scholarly journals Chlorophyll-a concentration retrieval in eutrophic lakes in Lithuania from Sentinel-2 data

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Dalia Grendaitė ◽  
Edvinas Stonevičius ◽  
Jūratė Karosienė ◽  
Ksenija Savadova ◽  
Jūratė Kasperovičienė
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Remote Sensing Data ◽  
Empirical Equations ◽  
Active Constituent ◽  
Eutrophic Lakes ◽  
Band Ratio ◽  
Local Conditions ◽  
Chlorophyll A Concentration ◽  
Sentinel 2

Inland waters are an important habitat for flora and fauna and are also used for aesthetic, recreational, and industrial needs; therefore, monitoring the current state of freshwaters and applying measures to improve water quality are of high importance. To have an efficient monitoring system that could cover large areas, the use of remote sensing data is crucial. In this study the suitability of the Sentinel-2 Multispectral Imager data is tested for observing cyanobacteria bloom events in the eutrophic lakes and retrieving the chlorophyll-a concentration – an indicator of phytoplankton biomass. The analysis is carried out using data from four lakes in Lithuania – two eutrophic blooming lakes and two oligo-mesotrophic non-blooming lakes. The results showed that reflectances are higher in the eutrophic lakes than in the oligo-mesotrophic lakes due to the presence of an optically active constituent, namely, chlorophyll-a pigment. We tested empirical equations for chlorophyll-a concentration retrieval in eutrophic lakes derived in other studies to check whether they could be used without adaptation to local conditions. Most of the equations performed well (R2 = 0.5–0.8); however, they had high RMSEs = 17–53 μg L–1. The equation used with the bottom of atmosphere data CHL8_L2A (R2 = 0.76) had the lowest RMSE = 9 μg L–1. In addition, we derived empirical equations for eutrophic lakes in Lithuania. The equations that were based on the Sentinel-2 band ratio B5/B4 and the three band (B4, B5, and B8A) expression performed the best (R2 = 0.77–0.79) and had lower RMSE = 7 μg L–1 than empirical equations from other studies. A larger in situ dataset could improve the algorithm performance in retrieving the chlorophyll-a concentration. The first attempts to map water quality parameters in eutrophic lakes in Lithuania using the data received from the Sentinel-2 MSI sensor show good results, as the changes in reflectance, caused by the changes in chlorophyll-a concentration, can be seen from satellite images.

scholarly journals OPTMIZATION OF BIO-OPTICAL MODEL PARAMETERS FOR TURBID LAKE WATER QUALITY ESTIMATION USING LANDSAT 8 AND WASI-2D

2020 ◽  
Vol XLII-3/W11 ◽  
pp. 67-72
Author(s):  
A. Manuel ◽  
A. C. Blanco ◽  
A. M. Tamondong ◽  
R. Jalbuena ◽  
O. Cabrera ◽  
...  
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
The Philippines ◽  
Quality Data ◽  
Model Parameters ◽  
Landsat 8 ◽  
Water Quality Data ◽  
Chlorophyll A Concentration ◽  
In Situ Data

Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.

scholarly journals Evaluation of Satellite-Based Algorithms to Retrieve Chlorophyll-a Concentration in the Canadian Atlantic and Pacific Oceans

2019 ◽  
Vol 11 (22) ◽  
pp. 2609 ◽  
Author(s):  
Stephanie Clay ◽  
Angelica Peña ◽  
Brendan DeTracey ◽  
Emmanuel Devred
Keyword(s):  
Chlorophyll A ◽  
Science Studies ◽  
Infrared Imaging ◽  
Seasonal Pattern ◽  
Wide Field ◽  
Ocean Colour ◽  
Band Ratio ◽  
Chlorophyll A Concentration ◽  
Ocean Science ◽  
Moderate Resolution Imaging Spectroradiometer

