Establishing optimal matchup protocols between ocean color satellites and ground truth AeroNET-OC radiance

Lawson, Adam; Ladner, Sherwin; Crout, Richard; Wood, Christopher G.; Arnone, Robert; Bowers, Jennifer; Martinolich, Paul; Lewis, D. T.

doi:10.1117/12.2521062

Cited by 3 publications

(7 citation statements)

References 4 publications

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“…Several outlying match-ups are removed by the strict matchup constraints. In previous tests of the individual match-up criteria, the stray-light flag was responsible for the greatest reduction in the available match-ups [6], and in this case we have lost approximately 65% of the match-ups when applying the strict criteria. When applying the permissive and strict constraints to only the center pixel, a similar shift is observed (Figure 4).…”

Section: Wavecis Aeronet Sitementioning

confidence: 69%

“…These constraints also incorporate additional quality flags for high glint (HIGLINT), stray light (STRAYLIGHT), navigation failure (NAVFAIL), and low water-leaving radiance (LOWLW). These protocols have been previously observed to reduce the number of match-ups, while improving the overall statistics [6]. The summary of protocols can be seen in Table 1.…”

Section: Methodsmentioning

confidence: 97%

“…Previously acquired data is refreshed regularly to maintain a direct correlation between SAVANT holdings and any corrections NASA may make. The initial assessment utilizes WaveCIS data [6]. The Venise data are provided and maintained by Giuseppe Zibordi.…”

Section: Methodsmentioning

confidence: 99%

“…SAVANT's quality controls (Figure 2) include setting constraints for (a) the geographical box size of the average satellite data (1 km, 9 km, and 25 km), (b) the maximum temporal difference between the satellite overpass and the in situ measurement, (c) limiting the maximum observed windspeed (defaults to 8 ms −1 maximum) and aerosol optical thickness (defaults to 0.2), (d) the minimum and maximum valid normalized water-leaving radiance values, (e) the maximum coefficient of variance within the satellite box (measured standard deviation divided by measured mean, per match-up), (f) the number of valid satellite pixels (50% of the 5 × 5 box, for example, requiring 13 pixels to be valid), and (g) applying the following various quality control flags: high glint, maximum aerosol iteration [5], high polarization, stray light, absorbing aerosol, moderate sun glint, navigation failure, turbid water, low water-leaving radiance, epsilon out of range, and the high satellite and solar zenith flags. Previously, we set constraint thresholds and adjusted the individual constraints [6], in order to observe the impact of each individual constraint on the spectral ocean color and in situ match-ups. We defined protocols by determining what constraints were the closest to the optimum (based on statistical performance) match-up for use at the WaveCIS site.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Satellite Ocean Color Match-Up Protocols Using the Satellite Validation Navy Tool (SAVANT) at MOBY and Two AERONET-OC Sites

Lawson

Bowers²,

Ladner

et al. 2021

Remote Sensing

Self Cite

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The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory to help facilitate the assessment of the stability and accuracy of ocean color satellites, using numerous ground truth (in situ) platforms around the globe and support methods for match-up protocols. The effects of varying spatial constraints with permissive and strict protocols on match-up uncertainty are evaluated, in an attempt to establish an optimal satellite ocean color calibration and validation (cal/val) match-up protocol. This allows users to evaluate the accuracy of ocean color sensors compared to specific ground truth sites that provide continuous data. Various match-up constraints may be adjusted, allowing for varied evaluations of their effects on match-up data. The results include the following: (a) the difference between aerosol robotic network ocean color (AERONET-OC) and marine optical Buoy (MOBY) evaluations; (b) the differences across the visible spectrum for various water types; (c) spatial differences and the size of satellite area chosen for comparison; and (d) temporal differences in optically complex water. The match-up uncertainty analysis was performed using Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) SNPP data at the AERONET-OC sites and the MOBY site. It was found that the more permissive constraint sets allow for a higher number of match-ups and a more comprehensive representation of the conditions, while the restrictive constraints provide better statistical match-ups between in situ and satellite sensors.

