Seasonal to Decadal-Scale Variability in Satellite Ocean Color and Sea Surface Temperature for the California Current System

NASA Technical Reports Server (NTRS)

Mitchell, B. Greg; Kahru, Mati; Marra, John (Technical Monitor)

2002-01-01

Support for this project was used to develop satellite ocean color and temperature indices (SOCTI) for the California Current System (CCS) using the historic record of CZCS West Coast Time Series (WCTS), OCTS, WiFS and AVHRR SST. The ocean color satellite data have been evaluated in relation to CalCOFI data sets for chlorophyll (CZCS) and ocean spectral reflectance and chlorophyll OCTS and SeaWiFS. New algorithms for the three missions have been implemented based on in-water algorithm data sets, or in the case of CZCS, by comparing retrieved pigments with ship-based observations. New algorithms for absorption coefficients, diffuse attenuation coefficients and primary production have also been evaluated. Satellite retrievals are being evaluated based on our large data set of pigments and optics from CalCOFI.

Suomi NPP VIIRS Ocean Color Data Product Early Mission Assessment

NASA Technical Reports Server (NTRS)

Turpie, Kevin R.; Robinson, Wayne D.; Franz, Bryan A.; Eplee, Robert E., Jr.; Meister, Gerhard; Fireman, Gwyn F.; Patt, Frederick S.; Barnes, Robert A.; McClain, Charles R.

2013-01-01

Following the launch of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polarorbiting Partnership (NPP) spacecraft, the NASA NPP VIIRS Ocean Science Team (VOST) began an evaluation of ocean color data products to determine whether they could continue the existing NASA ocean color climate data record (CDR). The VOST developed an independent evaluation product based on NASA algorithms with a reprocessing capability. Here we present a preliminary assessment of both the operational ocean color data products and the NASA evaluation data products regarding their applicability to NASA science objectives.

Retrieval of aerosol properties and water leaving radiance from multi-angle spectro-polarimetric measurement over coastal waters

NASA Astrophysics Data System (ADS)

Gao, M.; Zhai, P.; Franz, B. A.; Hu, Y.; Knobelspiesse, K. D.; Xu, F.; Ibrahim, A.

2017-12-01

Ocean color remote sensing in coastal waters remains a challenging task due to the complex optical properties of aerosols and ocean water properties. It is highly desirable to develop an advanced ocean color and aerosol retrieval algorithm for coastal waters, to advance our capabilities in monitoring water quality, improve our understanding of coastal carbon cycle dynamics, and allow for the development of more accurate circulation models. However, distinguishing the dissolved and suspended material from absorbing aerosols over coastal waters is challenging as they share similar absorption spectrum within the deep blue to UV range. In this paper we report a research algorithm on aerosol and ocean color retrieval with emphasis on coastal waters. The main features of our algorithm include: 1) combining co-located measurements from a hyperspectral ocean color instrument (OCI) and a multi-angle polarimeter (MAP); 2) using the radiative transfer model for coupled atmosphere and ocean system (CAOS), which is based on the highly accurate and efficient successive order of scattering method; and 3) incorporating a generalized bio-optical model with direct accounting of the total absorption of phytoplankton, CDOM and non-algal particles(NAP), and the total scattering of phytoplankton and NAP for improved description of ocean light scattering. The non-linear least square fitting algorithm is used to optimize the bio-optical model parameters and the aerosol optical and microphysical properties including refractive indices and size distributions for both fine and coarse modes. The retrieved aerosol information is used to calculate the atmospheric path radiance, which is then subtracted from the OCI observations to obtain the water leaving radiance contribution. Our work aims to maximize the use of available information from the co-located dataset and conduct the atmospheric correction with minimal assumptions. The algorithm will contribute to the success of current MAP instruments, such as the Research Scanning Polarimeter (RSP), and future ocean color missions, such as the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission, by enabling retrieval of ocean biogeochemical properties under optically-complex atmospheric and oceanic conditions.

Optical and Ancillary Measurements at High Latitudes in Support of the MODIS Ocean Validation Program

NASA Technical Reports Server (NTRS)

Stramski, Dariusz; Stramska, Malgorzata; Starr, David OC. (Technical Monitor)

2002-01-01

The overall goal of this project was to validate and refine ocean color algorithms at high latitudes in the north polar region of the Atlantic. The specific objectives were defined as follows: (1) to identify and quantify errors in the satellite-derived water-leaving radiances and chlorophyll concentration; (2) to develop understanding of these errors; and (3) to improve in-water ocean color algorithms for retrieving chlorophyll concentration in the investigated region.

