The Use of Sentinel-3 Imagery to Monitor Cyanobacterial Blooms

Cyanobacterial harmful algal blooms (CHABs) have been a concern for aquatic systems, especially those used for water supply and recreation. Thus, the monitoring of CHABs is essential for the establishment of water governance policies. Recently, remote sensing has been used as a tool to monitor CHABs worldwide. Remote monitoring of CHABs relies on the optical properties of pigments, especially the phycocyanin (PC) and chlorophyll-a (chl-a). The goal of this study is to evaluate the potential of recent launch the Ocean and Land Color Instrument (OLCI) on-board the Sentinel-3 satellite to identify PC and chl-a. To do this, OLCI images were collected over the Western part of Lake Erie (U.S.A.) during the summer of 2016, 2017, and 2018. When comparing the use of traditional remote sensing algorithms to estimate PC and chl-a, none was able to accurately estimate both pigments. However, when single and band ratios were used to estimate these pigments, stronger correlations were found. These results indicate that spectral band selection should be re-evaluated for the development of new algorithms for OLCI images. Overall, Sentinel 3/OLCI has the potential to be used to identify PC and chl-a. However, algorithm development is needed

Hyperspectral remote sensing of cyanobacterial pigments as indicators for cell populations and toxins in eutrophic lakes

The growth of mass populations of toxin-producing cyanobacteria is a serious concern for the ecological status of inland waterbodies and for human and animal health. In this study we examined the performance of four semi-analytical algorithms for the retrieval of chlorophyll a (Chl a) and phycocyanin (C-PC) from data acquired by the Compact Airborne Spectrographic Imager-2 (CASI-2) and the Airborne Imaging Spectrometer for Applications (AISA) Eagle sensor. The retrieval accuracies of the semi-analytical models were compared to those returned by optimally calibrated empirical band-ratio algorithms. The best-performing algorithm for the retrieval of Chl a was an empirical band-ratio model based on a quadratic function of the ratio of re!ectance at 710 and 670 nm (R2=0.832; RMSE=29.8%). However, this model only provided a marginally better retrieval than the best semi-analytical algorithm. The best-performing model for the retrieval of C-PC was a semi-analytical nested band-ratio model (R2=0.984; RMSE=3.98 mg m−3). The concentrations of C-PC retrieved using the semi-analytical model were correlated with cyanobacterial cell numbers (R2=0.380) and the particulate and total (particulate plus dissolved) pools of microcystins (R2=0.858 and 0.896 respectively). Importantly, both the empirical and semi-analytical algorithms were able to retrieve the concentration of C-PC at cyanobacterial cell concentrations below current warning thresholds for cyanobacteria in waterbodies. This demonstrates the potential of remote sensing to contribute to early-warning detection and monitoring of cyanobacterial blooms for human health protection at regional and global scales

Development of an empirical model for chlorophyll-a and Secchi Disk Depth estimation for a Pampean shallow lake (Argentina)

Shallow Pampean lakes are located in the most productive plain of Argentina. They are highly variable in salinity, turbidity and surface area. Laguna Chascomús has been monitored as a representative example of them. We developed a linear model based on satellite images validated against field measurements (2001–2011 period). A vegetation index and Landsat Surface Reflectance (Band 4) produced the best correlations with chlorophyll-a (Chl-a) and Secchi Disk Depth (SDD), respectively. In a second instance, a retrospective analysis (1986–2013) was performed. As a result, significant positive trends were observed for SDD and Chl-a. In addition, both variables displayed trends related to rainfall and site depth.Fil: Bohn, Vanesa Yael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; ArgentinaFil: Carmona, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Tandil. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Tandil; ArgentinaFil: Rivas, Raúl Eduardo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Tandil. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto de Hidrología de Llanuras - Sede Tandil; ArgentinaFil: Lagomarsino, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Diovisalvi, Nadia Rosalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); ArgentinaFil: Zagarese, Horacio Ernesto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús). Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas "Dr. Raúl Alfonsín" (sede Chascomús); Argentin

Estimating specific inherent optical properties of tropical coastal waters using bio-optical model inversion and in situ measurements: case of the Berau estuary, East Kalimantan, Indonesia

