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Journal ArticleDOI

Dynamic range and sensitivity requirements of satellite ocean color sensors: learning from the past

TL;DR: This study quantifies signal dynamic range and sensitivity parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission.
Abstract: Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

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Citations
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Journal ArticleDOI
TL;DR: An overview of the state of the art in atmospheric correction algorithms is provided, recent advances are highlighted and the possible potential for hyperspectral data to address the current challenges is discussed.
Abstract: Accurate correction of the corrupting effects of the atmosphere and the water’s surface are essential in order to obtain the optical, biological and biogeochemical properties of the water from satellite-based multi- and hyper-spectral sensors. The major challenges now for atmospheric correction are the conditions of turbid coastal and inland waters and areas in which there are strongly-absorbing aerosols. Here, we outline how these issues can be addressed, with a focus on the potential of new sensor technologies and the opportunities for the development of novel algorithms and aerosol models. We review hardware developments, which will provide qualitative and quantitative increases in spectral, spatial, radiometric and temporal data of the Earth, as well as measurements from other sources, such as the Aerosol Robotic Network for Ocean Color (AERONET-OC) stations, bio-optical sensors on Argo (Bio–Argo) floats and polarimeters. We provide an overview of the state of the art in atmospheric correction algorithms, highlight recent advances and discuss the possible potential for hyperspectral data to address the current challenges.

490 citations


Cites background from "Dynamic range and sensitivity requi..."

  • ...Unfortunately, both of these sensors have been plagued with issues, such as unreliable spectral and radiometric calibration [100] and their low signal-to-noise ratio (SNR), especially over bodies of water, and this often leads to poor retrievals [101,102], e....

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  • ...The GEO-CAPE mission will provide high spectral, spatial, radiometric and temporal resolution, although as it will be positioned in a geostationary orbit, it will provide only products for the Americas, not global coverage [101,150]....

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Journal ArticleDOI
TL;DR: Aquatic color radiometry remote sensing of coastal and inland water bodies is of great interest to a wide variety of research, management, and commercial entities as well as the general public as mentioned in this paper.

243 citations


Cites background from "Dynamic range and sensitivity requi..."

  • ...For example, the near infrared (NIR) channels (MODIS 748 and 869 nm) are designed to have high sensitivity (signal-to-noise ratio (SNR) N 800:1, Hu et al., 2012b) to improve atmospheric correction, yet these bands tend to saturate over highly turbid waters (suspended sediment concentration N ~35 mg…...

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Journal ArticleDOI
TL;DR: In this article, Vanhellemont et al. presented the use of the high quality SWIR bands of the Operational Land Imager (OLI) on Landsat-8, launched in 2013, to extend their existing turbid water atmospheric correction to extremely turbid waters.

241 citations

Journal ArticleDOI
TL;DR: A synopsis of the current state of the art in the retrieval of core optical properties from satellite ocean color is presented and recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches are made.

220 citations


Cites background from "Dynamic range and sensitivity requi..."

  • ...They are wellcalibrated sensors with dynamic ranges and signal-to-noise characteristics necessary for observing ocean properties (Hu et al., 2012)....

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Journal ArticleDOI
TL;DR: The European Space Agency's Sentinel-2A mission with the MultiSpectral Instrument (MSI) onboard was launched in 2015, initiating a new era in high-to-moderate-resolution (i.e., 10 to 60m) imaging of Earth's resources as discussed by the authors.

202 citations


Cites background from "Dynamic range and sensitivity requi..."

  • ..., SNR(443) = 1000) for existing (Hu et al., 2012) and/or future (Del Castillo et al....

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  • ...Therefore, the overall radiometric quality of MSI and OLI products is comparable, and both are found to offer more precise measurements than those of the heritage Landsat missions over aquatic systems (Franz et al., 2015; Gerace et al., 2013; Hu et al., 2012; Pahlevan and Schott, 2013)....

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  • ...Note, however, that MSI and OLI SNRs are still considerably below the radiometric requirements recommended (e.g., SNR(443) = 1000) for existing (Hu et al., 2012) and/or future (Del Castillo et al., 2012) ocean color missions....

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References
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Journal ArticleDOI
TL;DR: It is shown, using aerosol models, that certain assumptions regarding the spectral behavior of the aerosol reflectance employed in the standard CZCS correction algorithm are not valid over the spectral range encompassing both the visible and the NIR.
Abstract: The second generation of ocean-color-analyzing instruments requires more accurate atmospheric correction than does the Coastal Zone Color Scanner (CZCS), if one is to utilize fully their increased radiometric sensitivity. Unlike the CZCS, the new instruments possess bands in the near infrared (NIR) that are solely for aiding atmospheric correction. We show, using aerosol models, that certain assumptions regarding the spectral behavior of the aerosol reflectance employed in the standard CZCS correction algorithm are not valid over the spectral range encompassing both the visible and the NIR. Furthermore, we show that multiple-scattering effects on the algorithm depend significantly on the aerosol model. Following these observations, we propose an algorithm that utilizes the NIR bands for atmospheric correction to the required accuracy. Examples of the dependence of the error on the aerosol model, the turbidity of the atmosphere, and surface roughness (waves) are provided. The error in the retrieved phytoplankton-pigment concentration (the principal product of ocean-color sensors) induced by errors in the atmospheric correction are shown to be <20% in approximately 90% of the cases examined. Finally, the aerosol thickness (τ(α)) is estimated through a simple extension of the correction algorithm. Simulations suggest that the error in the recovered value of τ(α) should be ≲ 10%.

