A first attempt at testing correlation between MODIS ocean colour data and in situ chlorophyll-a measurements within Maltese coastal waters

2011 ◽  
Author(s):  
A. Deidun ◽  
A. Drago ◽  
A. Gauci ◽  
A. Galea ◽  
J. Azzopardi ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Ocean Colour

scholarly journals CoastColour Round Robin data sets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

2015 ◽  
Vol 7 (2) ◽  
pp. 319-348 ◽  
Author(s):  
B. Nechad ◽  
K. Ruddick ◽  
T. Schroeder ◽  
K. Oubelkheir ◽  
D. Blondeau-Patissier ◽  
...  
Keyword(s):  
Water Quality ◽  
Coastal Waters ◽  
Reference Data ◽  
Quality Parameters ◽  
Round Robin ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Data Sets ◽  
Ocean Colour

Abstract. The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950. The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

scholarly journals Local, Daily, and Total Bio-Optical Models of Coastal Waters of Manfredonia Gulf Applied to Simulated Data of CHRIS, Landsat TM, MIVIS, MODIS, and PRISMA Sensors for Evaluating the Error

2020 ◽  
Vol 12 (9) ◽  
pp. 1428 ◽  
Author(s):  
Rosa Maria Cavalli
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Organic Material ◽  
Simulated Data ◽  
Local Models ◽  
Imaging Spectrometer ◽  
Mode 2 ◽  
Resolution Imaging ◽  
Remote Data

The spatial–temporal resolution of remote data covers coastal water variability, but this approach offers a lower accuracy than in situ observations. Two of the major error sources occur due to the parameterization of bio-optical models and spectral capability of the remote data. These errors were evaluated by exploiting data acquired in the coastal waters of Manfredonia Gulf. Chlorophyll-a concentrations, absorption of the colored dissolved organic material at 440 nm (aCDOM440nm), and tripton concentrations measured in situ varied between 0.09–1.76 mgm−3, 0.00–0.41 m−1, and 1.97–8.90 gm−3. In accordance with the position and time of in situ surveys, 36 local models, four daily models, and one total bio-optical model were parameterized and validated using in situ data before applying to Compact High-Resolution Imaging Spectrometer (CHRIS) mode 1, CHRIS mode 2, Landsat Thematic Mapper (TM), Multispectral Infrared and Visible Imaging Spectrometer (MIVIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Precursore Iperspettrale della Missione Applicativa (PRISMA) simulated data. Concentrations retrieved from PRISMA data using local models highlighted the smallest errors. Because tripton abundance is great and tripton absorptions were better resolved than those of chlorophyll-a and colored dissolved organic material (CDOM), tripton concentrations were adequately retrieved from all data using total models, while only local models adequately retrieved chlorophyll-a concentrations and aCDOM440nm from CHRIS mode 1, CHRIS mode 2, MIVIS, and MODIS data. Therefore, the application of local models shows smaller errors than those of daily and total models; however, the capability to resolve the absorption of water constituents and analyze their concentration range can dictate the model choice. Consequently, the integration of more models allows us to overcome the limitations of the data and sensors.

scholarly journals Bio-Optical Characteristics of the Black Sea Coastal Waters near Sevastopol: Assessment of the MODIS and VIIRS Products Accuracy

2021 ◽  
Vol 37 (2) ◽  
Author(s):  
E. Yu. Skorokhod ◽  
T. Ya. Churilova ◽  
T. V. Efimova ◽  
N. A. Moiseeva ◽  
V. V. Suslin ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Black Sea ◽  
Coastal Waters ◽  
Light Absorption ◽  
Ecological Monitoring ◽  
Optically Active ◽  
The Black Sea ◽  
Active Components ◽  
Chlorophyll A Concentration

