MERIS-based ocean colour classification with the discrete Forel-Ule scale

Multispectral information from satellite borne ocean colour sensors is at present used to characterize natural waters via the retrieval of concentrations of the three dominant optical constituents; pigments of phytoplankton, non-algal particles and coloured dissolved organic matter. A limitation of this approach is that accurate retrieval of these constituents requires detailed local knowledge of the specific absorption and scattering properties. In addition, the retrieval algorithms generally use only a limited part of the collected spectral information. In this paper we present an additional new algorithm that has the merit of using the full spectral information in the visible domain to characterize natural waters in a simple and globally valid way. This Forel–Ule MERIS (FUME) algorithm converts the normalized multiband reflectance information into a discrete set of numbers using uniform colourimetric functions. The Forel–Ule (<i>FU</i>) scale is a sea colour comparator scale that has been developed to cover all possible natural sea colours, ranging from indigo blue (the open ocean) to brownish-green (coastal water) and even brown (humic-acid dominated) waters. Data using this scale have been collected since the late nineteenth century, and therefore, this algorithm creates the possibility to compare historic ocean colour data with present-day satellite ocean colour observations. The FUME algorithm was tested by transforming a number of MERIS satellite images into Forel–Ule colour index images and comparing in situ observed <i>FU</i> numbers with <i>FU</i> numbers modelled from in situ radiometer measurements. Similar patterns and <i>FU</i> numbers were observed when comparing MERIS ocean colour distribution maps with ground truth Forel–Ule observations. The <i>FU</i> numbers modelled from in situ radiometer measurements showed a good correlation with observed <i>FU</i> numbers (<i>R</i>² = 0.81 when full spectra are used and <i>R</i>² = 0.71 when MERIS bands are used)

Estimating the Underwater Diffuse Attenuation Coefficient with a Low-Cost Instrument: The KdUINO DIY Buoy

A critical parameter to assess the environmental status of water bodies is the transparency of the water, as it is strongly affected by different water quality related components (such as the presence of phytoplankton, organic matter and sediment concentrations). One parameter to assess the water transparency is the diffuse attenuation coefficient. However, the number of subsurface irradiance measurements obtained with conventional instrumentation is relatively low, due to instrument costs and the logistic requirements to provide regular and autonomous observations. In recent years, the citizen science concept has increased the number of environmental observations, both in time and space. The recent technological advances in embedded systems and sensors also enable volunteers (citizens) to create their own devices (known as Do-It-Yourself or DIY technologies). In this paper, a DIY instrument to measure irradiance at different depths and automatically calculate the diffuse attenuation Kd coefficient is presented. The instrument, named KdUINO, is based on an encapsulated low-cost photonic sensor and Arduino (an open-hardware platform for the data acquisition). The whole instrument has been successfully operated and the data validated comparing the KdUINO measurements with the commercial instruments. Workshops have been organized with high school students to validate its feasibility

A mesocosm tool to optically study phytoplankton dynamics

The accuracy of remote sensing algorithms for phytoplankton biomass and physiology is difficult to test under natural conditions due to rapid changes in physical and biological forcings and the practical inability to manipulate nutrient conditions and phytoplankton composition in the sea. Therefore, an indoor mesocosm was designed to examine the optical properties of phytoplankton under controlled and manipulated conditions of irradiance, temperature, turbulence, and nutrient availability. Equipped with hyperspectral radiometers and bottom irradiance meters, it is shown that under semi-natural environmental conditions biogeochemically relevant species as Emiliania huxleyi and Phaeocystis globosa can be grown with good precision (+/- 20%) between duplicate mesocosms and between duplicate sensors (< 5% deviation). The accuracy of chlorophyll estimates by absorption, using an Integrating Cavity Absorption Meter, and fluorescence using water-leaving radiance was 74% to 80%, respectively, as it was negatively influenced by changes in phytoplankton physiology. Biomass detection was limitedto 1 to 2 mu g chlorophyll/L with an apparent linearity to 50 mu g chlorophyll/L. Estimates of the quantum efficiency of fluorescence (phi approximate to 0.01) were comparable to real-world estimates derived from satellite observations. It is concluded that the mesocosms adequately simulate natural conditions with sufficient accuracy and precision and that they offer an important tool in validating assumptions and hypotheses underlying remote sensing algorithms and models

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