scholarly journals Retrieval and mapping of chlorophyll-a concentration from Sentinel-2 images in an urban river in the semiarid region of Brazil

2020 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Alessandro Rhadamek Alves Pereira ◽  
João Batista Lopes ◽  
Giovana Mira de Espindola ◽  
Carlos Ernando da Silva
Keyword(s):  
Chlorophyll A ◽  
River Mouth ◽  
Water Quality Monitoring ◽  
Semiarid Region ◽  
Surface Reflectance ◽  
Chlorophyll A Concentration ◽  
In Situ Data ◽  
Sentinel 2A ◽  
Sentinel 2

Recently, the Poti river mouth region has experienced environmental impacts that resulted in a change of landscape in its dry season, highlighting the eutrophication and proliferation of phytoplankton, algae, cyanobacteria and aquatic plants. Considering the aspects related to water-quality monitoring in the semiarid region of Brazil from remote sensing, this study aimed to evaluate the performance of Sentinel-2A satellite data in the retrieval of chlorophyll-a concentration in Poti River in Teresina, Piaui, Brazil. The chlorophyll-a concentration retrieval and mapping methodology involved the study of the water surface reflectance in Sentinel-2A images and their correlation with the chlorophyll-a data collected in situ during the years 2016 and 2017. The results generated by the Chl-1, Ha et al. (2017), Chl-2, Page et al. (2018), and Chl-3, Kuhn et al. (2019) equations show the need for calibrating the algorithms used for the Poti River water components. However, the empirical algorithm Chl-2 shows a correlation has been established to identify the spatiotemporal variation of chlorophyll-a concentration along the Poti River broadly and not punctually. The spatial distribution of this pigment in maps derived from Sentinel-2A is consistent with the pattern of occurrence determined by the in situ data. Therefore, the MSI sensor proved to be a tool suitable for the retrieval and monitoring of chlorophyll-a concentration along the Poti River.

scholarly journals ESTIMATION OF CHLOROPHYLL-A CONCENTRATION FROM THE ATMOSPHERIC CORRECTION OF MISR DATA

2010 ◽  
Vol 3 (-) ◽  
Author(s):  
Sisir Kumar Dash ◽  
Tasuku Tanaka ◽  
Hiroyuki Hachiya ◽  
Yashuhiro Sugimori
Keyword(s):  
Chlorophyll A ◽  
Optical Thickness ◽  
Radiation Transfer ◽  
Atmospheric Correction ◽  
Ocean Surface ◽  
Aerosol Optical Thickness ◽  
Surface Reflectance ◽  
Chlorophyll A Concentration ◽  
In Situ Data

Multi Angle Imaging Spectro Radiometer (MISR) has a capability to observe the ocean surface from different viewing directions. Attempts were made to estimate the ocean surface reflectance and chlorophyll-a concentration using MISR data. The aerosol optical thickness (OAT), available from the MISR archive is compared with the results simulated using the 6S radiation transfer code. It turns out that the AOT values agree with each other up to 85 percent in certain areas in case-1 waters. Substituting the archive values of AOT into the radiative transfer process, we obtain the surface reflectance. This surface reflectance, in turn, is employed together with the in-water algorithm, to obtain the clhorophyll concentration maps for three viewing directions (aft, nadir and forward). The pattern of obtained chlorophyll map is reasonable. It is estimated that an error of about 35 percent is involved in the radiance calibration and AOT , Hence, with best possibility, the surface reflectance is quantified and the chlorophyll maps were generated. When it is compared with the nadir observation, the forward viewing camera overestimates and the aft viewing camera underestimates the chlorophyll-a concentrartion especially in case-1 waters. In case 2 waters, the chlorophyll-a concentration shows similiar patterns for the three different viewing directions. Due to lack of in-situ data, absolute chlorophyll values were ignored but errors were quatified for the surface reflectance and the aerosol optical thickness with the 6S simulated results. Keywords: MISR, 6S, AOT, Surface reflectance, Chlorophyll-a

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 Trophic status assessment of small turbid lakes comparing remote sensing and in situ data: case study at lower Danube floodplain