Remote-sensing reflectance data collected by ocean colour satellites are processed using bio-optical algorithms to retrieve biogeochemical properties of the ocean. One such important property is the concentration of chlorophyll-a, an indicator of phytoplankton biomass that serves a multitude of purposes in various ocean science studies. Here, the performance of two generic chlorophyll-a algorithms (i.e., a band ratio one, Ocean Colour X (OCx), and a semi-analytical one, Garver–Siegel Maritorena (GSM)) was assessed against two large in situ datasets of chlorophyll-a concentration collected between 1999 and 2016 in the Northeast Pacific (NEP) and Northwest Atlantic (NWA) for three ocean colour sensors: Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS). In addition, new regionally-tuned versions of these two algorithms are presented, which reduced the mean error (mg m−3) of chlorophyll-a concentration modelled by OCx in the NWA from −0.40, −0.58 and −0.45 to 0.037, −0.087 and −0.018 for MODIS, SeaWiFS, and VIIRS respectively, and −0.34 and −0.36 to −0.0055 and −0.17 for SeaWiFS and VIIRS in the NEP. An analysis of the uncertainties in chlorophyll-a concentration retrieval showed a strong seasonal pattern in the NWA, which could be attributed to changes in phytoplankton community composition, but no long-term trends were found for all sensors and regions. It was also found that removing the 443 nm waveband for the OCx algorithms significantly improved the results in the NWA. Overall, GSM performed better than the OCx algorithms in both regions for all three sensors but generated fewer chlorophyll-a retrievals than the OCx algorithms.

scholarly journals First Results of Phytoplankton Spatial Dynamics in Two NW-Mediterranean Bays from Chlorophyll-a Estimates Using Sentinel 2: Potential Implications for Aquaculture

2019 ◽  
Vol 11 (15) ◽  
pp. 1756 ◽  
Author(s):  
Soriano-González ◽  
Angelats ◽  
Fernández-Tejedor ◽  
Diogene ◽  
Alcaraz
Keyword(s):  
Chlorophyll A ◽  
Spatial Dynamics ◽  
Ebro Delta ◽  
Band Ratio ◽  
Environmental Forcing ◽  
Shellfish Farming ◽  
First Results ◽  
Nw Mediterranean ◽  
Sentinel 2A ◽  
Sentinel 2

Shellfish aquaculture has a major socioeconomic impact on coastal areas, thus it is necessary to develop support tools for its management. In this sense, phytoplankton monitoring is crucial, as it is the main source of food for shellfish farming. The aim of this study was to assess the applicability of Sentinel 2 multispectral imagery (MSI) to monitor the phytoplankton biomass at Ebro Delta bays and to assess its potential as a tool for shellfish management. In situ chlorophyll-a data from Ebro Delta bays (NE Spain) were coupled with several band combination and band ratio spectral indices derived from Sentinel 2A levels 1C and 2A for time-series mapping. The best results (AIC = 72.17, APD < 10%, and MAE < 0.7 mg/m3) were obtained with a simple blue-to-green ratio applied over Rayleigh corrected images. Sentinel 2–derived maps provided coverage of the farm sites at both bays allowing relating the spatiotemporal distribution of phytoplankton with the environmental forcing under different states of the bays. The applied methodology will be further improved but the results show the potential of using Sentinel 2 MSI imagery as a tool for assessing phytoplankton spatiotemporal dynamics and to encourage better future practices in the management of the aquaculture in Ebro Delta bays.

scholarly journals Assessing the potential of integrating Landsat sensors for estimating chlorophyll-a concentration in a reservoir

2017 ◽  
Vol 49 (5) ◽  
pp. 1608-1617 ◽  
Author(s):  
Matias Bonansea ◽  
Claudia Rodriguez ◽  
Lucio Pinotti
Keyword(s):  
Water Quality ◽  
Chlorophyll A ◽  
Landsat Imagery ◽  
Quality Parameters ◽  
Landsat 8 ◽  
Chlorophyll A Concentration ◽  
Chl A ◽  
Sensing Applications ◽  
Wide Range ◽  
Quality Assessments

Abstract Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 = 0.88). Using observed versus predicted Chl-a values the model was validated (R2 = 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.

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