On the equivalence of near-surface methods to determine the water-leaving radiance

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.

Australian aquatic bio-optical dataset with applications for satellite calibration, algorithm development and validation

The authors present bio-optical data spanning 316 sets of observations made at 34 inland waterbodies in Australia. The data was collected over the period 2013–2021 and comprise radiometric measurements of remote sensing reflectance (Rrs), diffuse attenuation extinction coefficient (Kd); optical backscattering; absorption of coloured dissolved organic matter (aCDOM), phytoplankton (aph) and non-algal particles (aNAP); HPLC analysis of algal pigments including chlorophyll-a (CHL-a); organic and inorganic total suspended solids (TSS); and total and dissolved organic carbon concentration. Data collection has been timed to coincide with either Landsat 8 or Sentinel-2 overpasses. The dataset covers a diverse range of optical water types and is suitable for algorithm development, satellite calibration and validation as well as machine learning applications.

Experimental analysis of the measurement precision of spectral water-leaving radiance in different water types: comment

This work aims at commenting requirements and conclusions in a recent paper [Wei et al., Opt. Express29, 2780 (2021)10.1364/OE.413784] presenting an evaluation of the precision of water-leaving radiance measurements from a near-surface method. Specifically, this work challenges the uncertainty requirements indicated for satellite ocean color system vicarious calibration resulting from an erroneous interpretation of literature, and an incorrect application of radiometry principles leading to a misestimate of the difference between radiances collected by nadir-view optical sensors operated below and above the water surface.

Underwater image enhancement method based on adaptive attenuation-curve prior

The attenuation (sum of absorption and scattering), which is caused by the dense and non-uniform medium, generally leads to problems of color degradation and detail loss in underwater imaging. In this study, we describe an underwater image enhancement method based on adaptive attenuation-curve prior. This method uses color channel transfer (CCT) to preprocess the underwater images, light smoothing, and wavelength-dependent attenuation to estimate water light and obtain the attenuation ratio between color channels, and estimates and refines the initial relative transmission of the channel. Additionally, the method calculates the attenuation factor and saturation constraints of the three color channels and generates an adjusted reverse saturation map (ARSM) to address uneven light intensity, after which the image is restored through water light and transmission estimation. Furthermore, we applied white balance fusion globally guided image filtering (G-GIF) technology to achieve color enhancement and edge detail preservation in the underwater images. Comparison experiments showed that the proposed method obtained better color and de-hazing effects, as well as clearer edge details, relative to current methods.

Uncertainty assessment of unattended above-water radiometric data collection from research vessels with the Dynamic Above-water Radiance (L) and Irradiance (E) Collector (DALEC)

We used above- and below-water radiometry measurements collected during a research voyage in the eastern Indian Ocean to assess uncertainties in deriving the remote sensing reflectance, R_rs, from unattended above-water radiometric data collection with the In-Situ Marine Optics Pty. Ltd. (IMO) Dynamic Above-water Radiance (L) and Irradiance (E) Collector (DALEC). To achieve this, the R_rs values derived from using the latest version of this hyperspectral radiometer were compared to values obtained from two in-water profiling radiometer systems of rather general use in the ocean optics research community, i.e., the Biospherical Instruments Inc. Compact Optical Profiling System (C-OPS) and the Seabird HyperPro II. Our results show that unattended, carefully quality-controlled, DALEC measurements provide R_rs for wavelengths < 600 nm that match those derived from the in-water systems with no bias and a dispersion of about 8%, provided that the appropriate technique is used to quantify the contribution of sky light reflection to the measured signal. The dispersion is larger (25-50%) for red bands, which is expected for clear oligotrophic waters as encountered during the voyage, where ∼2 10^-5 < R_rs < ∼2 10^-4 sr^-1. For comparison, the two in-water systems provided R_rs in agreement within 4% for wavelengths < 600 nm.

