VIIRS Reflective Solar Bands Calibration Progress and Its Impact on Ocean Color Products

Sun, Junqiang; Wang, Menghua

doi:10.3390/rs8030194

Cited by 38 publications

(11 citation statements)

References 45 publications

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“…Using the coincident in situ TSM measurements and VIIRS-derived TSM (745) and TSM (862) , we further validate the VIIRS TSM retrieval algorithms in Lake Taihu. Previous studies have already shown that the SWIR-based atmospheric correction with MODIS can be used to drive nL w (λ) spectra with good accuracy in Lake Taihu [40,41], and the VIIRS sensor is well characterized and calibrated for all of the bands from the visible to SWIR wavelengths [55,70]. This shows that VIIRS-derived nL w (λ) spectra in Lake Taihu are reasonably accurate and can be used to produce other biogeochemical products, such as the TSM concentration.…”

Section: Discussionmentioning

confidence: 71%

Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

2018

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Normalized water-leaving radiance spectra nL w (λ), particle backscattering coefficients b bp (λ) in the near-infrared (NIR) wavelengths, and total suspended matter (TSM) concentrations over turbid waters are analytically correlated. To demonstrate the use of b bp (λ) in the NIR wavelengths in coastal and inland waters, we used in situ optics and TSM data to develop two TSM algorithms from measurements of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) using backscattering coefficients at the two NIR bands b bp (745) and b bp (862) for Lake Taihu. The correlation coefficients between the modeled TSM concentrations from b bp (745) and b bp (862) and the in situ TSM are 0.93 and 0.92, respectively. A different in situ dataset acquired between 2012 and 2016 for Lake Taihu was used to validate the performance of the NIR TSM algorithms for VIIRS-SNPP observations. TSM concentrations derived from VIIRS-SNPP observations with these two NIR b bp (λ)-based TSM algorithms matched well with in situ TSM concentrations in Lake Taihu between 2012 and 2016. The normalized root mean square errors (NRMSEs) for the two NIR algorithms are 0.234 and 0.226, respectively. The two NIR-based TSM algorithms are used to compute the satellite-derived TSM concentrations to study the seasonal and interannual variability of the TSM concentration in Lake Taihu between 2012 and 2016. In fact, the NIR-based TSM algorithms are analytically based with minimal in situ data to tune the coefficients. They are not sensitive to the possible nL w (λ) saturation in the visible bands for highly turbid waters, and have the potential to be used for estimation of TSM concentrations in turbid waters with similar NIR nL w (λ) spectra as those in Lake Taihu.

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Section: Discussionmentioning

confidence: 71%

Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

2018

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“…VIIRS-SNPP ocean color Environmental Data Records (EDR or Level-2 data) [28,29] are routinely produced from Sensor Data Records (SDR or Level-1B products) after sensor on-orbit calibrations [30,31] using the Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system, which is the official VIIRS ocean color data processing system. MSL12 was originally developed for providing consistent ocean color products from multiple satellite sensors [32][33][34].…”

Section: Viirs-snpp Ocean Color Datamentioning

confidence: 99%

VIIRS-Derived Water Turbidity in the Great Lakes

Son

Wang

2019

Remote Sensing

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Satellite ocean color products from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) since 2012 and in situ water turbidity measurements from the U.S. Environmental Protection Agency’s Great Lakes Environmental Database System are used to develop a water turbidity algorithm for satellite ocean color applications in the Great Lakes for water quality monitoring and assessments. Results show that the proposed regional algorithm can provide reasonably accurate estimations of water turbidity from satellite observations in the Great Lakes. Therefore, VIIRS-derived water turbidity data are used to investigate spatial and temporal variations in water turbidity for the entirety of the Great Lakes. Water turbidity values are overall the highest in Lake Erie, moderate in Lake Ontario, and relatively low in lakes Superior, Michigan, and Huron. Significantly high values in water turbidity appear in the nearshore regions, particularly in Thunder Bay (Lake Superior), Green Bay (Lake Michigan), and Saginaw Bay (Lake Huron). Seasonal patterns of water turbidity are generally similar in lakes Superior, Michigan, Huron, and Ontario, showing relatively high values in the spring and autumn months and lows in the winter season, while the seasonal pattern in Lake Erie is apparently different from the other lakes, with the highest value in the winter season and the lowest in the summer season. A strong interannual variability in water turbidity is shown in the time series of the VIIRS-derived water turbidity data for most of the lakes.