2020 ◽  
Vol 32 ◽  
pp. 53-63
Author(s):  
Stefan Kazakov ◽  
Valko Biserkov ◽  
Luchezar Pehlivanov ◽  
Stoyan Nedkov
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Suspended Matter ◽  
Trophic Status ◽  
Remote Sensing Data ◽  
Water Quality Monitoring ◽  
Floodplain Lakes ◽  
In Situ Data

The aim of the study was to compare in situ and remote sensing data, in order to assess the applicability of satellite images in water quality monitoring of floodplain lakes. Two indicators of trophic status were compared: chlorophyll a and total suspended matter. Two lakes on Lower Danube floodplain were selected: Srebarna and Malak Preslavets. Data were obtained in July and August 2018. Sentinel 2 MSI L1c images were analyzed in SeNtinel Application Platform (SNAP), (v. 6.0). According to in situ data, Srebarna Lake indicated status of eutrophication, while Malak Preslavets experienced hypertrophic conditions. Satellite data indicated eutrophic conditions for both lakes. Comparing the results from in situ and satellite data, chlorophyll a showed higher correlation (r = 0.66) and comparable results. On the other hand, significantly overestimation of suspended matter according to satellite data were found, as well weaker correlation (r = 0.57) between both methods. Remote sensing i.e. Sentinel products are emerging as a powerful tool in environmental observation. Although weather conditions could have significant impact on environmental dynamic especially in floodplain lakes, combining and comparing of different methods could improve the preciseness of the methodology as well as assessment reliability.

scholarly journals Spatial Variability Assessment on The High-resolution Chlorophyll-a Extraction from Landsat 8and Sentinel 2 Imageries in Johor Waters

2020 ◽  
Vol 2 ◽  
pp. 38-43
Author(s):  
Fatin Nabihah Syahira Ridzuan ◽  
Mohd Nadzri Md Reba ◽  
Monaliza Mohd Din ◽  
Mazlan Hashim ◽  
Po Teen Lim ◽  
...  
Keyword(s):  
High Resolution ◽  
Chlorophyll A ◽  
Spatial Resolution ◽  
Coastal Region ◽  
Water Quality Monitoring ◽  
Landsat 8 ◽  
Statistical Regression ◽  
Chl A ◽  
In Situ Data ◽  
Sentinel 2

High resolution Chlorophyll-a (Chl-a) can indicate the trophic status of the water and provide useful information on optical features of water body in water quality monitoring. Remote sensing has great potential to offer the spatial and temporal coverage needed. Over the last decades the Sea WIFS and MODIS were applied, but not suitable due to the low spatial resolution for monitoring Chl-a in coastal area. However, the retrieval of Chl-a in the coastal region is usually challenging due to the other in-water substances regardless of Chl-a, hence resulting in the satellite retrieved Chl-a overestimation. By the advancement of the Sentinel-2 and Landsat 8 satellites, continuous high resolution optical imageries have served for remarkable coastal mapping capability thanks to the spectroscopic capability certain spectral bands and as high as 10-meter spatial resolution. This paper aims to evaluate the performance of the SEADASS and SNAP processor for Chl-a estimation from the Operational Land Imager (OLI)and MultiSpectral Instrument(MSI) data in Johor waters. The representative models, in standard algorithm OC3and C2RCC, were adapted to retrieve Chl-a concentration. The statistical regression has shown that these algorithms give an acceptable Chl-a estimation at medium and high resolution with R2=0.44 from OC3and R2=0.55from C2RCC comparing to the in-situ data. Despite of the spatial, temporal and spectral variability, this paper shows that OLI and MSI could provide Chl-a mapping capability at suitable Chl-a estimation techniques.

scholarly journals Towards a merged satellite and in situ fluorescence ocean chlorophyll product

2012 ◽  
Vol 9 (6) ◽  
pp. 2111-2125 ◽  
Author(s):  
H. Lavigne ◽  
F. D'Ortenzio ◽  
H. Claustre ◽  
A. Poteau
Keyword(s):  
Chlorophyll A ◽  
Correction Coefficient ◽  
Data Set ◽  
Chlorophyll A Concentration ◽  
Profiling Float ◽  
In Situ Data ◽  
Biogeochemical Models ◽  
Wide Range ◽  
Similar Accuracy