Specific inherent optical properties (SIOP) of the Berau coastal waters were derived from in situ measurements and inversion of an ocean color model. Field measurements of water-leaving reflectance, total suspended matter (TSM), and chlorophyll a (Chl a) concentrations were carried out during the 2007 dry season. The highest values for SIOP were found in the turbid waters, decreasing in value when moving toward offshore waters. The specific backscattering coefficient of TSM varied by an order of magnitude and ranged from 0.003 m2 g-1, for clear open ocean waters, to 0.020 m2 g-1, for turbid waters. On the other hand, the specific absorption coefficient of Chl a was relatively constant over the whole study area and ranged from 0.022 m2 mg-1, for the turbid shallow estuary waters, to 0.027 m2 mg-1, for deeper shelf edge ocean waters. The spectral slope of colored dissolved organic matter light absorption was also derived with values ranging from 0.015 to 0.011 nm-1. These original derived values of SIOP in the Berau estuary form a corner stone for future estimation of TSM and Chl a concentration from remote sensing data in tropical equatorial water

S190 interpretation techniques development and application to New York State water resources

The author has identified the following significant results. The program has demonstrated that Skylab imagery can be utilized to regularly monitor eutrophication indices of lakes, such as chlorophyll concentration and photic zone depth. The relationship between the blue to green reflectance ratio and chlorophyll concentration was shown, along with changes in lake properties caused by chlorophyll, lignin, and humic acid using reflectance ratios and changes. A data processing technique was developed for detecting atmospheric fluctuations occurring over a large lake

Remote sensing for Mapping TSM concentration in Mahakam Delta: an analytical approach

The Indonesian coastal zones have always been under heavy pressures, including those from fisheries, oil industries and sea transportation. The presence of these activities carry a large portion of risk in damaging the environment as well as in destroying the marine resources, leading to the need for an integrated management approach based on an environmental information system that is comprehensive and multi-disciplinary in nature. The Mahakam Delta has the same general problems as other coastal regions in Indonesia. The method is based on bio optical modeling. The forward water analysis comprised the laboratory measurements of water quality (TSM and Chl) and Inherent Optical Properties (IOPs) to derive Spesific Inherent Optical properties (SIOPs). SIOPs (of water, TSM, Chl and CDOM), coefficient f and B were used to developed R(0-) model. The inverse atmosphere analysis comprised the image preprocessing (i.e. geometric correction, atmospheric correction, air-water interface correction). The last step is inverse water analysis, which comprised the development of algorithm and image processing to develop TSM concentration maps. The spectrometer measurements collected in the field were used for obtaining the subsurface irradiance reflectance. The subsurface irradiance reflectance R(0-) is the ratio of upwelling (Ewu) and downwelling irradiance (Ewd) just beneath the water surface. There are some discrepancies from matching R(0-) model and R(0-) measured in the field, especially in the blue region and NIR region. The reason of the discrepancies could be due to the fact that the Q factor (the angular distribution factor of spectral radiance) is still not understood completely. This model is very susceptible to the decrease of the proportional factor f, and to the increase of the backscattering probability B. The results indicates that red band of satellite sensor is sensitive to detect higher TSM concentration. For Mahakam Delta, red band algorithm was used to derive TSM map, since higher TSM concentration occurred in the delta

Evaluation of Hyperspectral Indices for Chlorophyll-a Concentration Estimation in Tangxun Lake (Wuhan, China)

Chlorophyll-a (Chl-a) concentration is a major indicator of water quality which is harmful to human health. A growing number of studies have focused on the derivation of Chl-a concentration information from hyperspectral sensor data and the identification of best indices for Chl-a monitoring. The objective of this study is to assess the potential of hyperspectral indices to detect Chl-a concentrations in Tangxun Lake, which is the second largest lake in Wuhan, Central China. Hyperspectral reflectance and Chl-a concentration were measured at ten sample sites in Tangxun Lake. Three types of hyperspectral methods, including single-band reflectance, first derivative of reflectance, and reflectance ratio, were extracted from the spectral profiles of all bands of the hyperspectral sensor. The most appropriate bands for algorithms mentioned above were selected based on the correlation analysis. Evaluation results indicated that two methods, the first derivative of reflectance and reflectance ratio, were highly correlated (R2 > 0.8) with the measured Chl-a concentrations. Thus, the spatial and temporal variations of Chl-a concentration could be conveniently monitored with these hyperspectral methods