Purpose. The purpose of the work is to evaluate accuracy of the satellite products for the coastal waters near Sevastopol, reconstructed by the standard algorithms based on the MODIS and VIIRS (installed at the artificial Earth satellites Aqua and Terra, and at Suomi NPP, respectively) data. Methods and Results. In situ sampling was carried out at the station (44°37'26" N and 33°26'05" E) located at a distance of two miles from the Sevastopol Bay. The chlorophyll a concentration was measured by the spectrophotometric method. The spectral light absorption coefficients by optically active components were measured in accordance with the current NASA protocol. The spectroradiometers MODIS and VIIRS Level 2 data with spatial resolution 1 km in nadir around the in situ station (44°37'26"±0°00'32" N and 33°26'05"±0°00'54" E) were used. The satellite products were processed by the SeaDAS 7.5.3 software developed in NASA. The research showed that the standard NASA algorithms being applied to the MODIS and VIIRS data, yielded incorrect values of the optically active components’ content in the Black Sea coastal waters near Sevastopol as compared to the data of in situ measurements in the same region: the satellite-derived “chlorophyll a concentration” was on average 1.6 times lower in spring, and 1.4 times higher in summer; the contribution of phytoplankton pigments to total light absorption at 443 nm was underestimated in 8.7 times; the light absorption by colored detrital organic matter was overestimated in 2.2 times. Conclusions. The NASA standard algorithms are inapplicable to calculating bio-optical indices in the coastal waters of the Black Sea near Sevastopol since they provide incorrect values of the satellite products (Ca-s, aph-s(443) and aCDM-s(443)). Operative ecological monitoring based on satellite data requires development of a regional algorithm taking into account the seawater optical features in the region and in the coastal zone, in particular.

scholarly journals Modelling Ocean Colour Derived Chlorophyll-a

2017 ◽  
Author(s):  
Stephanie Dutkiewicz ◽  
Anna E. Hickman ◽  
Oliver Jahn
Keyword(s):  
Chlorophyll A ◽  
Real World ◽  
World Ocean ◽  
Model Output ◽  
Ocean Colour ◽  
The Real ◽  
Chl A ◽  
Absolute Bias ◽  
Water Constituents

Abstract. This article provides a proof-of-concept for using a biogeochemical/ecosystem/optical model with radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour Chlorophyll-a (Chl-a) product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl-a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model) water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl-a (called derived Chl-a in this paper). We compare the derived Chl-a the actual model Chl-a field. In the model we find that the mean absolute bias due to the algorithm is 22 % between derived and actual Chl-a. The real world algorithm is found using concurrent in situ measurement of Chl-a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. We do find that regional specific algorithms provide a significant improvement. However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl-a and the actual Chl-a. These mismatches stem from temporal decoupling between Chl-a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter). The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation and peak of the spring bloom in the derived Chl-a lags the actual Chl-a by days and sometimes weeks. This result indicate care should also be taken when studying phenology through satellite derived products of Chl-a. This study also re-emphasises that ocean colour derived Chl-a is not the same as the real in situ Chl-a. In fact the model derived Chl-a compares better to real world Chl-a than the model actual Chl-a. Modellers should keep this is mind when evaluating model output with ocean colour Chl-a and in particular when assimilating this product. Our study spans several disciplines: Our goal is to illustrate the use of numerical laboratory that a) helps users of ocean colour, particularly modellers, gain further understanding of the products they use; and b) the ocean colour community could use to explore other ocean colour products, their biases and uncertainties, as well as to aid in future algorithm development.

Chlorophyll-a retrieval of coastal waters based on in situ hyperspectral data

2009 ◽  
Author(s):  
Wandong Ma ◽  
Ping Shi ◽  
Yuanzhi Zhang ◽  
Qianguo Xing ◽  
Jiakui Tang ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Hyperspectral Data

scholarly journals Mapping Chlorophyll-a Concentrations in the Kaštela Bay and Brač Channel Using Ridge Regression and Sentinel-2 Satellite Images

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3004
Author(s):  
Antonia Ivanda ◽  
Ljiljana Šerić ◽  
Marin Bugarić ◽  
Maja Braović
Keyword(s):  
Remote Sensing ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Coastal Waters ◽  
Optical Parameter ◽  
Data Set ◽  
Chl A ◽  
Sentinel 2