Abstract. Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represent the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers have operated routinely on oceanographic cruises since the 1970s. Nevertheless, fluorescence is only a proxy of the total chlorophyll a concentration and a data calibration is required. Calibration issues are, however, sources of uncertainty, and they have prevented a systematic and wide range exploitation of the fluorescence data set. In particular, very few attempts to standardize the fluorescence databases have been made. Consequently, merged estimations with other data sources (e.g. satellite) are lacking. We propose a merging method to fill this gap. It consists firstly in adjusting the fluorescence profile to impose a zero chlorophyll a concentration at depth. Secondly, each point of the fluorescence profile is then multiplied by a correction coefficient, which forces the chlorophyll a integrated content measured on the fluorescence profile to be consistent with the concomitant ocean colour observation. The method is close to the approach proposed by Boss et al. (2008) to correct fluorescence data of a profiling float, although important differences do exist. To develop and test our approach, in situ data from three open ocean stations (BATS, HOT and DYFAMED) were used. Comparison of the so-called "satellite-corrected" fluorescence profiles with concomitant bottle-derived estimations of chlorophyll a concentration was performed to evaluate the final error (estimated at 31%). Comparison with the Boss et al. (2008) method, using a subset of the DYFAMED data set, demonstrated that the methods have similar accuracy. The method was applied to two different data sets to demonstrate its utility. Using fluorescence profiles at BATS, we show that the integration of "satellite-corrected" fluorescence profiles in chlorophyll a climatologies could improve both the statistical relevance of chlorophyll a averages and the vertical structure of the chlorophyll a field. We also show that our method could be efficiently used to process, within near-real time, profiles obtained by a fluorometer deployed on autonomous platforms, in our case a bio-optical profiling float. The application of the proposed method should provide a first step towards the generation of a merged satellite/fluorescence chlorophyll a product, as the "satellite-corrected" profiles should then be consistent with satellite observations. Improved climatologies with more consistent satellite and in situ data are likely to enhance the performance of present biogeochemical models.

scholarly journals Towards a merged satellite and in situ fluorescence ocean chlorophyll product

2011 ◽  
Vol 8 (6) ◽  
pp. 11899-11939
Author(s):  
H. Lavigne ◽  
F. D'Ortenzio ◽  
H. Claustre ◽  
A. Poteau
Keyword(s):  
Chlorophyll A ◽  
Correction Coefficient ◽  
Data Set ◽  
Chlorophyll A Concentration ◽  
Profiling Float ◽  
In Situ Data ◽  
Biogeochemical Models ◽  
Wide Range ◽  
Similar Accuracy

Abstract. Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represents the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers operate routinely on oceanographic cruise since the seventies. Nevertheless, fluorescence is only a proxy of the Total Chlorophyll-a concentration and a data calibration is required. Calibration issues are, however, source of uncertainty and they have prevented a systematic and wide range exploitation of the fluorescence data set. In particular, very few attempts to standardize the fluorescence data bases exist. Consequently, merged estimations with other data sources (i.e. satellite) are lacking. We propose a merging method to fill this gap. It consists firstly, in adjusting the fluorescence profile to impose a zero Chlorophyll-a concentration at depth. Secondly, each point of the fluorescence profile is then multiplied by a correction coefficient which forces the Chlorophyll-a integrated content measured on the fluorescence profile to be consistent with the concomitant ocean color observation. The method is close to the approach proposed by Boss et al. (2008) to calibrate fluorescence data of a profiling float, although important differences do exist. To develop and test our approach, in situ data from three open ocean stations (BATS, HOT and DYFAMED) were used. Comparison of the so-called "satellite-corrected" fluorescence profiles with concomitant bottle derived estimations of Chlorophyll-a concentration was performed to evaluate the final error, which resulted to be of about 31 %. Comparison with the Boss et al. (2008) method, carried out on a subset of the DYFAMED data set simulating a profiling float time series, demonstrated that the methods have similar accuracy. Applications of the method were then explored on two different data sets. Using fluorescence profiles at BATS, we show that the integration of "satellite-corrected" fluorescence profiles in Chlorophyll-a climatologies could improve both the statistical relevance of Chlorophyll-a averages and the vertical structure of the Chlorophyll-a field. We also show that our method could be efficiently used to process, within near-real time, profiles obtained by a fluorometer deployed on autonomous platforms, in our case a bio-optical profiling float. The wide application of the proposed method should provide a first step toward the generation of a merged satellite/fluorescence Chlorophyll-a product, as the "satellite-corrected" profiles should then be consistent with satellite observations. Improved climatologies and more consistent satellite and in situ data (comprising those from autonomous platforms) should strongly enhance the performance of present biogeochemical models.