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“…Lastly, as a comparison study evaluates only the relative performance, the inference of the SNPP VIIRS M11 stability is drawn base on the combined results from numerous studies on calibration and intercomparison. The Chu et al [9] study has provided a detailed discussion of the stability of Aqua MODIS and SNPP VIIRS RSBs in the context of their on-orbit calibration [10,11,[14][15][16][17][18], and demonstrated the general good agreement between Aqua MODIS C6 data and the OC SDRs of SNPP VIIRS. In addition, the two SWIR band comparisons, Aqua MODIS B2 versus SNPP VIIRS M7 and Aqua MODIS B5 versus SNPP VIIRS M8, are further demonstrated to be the most stable, fully consistent with the understanding that the known RSB calibration error diminishes toward longer wavelength.…”

Section: Discussionmentioning

confidence: 97%

“…The official operational release of SDRs for SNPP VIIRS comes form the Interface Data Processing Segment (IDPS). However, an independent SDR version generated by the NOAA OC team has achieved significantly superior calibration for the RSBs [14][15][16][17][18]31] having corrected for an inherent worsening calibration bias within the standard on-orbit calibration methodology. The worsening error in the IDPS SDRs is particularly pronounced for bands M1 through M4.…”

Section: The Use Of the Noaa Idps And Ocean Color Team-generated Sdrsmentioning

confidence: 99%

Radiometric Evaluation of SNPP VIIRS Band M11 via Sub-Kilometer Intercomparison with Aqua MODIS Band 7 over Snowy Scenes

2018

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A refined intersensor comparison study is carried out to evaluate the radiometric stability of the 2257 nm channel (M11) of the first Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. This study is initiated as part of the examination into the performance of key shortwave infrared (SWIR) bands for SNPP VIIRS ocean color data processing and applications, with Band M11 playing key role over turbid and inland waters. The evaluation utilizes simultaneous nadir overpasses (SNOs) to compare SNPP VIIRS Band M11 against Band 7 of the MODerate-resolution Imaging Spectroradiometer (MODIS) in the Aqua satellite over concurrently observed scenes. The standard result of the radiance comparison is a seemingly uncontrolled and inconsistent time series unsuitable for further analyses, in great contrast to other matching band-pairs whose radiometric comparisons are typically stable around 1.0 within 1% variation. The mismatching relative spectral response (RSR) between the two respective bands, with SNPP VIIRS M11 at 2225 to 2275 nm and Aqua MODIS B7 at 2125 to 2175 nm, is demonstrated to be the cause of the large variation because of the different dependence of the spectral responses of the two bands over identical scenes. A consistent radiometric comparison time series, however, can be extracted from SNO events that occur over snowy surfaces. A customized selection and analysis procedure successfully identifies the snowy scenes within the SNO events and builds a stable comparison time series. Particularly instrumental for the success of the comparison is the use of the half-kilometer spatial resolution data of Aqua MODIS B7 that significantly enhances the statistics. The final refined time series of Aqua MODIS B7 radiance over the SNPP VIIRS M11 radiance is stable at around 0.39 within 2.5% showing no evidence of drift. The radiometric ratio near 0.39 suggests the strong presence of medium-grained snow of a mixed-snow condition in those SNO scenes leading to successful comparison. The multi-year stability indicates the correctness of the on-orbit RSB calibration of SNPP VIIRS M11 whose result does not suffer from long-term drift.

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VIIRS Reflective Solar Bands Calibration Progress and Its Impact on Ocean Color Products

Cited by 38 publications

References 45 publications

Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

VIIRS-Derived Water Turbidity in the Great Lakes

Radiometric Evaluation of SNPP VIIRS Band M11 via Sub-Kilometer Intercomparison with Aqua MODIS Band 7 over Snowy Scenes

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