In this paper, we describe a method for the prediction of concentration of chlorophyll-a (Chl-a) from satellite data in the coastal waters of Kaštela Bay and the Brač Channel (our case study areas) in the Republic of Croatia. Chl-a is one of the parameters that indicates water quality and that can be measured by in situ measurements or approximated as an optical parameter with remote sensing. Remote sensing products for monitoring Chl-a are mostly based on the ocean and open sea monitoring and are not accurate for coastal waters. In this paper, we propose a method for remote sensing monitoring that is locally tailored to suit the focused area. This method is based on a data set constructed by merging Sentinel 2 Level-2A satellite data with in situ Chl-a measurements. We augmented the data set horizontally by transforming the original feature set, and vertically by adding synthesized zero measurements for locations without Chl-a. By transforming features, we were able to achieve a sophisticated model that predicts Chl-a from combinations of features representing transformed bands. Multiple Linear Regression equation was derived to calculate Chl-a concentration and evaluated quantitatively and qualitatively. Quantitative evaluation resulted in R2 scores 0.685 and 0.659 for train and test part of data set, respectively. A map of Chl-a of the case study area was generated with our model for the dates of the known incidents of algae blooms. The results that we obtained are discussed in this paper.

scholarly journals Bio-Optical Characteristics of the Black Sea Coastal Waters near Sevastopol: Assessment of the MODIS and VIIRS Products Accuracy

2021 ◽  
Vol 28 (2) ◽  
Author(s):  
E. Yu. Skorokhod ◽  
T. Ya. Churilova ◽  
T. V. Efimova ◽  
N. A. Moiseeva ◽  
V. V. Suslin ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Black Sea ◽  
Coastal Waters ◽  
Light Absorption ◽  
Ecological Monitoring ◽  
Optically Active ◽  
The Black Sea ◽  
Active Components ◽  
Chlorophyll A Concentration

Purpose. The purpose of the work is to evaluate accuracy of the satellite products for the coastal waters near Sevastopol, generated by the standard algorithms based on the MODIS and VIIRS (installed at the artificial Earth satellites Aqua and Terra, and at Suomi NPP, respectively) data. Methods and Results. In situ sampling was carried out at the station (44°37’26" N and 33°26’05" E) located at a distance of two miles from the Sevastopol Bay. The chlorophyll a concentration was measured by the spectrophotometric method. The spectral light absorption coefficients by optically active components were measured in accordance with the current NASA protocol. The spectroradiometers MODIS and VIIRS Level-2 data with spatial resolution 1 km in nadir around the in situ station (44°37’26"±0°00’32" N and 33°26’05"±0°00’54" E) were used. The satellite products were processed by the SeaDAS 7.5.3 software developed in NASA. The research showed that the standard NASA algorithms being applied to the MODIS and VIIRS data, yielded incorrect values of the optically active components’ content in the Black Sea coastal waters near Sevastopol as compared to the data of in situ measurements in the same region: the satellite-derived “chlorophyll a concentration” was on average 1.6 times lower in spring, and 1.4 times higher in summer; the contribution of phytoplankton to total light absorption at 443 nm was underestimated in 8.7 times; the light absorption by colored detrital matter was overestimated in 2.2 times. Conclusions. The NASA standard algorithms are inapplicable to calculating bio-optical indices in the coastal waters of the Black Sea near Sevastopol since they provide incorrect values of the satellite products (Ca-s, aph-s(443) and aCDM-s(443)). Operative ecological monitoring based on satellite data requires development of a regional algorithm taking into account the seawater optical features in the region and in the coastal zone, in particular.

scholarly journals CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

2015 ◽  
Vol 8 (1) ◽  
pp. 173-258 ◽  
Author(s):  
B. Nechad ◽  
K. Ruddick ◽  
T. Schroeder ◽  
K. Oubelkheir ◽  
D. Blondeau-Patissier ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Coastal Waters ◽  
Quality Parameters ◽  
Round Robin ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Ocean Colour ◽  
Water Quality Data

Abstract. The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive inter-comparison due to the availability of quality checked in situ databases. The CoastColour project Round Robin (CCRR) project funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). These datasets are available from doi.pangaea.de/10.1594/PANGAEA.841950. The datasets mainly consisted of 6484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Sign in / Sign up

Export Citation Format

Share Document