1,609 citations

Journal ArticleDOI
TL;DR: For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff, based on remote-sensing reflectance models derived from the radiative transfer equation.
Abstract: For open ocean and coastal waters, a multiband quasi-analytical algorithm is developed to retrieve absorption and backscattering coefficients, as well as absorption coefficients of phytoplankton pigments and gelbstoff. This algorithm is based on remote-sensing reflectance models derived from the radiative transfer equation, and values of total absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. In the calculation of total absorption coefficient, no spectral models for pigment and gelbstoff absorption coefficients are used. Actually those absorption coefficients are spectrally decomposed from the derived total absorption coefficient in a separate calculation. The algorithm is easy to understand and simple to implement. It can be applied to data from past and current satellite sensors, as well as to data from hyperspectral sensors. There are only limited empirical relationships involved in the algorithm, and they are for less important properties, which implies that the concept and details of the algorithm could be applied to many data for oceanic observations. The algorithm is applied to simulated data and field data, both non-case1, to test its performance, and the results are quite promising. More independent tests with field-measured data are desired to validate and improve this algorithm.

1,375 citations

Journal ArticleDOI
TL;DR: A procedure for optimizing SA ocean color models for global applications by tuned by simulated annealing as the global optimization protocol and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl.
Abstract: Semianalytical (SA) ocean color models have advantages over conventional band ratio algorithms in that multiple ocean properties can be retrieved simultaneously from a single water-leaving radiance spectrum. However, the complexity of SA models has stalled their development, and operational implementation as optimal SA parameter values are hard to determine because of limitations in development data sets and the lack of robust tuning procedures. We present a procedure for optimizing SA ocean color models for global applications. The SA model to be optimized retrieves simultaneous estimates for chlorophyll (Chl) concentration, the absorption coefficient for dissolved and detrital materials [a(cdm)(443)], and the particulate backscatter coefficient [b(bp)(443)] from measurements of the normalized water-leaving radiance spectrum. Parameters for the model are tuned by simulated annealing as the global optimization protocol. We first evaluate the robustness of the tuning method using synthetic data sets, and we then apply the tuning procedure to an in situ data set. With the tuned SA parameters, the accuracy of retrievals found with the globally optimized model (the Garver-Siegel-Maritorena model version 1; hereafter GSM01) is excellent and results are comparable with the current Sea-viewing Wide Field-of-view sensor (SeaWiFS) algorithm for Chl. The advantage of the GSM01 model is that simultaneous retrievals of a(cdm)(443) and b(bp)(443) are made that greatly extend the nature of global applications that can be explored. Current limitations and further developments of the model are discussed.

872 citations

Journal ArticleDOI
TL;DR: In this paper, the basic concepts of atmospheric correction over the oceans and details of the algorithms currently being developed for SeaWiFS, MODIS, and MISR are reviewed and an alternate correction algorithm that could be of significant value in the coastal zone is described.
Abstract: Sensors that can be used for the observation of ocean color in NASA's Earth Observing System era (SeaWiFS, MODIS, and MISR) have been designed with 2–4 times the radiometric sensitivity of the proof-of-concept ocean color instrument CZCS (coastal zone color scanner). To realize an improvement in the retrieval of biologically important ocean parameters, e.g., the concentration of the photosynthetic pigment chlorophyll a, from this increased sensitivity, significantly better atmospheric correction than was applied to CZCS is required. Atmospheric correction improvement necessitates the inclusion of the effects of multiple scattering, which are strongly dependent on the aerosol size distribution, concentration, and absorption properties. We review the basic concepts of atmospheric correction over the oceans and provide the details of the algorithms currently being developed for SeaWiFS, MODIS, and MISR. An alternate correction algorithm that could be of significant value in the coastal zone is described for MISR. Related issues such as the influence of aerosol vertical structure in the troposphere, polarization of the light field, sea surface roughness, and oceanic whitecaps on the sea surface are evaluated and plans for their inclusion in the algorithm are described. Unresolved issues, such as the presence of stratospheric aerosol, the appropriateness of the aerosol models used in the assessment of multiple scattering, and the identification of, and difficulties associated with the correction for, the presence of absorbing aerosols, e.g., urban pollution or mineral dust, are identified, and suggestions are provided for their resolution.

689 citations


"Dynamic range and sensitivity requi..." refers background in this paper

  • ...The disproportionally low SNRs in the SeaWiFS NIR bands have significant implications on atmospheric correction [29,30] and ocean color data products, as small noises in these bands would propagate to much higher noises in the blue–green bands through atmospheric correction, resulting in pixelization in Chl images [4]....

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Journal ArticleDOI
TL;DR: In this paper, a color index (CI) was proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters.
Abstract: A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

684 citations