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.

Validation of a spectral correction procedure for sun and sky reflections in above-water reflectance measurements.

A three-component reflectance model (3C) is applied to above-water radiometric measurements to derive remote-sensing reflectance Rrs (λ). 3C provides a spectrally resolved offset Δ(λ) to correct for residual sun and sky radiance (Rayleigh- and aerosol-scattered) reflections on the water surface that were not represented by sky radiance measurements. 3C is validated with a data set of matching above- and below-water radiometric measurements collected in the Baltic Sea, and compared against a scalar offset correction Δ. Correction with Δ(λ) instead of Δ consistently reduced the (mean normalized root-mean-square) deviation between Rrs (λ) and reference reflectances to comparable levels for clear (Δ: 14.3 ± 2.5 %, Δ(λ): 8.2 ± 1.7 %), partly clouded (Δ: 15.4 ± 2.1 %, Δ(λ): 6.5 ± 1.4 %), and completely overcast (Δ: 10.8 ± 1.7 %, Δ(λ): 6.3 ± 1.8 %) sky conditions. The improvement was most pronounced under inhomogeneous sky conditions when measurements of sky radiance tend to be less representative of surface-reflected radiance. Accounting for both sun glint and sky reflections also relaxes constraints on measurement geometry, which was demonstrated based on a semi-continuous daytime data set recorded in a eutrophic freshwater lake in the Netherlands. Rrs (λ) that were derived throughout the day varied spectrally by less than 2 % relative standard deviation. Implications on measurement protocols are discussed. An open source software library for processing reflectance measurements was developed and is made publicly available.

Envilab: Measuring phytoplankton in-vivo absorption and scattering properties under tunable environmental conditions.

Optical remote sensing of phytoplankton draws on distinctive spectral features which can vary with both species and environmental conditions. Here, we present a set-up (Envilab) for growing phytoplankton under well-defined light, temperature and nutrient conditions. The custom-built light source enables creation of light with spectral composition similar to natural aquatic environments. Spectral tuning allows for light quality studies. Attenuation is monitored with a spectrometer in transmission mode. In combination with automated spectrophotometer and fluorimeter measurements, absorption and excitation-emission-fluorescence spectra are recorded. The set-up opens the door for systematic studies on phytoplankton optical properties and physiology.

Variability of adjacency effects in sky reflectance measurements.

Sky reflectance Rsky(λ) is used to correct in situ reflectance measurements in the remote detection of water color. We analyzed the directional and spectral variability in Rsky(λ) due to adjacency effects against an atmospheric radiance model. The analysis is based on one year of semi-continuous Rsky(λ) observations that were recorded in two azimuth directions. Adjacency effects contributed to Rsky(λ) dependence on season and viewing angle and predominantly in the near-infrared (NIR). For our test area, adjacency effects spectrally resembled a generic vegetation spectrum. The adjacency effect was weakly dependent on the magnitude of Rayleigh- and aerosol-scattered radiance. The reflectance differed between viewing directions 5.4±6.3% for adjacency effects and 21.0±19.8% for Rayleigh- and aerosol-scattered Rsky(λ) in the NIR. Under which conditions in situ water reflectance observations require dedicated correction for adjacency effects is discussed. We provide an open source implementation of our method to aid identification of such conditions.

Analytic model for the direct and diffuse components of downwelling spectral irradiance in water.

The direct and diffuse components of downwelling irradiance have in general different path lengths in water, and hence they decrease differently with sensor depth. Furthermore, the ever-changing geometry of a wind-roughened and wave-modulated water surface induces uncorrelated intensity changes to these components. To cope with both effects, an analytic model of the downwelling irradiance in water was developed that calculates the direct and diffuse components separately. By assigning weights f(dd) and f(ds) to the intensities of the two components, measurements performed at arbitrary surface conditions can be analyzed by treating f(dd) and f(ds) as fit parameters. The model was validated against HydroLight and implemented into the public-domain software WASI. It was applied to data from three German lakes to determine the statistics of f(dd) and ff(ds), to derive the sensor depth of each measurement and to estimate the concentrations of water constituents.

Sources of variance of downwelling irradiance in water.

The downwelling irradiance in water is highly variable due to the focusing and defocusing of sunlight and skylight by the wave-modulated water surface. While the time scales and intensity variations caused by wave focusing are well studied, little is known about the induced spectral variability. Also, the impact of variations of sensor depth and inclination during the measurement on spectral irradiance has not been studied much. We have developed a model that relates the variance of spectral irradiance to the relevant parameters of the environmental and experimental conditions. A dataset from three German lakes was used to validate the model and to study the importance of each effect as a function of depth for the range of 0 to 5 m.

Inversion of irradiance and remote sensing reflectance in shallow water between 400 and 800 nm for calculations of water and bottom properties.

What we believe to be a new inversion procedure for multi- and hyperspectral data in shallow water, represented by the subsurface irradiance and remote sensing reflectance spectra, was developed based on analytical equations by using the method of nonlinear curve fitting. The iteration starts using an automatic determination of the initial values of the fit parameters: concentration of phytoplankton and suspended matter, absorption of gelbstoff, bottom depth, and the fractions of up to six bottom types. Initial values of the bottom depth and suspended matter concentration are estimated analytically. Phytoplankton concentration and gelbstoff absorption are initially calculated by the method of nested intervals. A sensitivity analysis was made to estimate the accuracy of the entire inversion procedure including model error, error propagation, and influence of instrument characteristics such as noise, and radiometric and spectral resolution. The entire inversion technique is included in a public-domain software (WASI) to provide a fast and user-friendly tool of forward and inverse modeling.