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 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 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 Simultaneous determination of aerosol optical thickness and water leaving radiance from multispectral measurements in coastal waters

2017 ◽  
Author(s):  
Chong Shi ◽  
Teruyuki Nakajima
Keyword(s):  
Simultaneous Determination ◽  
Optical Thickness ◽  
Coastal Waters ◽  
Atmospheric Correction ◽  
Ocean Surface ◽  
Aerosol Optical Thickness ◽  
Surface Model ◽  
Spectral Measurements ◽  
Mean Square Errors

Abstract. Retrieval of aerosol optical properties and water leaving radiance over ocean is changeling since the latter mostly accounts for ~10% of satellite observed signal and can be easily contaminated by the atmospheric scattering. Such an effort would be more difficulty in turbid coastal waters due to the existence of optically complex oceanic substances or high aerosol loading. In an effort to solve such problems, we present an optimization approach for the simultaneous determination of aerosol optical thickness (AOT) and normalized water leaving radiance (nLw) from multi-spectral measurements. In this algorithm, a coupled atmosphere-ocean radiative transfer model combined with a comprehensive bio-optical oceanic module is used to jointly simulate the satellite observed reflectance at the top of atmosphere and water leaving radiance just above the ocean surface. Then a full-physical nonlinear optimization method is adopted to retrieve AOT and nLw in one step. The algorithm is validated using Aerosol Robotic Network Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observation cases covered both in and out of sun glint from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements in each site. It is demonstrated that more accurate AOT are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sun glint conditions, where the averaged percentage difference (APD) of retrieved AOT generally reduce by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme. It is caused that all the spectral measurements can be used jointly to increase the information content in the inversion of AOT and the wind speed is also simultaneously retrieved to compensate the specular reflectance error estimated from the rough ocean surface model. For the retrieval of nLw, over atmospheric correction can be avoided to have a significant improvement for the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443)/nLw(554) and nLw(488)/nLw(554), which are employed in the inversion of chlorophyll a concentration (Chl), are obtained using simultaneous retrieval approach with less root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as a result that the APD value of retrieved Chl decreases by about 5 %. On the other hand, the standard AC scheme yields a more accurate retrieval of nLw at 488 nm, prompting a further optimization of oceanic bio-optical module of current model.

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 iCOR Atmospheric Correction on Sentinel-3/OLCI over Land: Intercomparison with AERONET, RadCalNet, and SYN Level-2

2021 ◽  
Vol 13 (4) ◽  
pp. 654
Author(s):  
Erwin Wolters ◽  
Carolien Toté ◽  
Sindy Sterckx ◽  
Stefan Adriaensen ◽  
Claire Henocq ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Vegetation Indices ◽  
Atmospheric Correction ◽  
Negative Bias ◽  
Surface Reflectance ◽  
Temporal Consistency ◽  
Correction Algorithm ◽  
Land Surfaces ◽  
Relative Differences ◽  
Level 2

To validate the iCOR atmospheric correction algorithm applied to the Sentinel-3 Ocean and Land Color Instrument (OLCI), Top-of-Atmosphere (TOA) observations over land, globally retrieved Aerosol Optical Thickness (AOT), Top-of-Canopy (TOC) reflectance, and Vegetation Indices (VIs) were intercompared with (i) AERONET AOT and AERONET-based TOC reflectance simulations, (ii) RadCalNet surface reflectance observations, and (iii) SYN Level 2 (L2) AOT, TOC reflectance, and VIs. The results reveal that, overall, iCOR’s statistical and temporal consistency is high. iCOR AOT retrievals overestimate relative to AERONET, but less than SYN L2. iCOR and SYN L2 TOC reflectances exhibit a negative bias of ~−0.01 and −0.02, respectively, in the Blue bands compared to the simulations. This diminishes for RED and NIR, except for a +0.02 bias for SYN L2 in the NIR. The intercomparison with RadCalNet shows relative differences < ±6%, except for bands Oa02 (Blue) and Oa21 (NIR), which is likely related to the reported OLCI “excess of brightness”. The intercomparison between iCOR and SYN L2 showed R2 = 0.80–0.93 and R2 = 0.92–0.96 for TOC reflectance and VIs, respectively. iCOR’s higher temporal smoothness compared to SYN L2 does not propagate into a significantly higher smoothness for TOC reflectance and VIs. Altogether, we conclude that iCOR is well suitable to retrieve statistically and temporally consistent AOT, TOC reflectance, and VIs over land surfaces from Sentinel-3/OLCI observations.

Consistent retrieval of cloud/aerosol single scattering properties and surface reflectance

2021 ◽  
Author(s):  
Marta Luffarelli ◽  
Yves Govaerts
Keyword(s):  
Radiative Transfer ◽  
Optical Thickness ◽  
Solution Space ◽  
Single Scattering ◽  
Aerosol Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Reflectance ◽  
Earth System ◽  
System Components

&lt;p&gt;The CISAR (Combined Inversion of Surface and AeRosols) algorithm is exploited in the framework of the ESA Aerosol Climate Change Initiatiave (CCI) project, aiming at providing a set of atmospheric (cloud and aerosol) and surface reflectance products derived from S3A/SLSTR observations using the same radiative transfer physics and assumptions. CISAR is an advance algorithm developed by Rayference originally designed for the retrieval of aerosol single scattering properties and surface reflectance from both geostationary and polar orbiting satellite observations. &amp;#160;It is based on the inversion of a fast radiative transfer model (FASTRE). The retrieval mechanism allows a continuous variation of the aerosol and cloud single scattering properties in the solution space.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Traditionally, different approaches are exploited to retrieve the different Earth system components, which could lead to inconsistent data sets. The simultaneous retrieval of different atmospheric and surface variables over any type of surface (including bright surfaces and water bodies) with the same forward model and inversion scheme ensures the consistency among the retrieved Earth system components. Additionally, pixels located in the transition zone between pure clouds and pure aerosols are often discarded from both cloud and aerosol algorithms. This &amp;#8220;twilight zone&amp;#8221; can cover up to 30% of the globe. A consistent retrieval of both cloud and aerosol single scattering properties with the same algorithm could help filling this gap.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The CISAR algorithm aims at overcoming the need of an external cloud mask, discriminating internally between aerosol and cloud properties. This approach helps reducing the overestimation of aerosol optical thickness in cloud contaminated pixels. The surface reflectance product is delivered both for cloud-free and cloudy observations. &amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Global maps obtained from the processing of S3A/SLSTR observations will be shown. The SLSTR/CISAR products over events such as, for instance, the Australian fire in the last months of 2019, will be discussed in terms of aerosol optical thickness, aerosol-cloud discrimination and fine/coarse mode fraction.&lt;/p&gt;

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