBY) Radiance Collectors

The immersion coefficient accounts for the difference in responsivity for a radiometer placed in the air versus water or another medium. In this study, the immersion coefficients for the radiance collectors on the Marine Optical Buoy (MOBY) were modeled and measured. The experiment showed that the immersion coefficient for the MOBY radiance collectors agreed with a simple model using only the index of refraction for water and fused silica. With the results of this experiment, we estimate that the uncertainty in the current value of the immersion coefficient used in the MOBY project is 0.05 % (k = 1).

Estimation of underwater visibility in coastal and inland waters using remote sensing data

An optical method is developed to estimate water transparency (or underwater visibility) in terms of Secchi depth (Z _sd ), which follows the remote sensing and contrast transmittance theory. The major factors governing the variation in Z _sd , namely, turbidity and length attenuation coefficient (1/(c + K _d ), c = beam attenuation coefficient; K _d  = diffuse attenuation coefficient at 531 nm), are obtained based on band rationing techniques. It was found that the band ratio of remote sensing reflectance (expressed as (R _rs (443) + R _rs (490))/(R _rs (555) + R _rs (670)) contains essential information about the water column optical properties and thereby positively correlates to turbidity. The beam attenuation coefficient (c) at 531 nm is obtained by a linear relationship with turbidity. To derive the vertical diffuse attenuation coefficient (K _d ) at 531 nm, K _d (490) is estimated as a function of reflectance ratio (R _rs (670)/R _rs (490)), which provides the bio-optical link between chlorophyll concentration and K _d (531). The present algorithm was applied to MODIS-Aqua images, and the results were evaluated by matchup comparisons between the remotely estimated Z _sd and in situ Z _sd in coastal waters off Point Calimere and its adjoining regions on the southeast coast of India. The results showed the pattern of increasing Z _sd from shallow turbid waters to deep clear waters. The statistical evaluation of the results showed that the percent mean relative error between the MODIS-Aqua-derived Z _sd and in situ Z _sd values was within ±25%. A close agreement achieved in spatial contours of MODIS-Aqua-derived Z _sd and in situ Z _sd for the month of January 2014 and August 2013 promises the model capability to yield accurate estimates of Z _sd in coastal, estuarine, and inland waters. The spatial contours have been included to provide the best data visualization of the measured, modeled (in situ), and satellite-derived Z _sd products. The modeled and satellite-derived Z _sd values were compared with measurement data which yielded RMSE = 0.079, MRE = -0.016, and R ²  = 0.95 for the modeled Z _sd and RMSE = 0.075, MRE = 0.020, and R ²  = 0.95 for the satellite-derived Z _sd products.

An optical method to assess water clarity in coastal waters

Accurate estimation of water clarity in coastal regions is highly desired by various activities such as search and recovery operations, dredging and water quality monitoring. This study intends to develop a practical method for estimating water clarity based on a larger in situ dataset, which includes Secchi depth (Z sd ), turbidity, chlorophyll and optical properties from several field campaigns in turbid coastal waters. The Secchi depth parameter is found to closely vary with the concentration of suspended sediments, vertical diffuse attenuation coefficient K d (m(-1)) and beam attenuation coefficient c (m(-1)). The optical relationships obtained for the selected wavelengths (i.e. 520, 530 and 540 nm) exhibit an inverse relationship between Secchi depth and the length attenuation coefficient (1/(c + K d )). The variation in Secchi depth is expressed in terms of undetermined coupling coefficient which is composed of light penetration factor (expressed by z(1%)K d (λ)) and a correction factor (ξ) (essentially governed by turbidity of the water column). This method of estimating water clarity was validated using independent in situ data from turbid coastal waters, and its results were compared with those obtained from the existing methods. The statistical analysis of the measured and the estimated Z sd showed that the present method yields lower error when compared to the existing methods. The spatial structures of the measured and predicted Z sd are also highly consistent with in situ data, which indicates the potential of the present method for estimating the water clarity in turbid coastal and associated lagoon waters.

A new model for the vertical spectral diffuse attenuation coefficient of downwelling irradiance in turbid coastal waters: validation with in situ measurements

The vertical spectral diffuse attenuation coefficient of Kd is an important optical property related to the penetration and availability of light underwater, which is of fundamental interest in studies of ocean physics and biology. Models developed in the recent decades were mainly based on theoretical analyses and numerical (radiative transfer) simulations to estimate this property in optically deep waters, thus leaving inadequate knowledge of its variability at multiple depths and wavelengths, covering a wide range of solar incident geometry, in turbid coastal waters. In the present study, a new model is developed to quantify the vertical, spatial and temporal variability of K(d) at multiple wavelengths and to quantify its dependence with respect to solar incident geometry under differing sky conditions. Thus, the new model is derived as a function of inherent optical properties (IOPs - absorption a and backscattering b(b)), solar zenith angle and depth parameters. The model results are rigorously evaluated using time-series and discrete in situ data from clear and turbid coastal waters. The K(d) values derived from the new model are found to agree with measured data within the mean relative error 0.02~6.24% and R² 0.94~0.99. By contrast, the existing models have large errors when applied to the same data sets. Statistical results of the new model for the vertical spectral distribution of K(d) in clear oceanic waters (for different solar zenith and in-water conditions) are also good when compared to those of the existing models. These results suggest that the new model can provide an improved interpretation about the variation of the vertical spectral diffuse attenuation coefficient of downwelling irradiance, which will have important implications for ocean physics, biogeochemical cycles and underwater applications in both relatively clear and turbid coastal waters.