Experimental analysis of the measurement precision of spectral water-leaving radiance in different water types

The on-water radiometric approach employs a unique provision to obtain water-leaving radiance from nadir (Lw(λ)) which can be used for the calibration of ocean color satellites. In this effort, we address the measurement precision associated with Lw(λ) from a single on-water instrument, which is an important aspect of measurement uncertainty. First, we estimated the precision as the ratio of the standard deviation of the means of repeated measurements to the mean of these measurements. We show that the measurement precision for Lw(λ) is within 2.7-3.7% over 360-700 nm. The corresponding remote sensing reflectance spectra (Rrs(λ)) from the same instrument also exhibit a high precision of 1.9-2.8% in the same spectral domain. These measured precisions of radiance and reflectance over the 360-700 nm range are independent of the optical water type. Second, we quantified the consistency of on-water Lw(λ) and Rrs(λ) from two collocated systems for further insight into their measurement repeatability. The comparison reveals that Lw(λ) measurements in the 360-700 nm agree with each other with an absolute percentage difference of less than 3.5%. The corresponding Rrs(λ) data pairs are subjected to increased differences of up to 8.5%, partly due to variable irradiance measurements (Es(λ)). The evaluation of measurement precision corroborates the reliability of the on-water acquisition of radiometric data for supporting satellite calibration and validation.

Experimental evaluation of the self-shadow and its correction for on-water measurements of water-leaving radiance

Accurate determination of the water-leaving radiance (L_w) is key to correctly interpret in-water optical properties and to validate the atmospheric correction schemes in ocean color studies. Among the various approaches adopted to measure L_w in the field, the skylight-blocked approach (SBA) is the only scheme that can potentially measure L_w directly. However, the apparatus associated with an SBA system will introduce self-shading effects to the measured L_w, which is required to be corrected for an accurate L_w determination. In this study, we experimentally evaluate several factors that could contribute to the self-shading effects of the SBA-measured L_w, including solar zenith angle (∼18^∘-64^∘), water's optical properties, and cone size (radius of 22 mm and 45 mm). For waters with the total absorption coefficient at 440 nm as high as ∼6.0m^-1, the normalized root-mean-square difference between the SBA-measured L_w after shade correction and the "true" L_w is generally between ∼5% and ∼10% for wavelengths in the range of 400-750 nm. These results suggest that SBA can obtain highly accurate and precise L_w in nearly all natural aquatic environments.

An Evaluation of Citizen Science Smartphone Apps for Inland Water Quality Assessment

Rapid and widespread monitoring of inland and coastal water quality occurs through the use of remote sensing and near-surface water quality sensors. A new addition is the development of smartphone applications (Apps) to measure and record surface reflectance, water color and water quality parameters. In this paper, we present a field study of the HydroColor (HC, measures RGB reflectance and suspended particulate matter (SPM)) and EyeOnWater (EoW, determines the Forel–Ule scale—an indication to the visual appearance of the water surface) smartphone Apps to evaluate water quality for inland waters in Eastern Australia. The Brisbane river, multiple lakes and reservoirs and lagoons in Queensland and New South Wales were visited; hyperspectral reflection spectra were collected and water samples were analysed in the laboratory as reference. Based on detailed measurements at 32 sites, covering inland waters with a large range in sediment and algal concentrations, we find that both water quality Apps are close, but not quite on par with scientific spectrometers. EoW is a robust application that manages to capture the color of water with accuracy and precision. HC has great potential, but is influenced by errors in the observational procedure and errors in the processing of images in the iPhone. The results show that repeated observations help to reduce the effects of outliers, while implementation of camera response functions and processing should help to reduce systematic errors. For both Apps, no universal conversion to water quality composition is established, and we conclude that: (1) replicated measurements are useful; (2) color is a reliable monitoring parameter in its own right but it should not be used for other water quality variables, and; (3) tailored algorithms to convert reflectance and color to composition could be developed for lakes individually.