Estimating Advective Near-surface Currents from Ocean Color Satellite Images

DTIC Science & Technology

2015-01-01

of surface current information. The present study uses the sequential ocean color products provided by the Geostationary Ocean Color Imager (GOCI) and...on the SuomiNational Polar-Orbiting Partner- ship (S-NPP) satellite. The GOCI is the world’s first geostationary orbit satellite sensor over the...used to extract the near-surface currents by the MCC algorithm. We not only demonstrate the retrieval of currents from the geostationary satellite ocean

Remote Sensing of Particulate Organic Carbon Pools in the High-Latitude Oceans

NASA Technical Reports Server (NTRS)

Stramski, Dariusz; Stramska, Malgorzata

2005-01-01

The general goal of this project was to characterize spatial distributions at basin scales and variability on monthly to interannual timescales of particulate organic carbon (POC) in the high-latitude oceans. The primary objectives were: (1) To collect in situ data in the north polar waters of the Atlantic and in the Southern Ocean, necessary for the derivation of POC ocean color algorithms for these regions. (2) To derive regional POC algorithms and refine existing regional chlorophyll (Chl) algorithms, to develop understanding of processes that control bio-optical relationships underlying ocean color algorithms for POC and Chl, and to explain bio-optical differentiation between the examined polar regions and within the regions. (3) To determine basin-scale spatial patterns and temporal variability on monthly to interannual scales in satellite-derived estimates of POC and Chl pools in the investigated regions for the period of time covered by SeaWiFS and MODIS missions.

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for Southern Beaufort Sea (Canadian Arctic) waters: application to deriving concentrations of dissolved organic carbon from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2012-10-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for Southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows to separate colored detrital matter (CDM) into CDOM and non-algal particles (NAP) by determining NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, that were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and turbid waters, respectively. In situ measurements showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the Southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

Flagging optically shallow pixels for improved analysis of ocean color data

NASA Astrophysics Data System (ADS)

McKinna, L. I. W.; Werdell, J.; Knowles, D., Jr.

2016-02-01

Ocean color remote-sensing is routinely used to derive marine geophysical parameters from sensor-observed water-leaving radiances. However, in clear geometrically shallow regions, traditional ocean color algorithms can be confounded by light reflected from the seafloor. Such regions are typically referred to as "optically shallow". When performing spatiotemporal analyses of ocean color datasets, optically shallow features such as coral reefs can lead to unexpected regional biases. Benthic contamination of the water-leaving radiance is dependent on bathymetry, water clarity and seafloor albedo. Thus, a prototype ocean color processing flag called OPTSHAL has been developed that takes all three variables into account. In the method described here, the optical depth of the water column at 547 nm, ζ(547), is predicted from known bathymetry and estimated inherent optical properties. If ζ(547) is less then the pre-defined threshold, a pixel is flagged as optically shallow. Radiative transfer modeling was used to identify the appropriate threshold value of ζ(547) for a generic benthic sand albedo. OPTSHAL has been evaluated within the NASA Ocean Biology Processing Group's L2GEN code. Using MODIS Aqua imagery, OPTSHAL was tested in two regions: (i) the Pedro Bank south-west of Jamaica, and (ii) the Great Barrier Reef, Australia. It is anticipated that OPTSHAL will benefit end-users when quality controlling derived ocean color products. Further, OPTSHAL may prove useful as a mechanism for switching between optically deep and shallow algorithms during ocean color processing.

Optimization of Ocean Color Algorithms: Application to Satellite Data Merging

NASA Technical Reports Server (NTRS)

Ritorena, Stephane; Siegel, David A.; Morel, Andre

2004-01-01

The objective of the program is to develop and validate a procedure for ocean color data merging, which is one of the major goals of the SIMBIOS project. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances L((sub wN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) It works with single or multiple data sources regardless of their specific bands; 2) It exploits band redundancies and band differences; 3) It accounts for uncertainties in the L((sub wN)(lambda)) data; 4) It provides uncertainty estimates for the retrieved variables.

Implementation of an Analytical Raman Scattering Correction for Satellite Ocean-Color Processing

NASA Technical Reports Server (NTRS)

McKinna, Lachlan I. W.; Werdell, P. Jeremy; Proctor, Christopher W.

