Albert-Miquel Sánchez

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.

Hyperspectral characterization of marine particles based on MIE-LORENTZ and T-matrix codes and a genetic algorithm

Particle modeling is usually exploited, along with measured data, to infer the water content. However, the particle properties must be accurately known. In this paper, a methodology to estimate the hyperspectral complex-refractive-index signatures of marine particles is presented. It is is based on the Mie-Lorentz and T-matrix characterizations to obtain the particle inherent optical properties and uses a genetic algorithm for search optimization. This methodology is tested by accurately estimating the hyperspectral complex refractive indexes on two different examples, including monodisperse and polydisperse particle size distributions of spherical and non-spherical particles.

Analysis of Discrimination Techniques for Low-Cost Narrow-Band Spectrofluorometers

The need for covering large areas in oceanographic measurement campaigns and the general interest in reducing the observational costs open the necessity to develop new strategies towards this objective, fundamental to deal with current and future research projects. In this respect, the development of low-cost instruments becomes a key factor, but optimal signal-processing techniques must be used to balance their measurements with those obtained from accurate but expensive instruments. In this paper, a complete signal-processing chain to process the fluorescence spectra of marine organisms for taxonomic discrimination is proposed. It has been designed to deal with noisy, narrow-band and low-resolution data obtained from low-cost sensors or instruments and to optimize its computational cost, and it consists of four separated blocks that denoise, normalize, transform and classify the samples. For each block, several techniques are tested and compared to find the best combination that optimizes the classification of the samples. The signal processing has been focused on the Chlorophyll-a fluorescence peak, since it presents the highest emission levels and it can be measured with sensors presenting poor sensitivity and signal-to-noise ratios. The whole methodology has been successfully validated by means of the fluorescence spectra emitted by five different cultures.

Low-cost computationally hyperspectral simulator for highly dynamic marine environments

Hyperspectral optical observations and the development of new processing strategies are key for a better understanding of complex marine ecosystems and space-time distribution of ecological parameters. In this paper, the methodologies to implement a simulator of hyperspectral-resolved optical data corresponding to highly dynamic marine environments are presented. The simulator is based on a coupled radiative transfer and Lagrangian hydrodynamic model, which is organized in four basic blocks: a hydrodynamic model, a particle tracking model, a transformation function and a radiative transfer model. The transformation function is needed to adapt the output of the tracking model (given in number of particles per unit volume) to mass concentration, suitable for the radiative transfer model. The transformation function has been derived considering an allometric relationship between both magnitudes, since it is found in nature. The simulator is finally tested by considering the Alfacs Bay (NW Mediterranean Sea), as a case study site.

Do hyperspectral transmissometers allow us to go one step further on the analysis of particulate matter characteristics of marine samples

Several studies have been carried out to investigate the correlation between the spectral shape features of the beam attenuation coefficient and the particulate matter characteristics in seawater, but little attention has been paid to the spectral resolution of these measurements. For this reason, the potential of the new hyperspectral transmissometer VIPER (TriOS GmbH), with 1.7 nm spectral resolution, has been evaluated in this study and compared with lower resolution and multispectral based approaches (e.g. ac-9 or ac-s-with 4 nm resolution - from WETLabs Inc.) in order to evaluate whether any additional information about water composition can be retrieved from a spectral shape-based assessment. In this way, this study proposes a statistical-based method - a Hierarchical Cluster Analysis (HCA) using the cosine distance as similarity value - which allows discriminating suspended sediment samples with different particle size distribution (PSD) based on the attenuation spectral shape features. Finally, the effects of both particle size and concentration on the spectral shape have been analyzed separately. The results confirmed that the beam attenuation spectral features are in first-order driven by particle concentration, which means that a prior knowledge of particulate matter concentration is required in order to classify sediment samples according to their particle size. This approach based on hyperspectral attenuation measurements to characterize the PSD has been demonstrated a potential alternative compared to the traditional methods such as Coulter Counter or the particle size analyzer LISST 100X, which are much more expensive and time-consuming approaches.