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Section: Wavecis Aeronet Sitementioning

confidence: 69%

Section: Methodsmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analyzing Satellite Ocean Color Match-Up Protocols Using the Satellite Validation Navy Tool (SAVANT) at MOBY and Two AERONET-OC Sites

Lawson

Bowers²,

Ladner

et al. 2021

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Its approach includes the satellite data finder and the match-up extractor, both designed to work only with NASA's Ocean Biology Distributed Active Archive Center (OB.DAAC) Level-2 products. The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory (Lawson et al, 2021). SAVANT implements validation analysis in three steps: ingestion of satellite and in situ data into a database in addition to a set of metadata; match-up filtering according to the quality control criteria defined by the user; and production of validation graphs and statistical information.…”

Section: Introductionmentioning

confidence: 99%

Validation of satellite water products based on HYPERNETS in situ data using a Match-up Database (MDB) file structure

González Vilas,

Brando,

Concha

et al. 2024

Front. Remote Sens.

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A Match-up Database (MDB) file structure and tools were developed to ease the validation analysis of satellite water products and to improve the exchange and processing of match-up data from different sites, missions and atmospheric correction processors. In situ remote sensing reflectance (Rrs) measurements were available from the HYPSTAR® (HYperspectral Pointable System for Terrestrial and Aquatic Radiometry), a new automated hyperspectral radiometer. An MDB file is a NetCDF file containing all the potential match-ups between satellite and in situ data on a specific site and within a given time window. These files are generated and manipulated with three modules developed in Python to implement the validation protocols: extract satellite data, associate each extract with co-located in situ radiometry data, and then perform the validation analysis. This work provides details on the implementation of the open-source MDB file structure and tools. The approach is demonstrated by a multi-site matchup comparison based on satellite data from the Sentinel-2 MSI and Sentinel-3 OLCI sensors, and HYPSTAR® data acquired over six water sites with diverse optical regimes from February 2021 to March 2023.The analysis of Sentinel-3 OLCI matchups across the six sites shows consistency with previous comparisons based on AERONET-OC data over extended reflectance range. We evaluated Sentinel-2 MSI reflectance data corrected with two atmospheric correction processors (ACOLITE and C2RCC) over four sites with clear to highly turbid waters. Results showed that the performance of the processors depends on the optical regime of the sites. Overall, we proved the suitability of the open-source MDB-based approach to implement validation protocols and generate automated matchup analyses for different missions, processors and sites.

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Characterization and absolute calibration of an AERONET-OC radiometer

et al. 2021

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The Ocean Color component of the global Aerosol Robotic Network (AERONET-OC) utilizes CE-318 sun photometers modified for above-water radiometry from fixed structures such as oil rigs, lighthouses, and service platforms. Primarily, AERONET-OC measurements allow determination of the water-leaving radiance required for the validation of ocean color satellite data products. One instrument from the AERONET–OC network, identified as AERONET #080, was studied in this work. A laser-illuminated integrating sphere of known radiance enabled determination of the linearity with flux and absolute radiance responsivity at multiple wavelengths within seven of the AERONET #080 filter bands. We compared the results to calibrations from the AERONET facility at the Goddard Space Flight Center of the National Aeronautics and Space Administration and from the Joint Research Centre of the European Commission. These results agree within the estimated mean comparison uncertainty of 1.88 % ( k = 2 ). We also assessed these results using calibrated lamp-illuminated integrating spheres and observed a spectral dependence to the comparison results that is unexplained.

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Establishing optimal matchup protocols between ocean color satellites and ground truth AeroNET-OC radiance

Cited by 3 publications

References 4 publications

Analyzing Satellite Ocean Color Match-Up Protocols Using the Satellite Validation Navy Tool (SAVANT) at MOBY and Two AERONET-OC Sites

Analyzing Satellite Ocean Color Match-Up Protocols Using the Satellite Validation Navy Tool (SAVANT) at MOBY and Two AERONET-OC Sites

Validation of satellite water products based on HYPERNETS in situ data using a Match-up Database (MDB) file structure

Characterization and absolute calibration of an AERONET-OC radiometer

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