Hyperspectral determination of eutrophication for a water supply source via genetic algorithm-partial least squares (GA-PLS) modeling

Morse Reservoir (MR), a major source of the water supply for the Indianapolis metropolitan region, is now experiencing nuisance cyanobacterial blooms. These blooms cause water quality degradation, as well as reducing the aesthetic quality of water by producing toxins, scums, and foul odors. Hyperspectral remote sensing data from both in situ and airborne AISA measurements were applied to GA-PLS by relating the spectral signal with measured water eutrophication parameters, e.g., chlorophyll-a (Chl-a), phycocyanin (PC), total suspended matter (TSM), and Secchi disk depth (SDD). Our results indicate that GA-PLS relating field sensor acquired spectral reflectance to the above-mentioned four parameters yielded low root mean square error between measured and estimated Chl-a (RMSE=10.4; Range (R): 1.8-215.8 μg/L), PC (RMSE=18.6; R: 1.4-371.0 μg/L), TSM (RMSE=3.8; R: 3.6-81.4 mg/L), SDD (RMSE=5.8; R: 25-135 cm) for MR. The GA-PLS model also yielded high performance with AISA image spectra, and the RMSEs were 12.1 μg/L, 25.3 μg/L, 5.9 mg/L and 5.7 cm, respectively for Chl-a, PC, TSM, and SDD. Four water quality parameters were mapped with GA-PLS using AISA hyperspectral image. Based on these results, in situ and airborne hyperspectral remote sensors can provide both quantitative and qualitative information on the distribution and concentration of cyanobacteria, suspended matter, and transparency in MR.

Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data

Algorithms based on red and near infra-red (NIR) reflectances measured using field spectrometers have been previously shown to yield accurate estimates of chlorophyll-a concentration in turbid productive waters, irrespective of variations in the bio-optical characteristics of water. The objective of this study was to investigate the performance of NIR-red models when applied to multi-temporal airborne reflectance data acquired by the hyperspectral sensor, Airborne Imaging Spectrometer for Applications (AISA), with non-uniform atmospheric effects across the dates of data acquisition. The results demonstrated the capability of the NIR-red models to capture the spatial distribution of chlorophyll-a in surface waters without the need for atmospheric correction. However, the variable atmospheric effects did affect the accuracy of chlorophyll-a retrieval. Two atmospheric correction procedures, namely, Fast Line-of-sight Atmospheric Adjustment of Spectral Hypercubes (FLAASH) and QUick Atmospheric Correction (QUAC), were applied to AISA data and their results were compared. QUAC produced a robust atmospheric correction, which led to NIR-red algorithms that were able to accurately estimate chlorophyll-a concentration, with a root mean square error of 5.54 mg m(-3) for chlorophyll-a concentrations in the range 2.27-81.17 mg m(-3).

Evaluation of a High Exposure Solar UV Dosimeter for Underwater Use

Solar ultraviolet radiation (UV) is known to have a significant effect upon the marine ecosystem. This has been documented by many previous studies using a variety of measurement methods in aquatic environments such as oceans, streams and lakes. Evidence gathered from these investigations has shown that UVB radiation (280-320 nm) can negatively affect numerous aquatic life forms, while UVA radiation (320-400 nm) can both damage and possibly even repair certain types of underwater life. Chemical dosimeters such as polysulphone have been tested to record underwater UV exposures and in turn quantify the relationship between water column depth and dissolved organic carbon levels to the distribution of biologically damaging UV underwater. However, these studies have only been able to intercept UV exposures over relatively short time intervals. This paper reports on the evaluation of a high exposure UV dosimeter for underwater use. The UV dosimeter was fabricated from poly 2,6-dimethyl-1,4-phenylene oxide (PPO) film. This paper presents the dose response, cosine response, exposure additivity and watermarking effect relating to the PPO dosimeter as measured in a controlled underwater environment and will also detail the overnight dark reaction and UVA and visible radiation response of the PPO dosimeter, which can be used for error correction to improve the reliability of the UV data measured by the PPO dosimeters. These results show that this dosimeter has the potential for long-term underwater UV exposure measurements.

Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling

Spectral measurements of remote-sensing reflectance (Rrs) and absorption coefficients carried out in three European estuaries (Gironde and Loire in France, Tamar in the UK) are presented and analyzed. Typical Rrs and absorption spectra are compared with typical values measured in coastal waters. The respective contributions of the water constituents, i.e., suspended sediments, colored dissolved organic matter, and phytoplankton (characterized by chlorophyll-a), are determined. The Rrs spectra are then reproduced with an optical model from the measured absorption coefficients and fitted backscattering coefficients. From Rrs ratios, empirical quantification relationships are established, reproduced, and explained from theoretical calculations. These quantification relationships were established from numerous field measurements and a reflectance model integrating the mean values of the water constituents' inherent optical properties. The model's sensitivity to the biogeochemical constituents and to their nature and composition is assessed.