scholarly journals Evaluation of Sentinel-2 and Landsat 8 Images for Estimating Chlorophyll-a Concentrations in Lake Chad, Africa

2020 ◽  
Vol 12 (15) ◽  
pp. 2437 ◽  
Author(s):  
Willibroad Gabila Buma ◽  
Sang-Il Lee
Keyword(s):  
Chlorophyll A ◽  
Satellite Images ◽  
Landsat 8 ◽  
Lake Chad ◽  
Chl A ◽  
Estimation Algorithms ◽  
In Situ Data ◽  
Fluorescence Line ◽  
Sentinel 2

Much effort has been applied in estimating the concentrations of chlorophyll-a (Chl a) in lakes. The optical complexity and lack of in situ data complicate estimating Chl a in such water bodies. We compared four established satellite reflectance algorithms—the two-band and three-band algorithms (2BDA, 3BDA), fluorescence line height (FLH), and normalized difference chlorophyll index (NDCI)—to estimate Chl a concentration in Lake Chad. We evaluated the performance and applicability of Landsat-8 (L8) and Sentinel-2 (S2) images with the four Chl a estimation algorithms. For accuracy, we compared the concentration levels from the four algorithms to those from Worldview-3 (WV3) images. We identified two promising algorithms that could be used alongside L8 and S2 satellite images to monitor Chl a concentrations in Lake Chad. With an averaged R2 of 0.8, the 3BDA and NDCI Chl a algorithms performed accurately with S2 and L8 images. For the S2 and L8 images, 3BDA had the highest performance when compared to the WV3 estimates. We demonstrate the usefulness of sensor images in improving water quality information for areas that are difficult to access or when conventional data are limited.

scholarly journals Performance of a Handheld Chlorophyll-a Fluorometer: Potential Use for Rapid Algae Monitoring

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1409
Author(s):  
Hamdhani Hamdhani ◽  
Drew E. Eppehimer ◽  
David Walker ◽  
Michael T. Bogan
Keyword(s):  
Chlorophyll A ◽  
Surface Waters ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Water Quality Monitoring ◽  
Ambient Light ◽  
Calibration Equation ◽  
Field Samples ◽  
Potential Use

Chlorophyll-a measurements are an important factor in the water quality monitoring of surface waters, especially for determining the trophic status and ecosystem management. However, a collection of field samples for extractive analysis in a laboratory may not fully represent the field conditions. Handheld fluorometers that can measure chlorophyll-a in situ are available, but their performance in waters with a variety of potential light-interfering substances has not yet been tested. We tested a handheld fluorometer for sensitivity to ambient light and turbidity and compared these findings with EPA Method 445.0 using water samples obtained from two urban lakes in Tucson, Arizona, USA. Our results suggested that the probe was not sensitive to ambient light and performed well at low chlorophyll-a concentrations (<25 µg/L) across a range of turbidity levels (50–70 NTU). However, the performance was lower when the chlorophyll-a concentrations were >25 µg/L and turbidity levels were <50 NTU. To account for this discrepancy, we developed a calibration equation to use for this handheld fluorometer when field monitoring for potential harmful algal blooms in water bodies.

scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

Sign in / Sign up

Export Citation Format

Share Document