Improving Inland Water Quality Monitoring through Remote Sensing Techniques

Chlorophyll-a (chl-a) levels in lake water could indicate the presence of cyanobacteria, which can be a concern for public health due to their potential to produce toxins. Monitoring of chl-a has been an important practice in aquatic systems, especially in those used for human services, as they imply an increased risk of exposure. Remote sensing technology is being increasingly used to monitor water quality, although its application in cases of small urban lakes is limited by the spatial resolution of the sensors. Lake Thonotosassa, FL, USA, a 3.45-km2 suburban lake with several uses for the local population, is being monitored monthly by traditional methods. We developed an empirical bio-optical algorithm for the Moderate Resolution Imaging Spectroradiometer (MODIS) daily surface reflectance product to monitor daily chl-a. We applied the same algorithm to four different periods of the year using 11 years of water quality data. Normalized root mean squared errors were lower during the first (0.27) and second (0.34) trimester and increased during the third (0.54) and fourth (1.85) trimesters of the year. Overall results showed that Earth-observing technologies and, particularly, MODIS products can also be applied to improve environmental health management through water quality monitoring of small lakes

The Influence of the Zebra Mussel (Dreisena Polymorhpa) on Magnesium and Calcium Concentration in Water

In this study we examined changes in magnesium and calcium ion concentrations depending on Zebra Mussel biomass, pH values and temperature. We performed field experiments in years with different weather conditions using twelve 200 litre polycarbonate containers filled with 150 litres of non-filtered water from lowland, eutrophic reservoirs. Three treatments of the experiment were represented by: Phyto control with non-filtered water, Phyto+Dreis A with Zebra Mussel biomass of 500 g/m2, and Phyto+Dreis B with Zebra Mussel biomass of 1.000 g/m2. Magnesium and calcium ions concentrations were analyzed on an ion chromatograph (Dionex-1000). Results indicated a significant reduction in magnesium and calcium ion concentrations by Zebra Mussels (independent of mussel biomass), especially in the year with higher and more stable average temperatures. Mg concentration was significantly negatively correlated with temperature in this year. In both years of study the magnesium and calcium ion concentrations were negatively correlated with pH. Analyses of the Zebra Mussel's impact on magnesium and calcium loss from water, linked with the influence of physical factors (temperature and pH), may be valuable for the management of invaded ecosystems

Linking phytoplankton pigment composition and optical properties: A framework for developing remote-sensing metrics for monitoring cyanobacteria

International audienceThis study has been performed in the framework of a research program aiming to develop a low-cost aerial sensor for the monitoring of cyanobacteria in freshwater ecosystems that could be used for early detection. Several empirical and mechanistic remote-sensing tools have been already developed and tested at large scales and have proven useful in monitoring cyanobacterial blooms. However, the effectiveness of these tools for early detection is hard to assess because such work requires the detection of low concentrations of characteristic pigments amid complex ecosystems exhibiting several confounding factors (turbidity, blooms of other species, etc.). We developed a framework for performing high-throughput measurements of the absorbance and reflectance of small volumes (~= 20 mL) of controlled mixtures of phytoplankton species and studied the potential of this framework to validate remote-sensing proxies of cyanobacteria concentration. The absorption and reflectance spectra of single and multiple cultures carried a specific signal that allowed for the quantitative analysis of culture mixes. This specific signal was shown to be related to known pigment absorbance spectra. The concentrations of chlorophyll-a and -b, phycocyanin and phycoerythrin could be obtained from direct absorbance measurements and were correlated with the concentration obtained after pigment extraction (R2 ≥ 0.96 for all pigments). A systematic test of every possible two-band and three-band normalized difference between optical indices was then performed, and the coincidental correlation with chlorophyll-b (absent in cyanobacteria) was used as an indicator of non-specificity. Two-band indices were shown to suffer from non-specificity issues and could not yield strong and specific relationships with phycocyanin or phycoerythrin (maximum R2  0.8)