2016-01-01

Raman scattering of photons by seawater molecules is an inelastic scattering process. This effect can contribute significantly to the water-leaving radiance signal observed by space-borne ocean-color spectroradiometers. If not accounted for during ocean-color processing, Raman scattering can cause biases in derived inherent optical properties (IOPs). Here we describe a Raman scattering correction (RSC) algorithm that has been integrated within NASA's standard ocean-color processing software. We tested the RSC with NASA's Generalized Inherent Optical Properties algorithm (GIOP). A comparison between derived IOPs and in situ data revealed that the magnitude of the derived backscattering coefficient and the phytoplankton absorption coefficient were reduced when the RSC was applied, whilst the absorption coefficient of colored dissolved and detrital matter remained unchanged. Importantly, our results show that the RSC did not degrade the retrieval skill of the GIOP. In addition, a timeseries study of oligotrophic waters near Bermuda showed that the RSC did not introduce unwanted temporal trends or artifacts into derived IOPs.

NOAA-NASA Coastal Zone Color Scanner reanalysis effort.

PubMed

Gregg, Watson W; Conkright, Margarita E; O'Reilly, John E; Patt, Frederick S; Wang, Menghua H; Yoder, James A; Casey, Nancy W

2002-03-20

Satellite observations of global ocean chlorophyll span more than two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration (NOAA-NASA) CZCS reanalysis (NCR) effort. NCR consisted of (1) algorithm improvement (AI), where CZCS processing algorithms were improved with modernized atmospheric correction and bio-optical algorithms and (2) blending where in situ data were incorporated into the CZCS AI to minimize residual errors. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.

Ocean Color Inferred from Radiometers on Low-Flying Aircraft.

PubMed

Churnside, James H; Wilson, James J

2008-02-08

The color of sunlight reflected from the ocean to orbiting visible radiometers hasprovided a great deal of information about the global ocean, after suitable corrections aremade for atmospheric effects. Similar ocean-color measurements can be made from a lowflyingaircraft to get higher spatial resolution and to obtain measurements under clouds.A different set of corrections is required in this case, and we describe algorithms to correctfor clouds and sea-surface effects. An example is presented and errors in the correctionsdiscussed.

Estimating absorption coefficients of colored dissolved organic matter (CDOM) using a semi-analytical algorithm for southern Beaufort Sea waters: application to deriving concentrations of dissolved organic carbon from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Hooker, S. B.; Bricaud, A.; Gentili, B.; Babin, M.

2013-02-01

A series of papers have suggested that freshwater discharge, including a large amount of dissolved organic matter (DOM), has increased since the middle of the 20th century. In this study, a semi-analytical algorithm for estimating light absorption coefficients of the colored fraction of DOM (CDOM) was developed for southern Beaufort Sea waters using remote sensing reflectance at six wavelengths in the visible spectral domain corresponding to MODIS ocean color sensor. This algorithm allows the separation of colored detrital matter (CDM) into CDOM and non-algal particles (NAP) through the determination of NAP absorption using an empirical relationship between NAP absorption and particle backscattering coefficients. Evaluation using independent datasets, which were not used for developing the algorithm, showed that CDOM absorption can be estimated accurately to within an uncertainty of 35% and 50% for oceanic and coastal waters, respectively. A previous paper (Matsuoka et al., 2012) showed that dissolved organic carbon (DOC) concentrations were tightly correlated with CDOM absorption in our study area (r2 = 0.97). By combining the CDOM absorption algorithm together with the DOC versus CDOM relationship, it is now possible to estimate DOC concentrations in the near-surface layer of the southern Beaufort Sea using satellite ocean color data. DOC concentrations in the surface waters were estimated using MODIS ocean color data, and the estimates showed reasonable values compared to in situ measurements. We propose a routine and near real-time method for deriving DOC concentrations from space, which may open the way to an estimate of DOC budgets for Arctic coastal waters.

Optimization of Ocean Color Algorithms: Application to Satellite Data Merging

NASA Technical Reports Server (NTRS)

Maritorena, Stephane; Siegel, David A.; Morel, Andre

2003-01-01

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project. The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage. The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global Ocean the merging of Ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program. As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized water-leaving radiances (L(sub WN)(lambda)) from single or multiple sensors and uses them in the inversion of a semi-analytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the (L(sub WN)(lambda)) data and, 4) it provides uncertainty estimates for the retrieved variables.

Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

NASA Technical Reports Server (NTRS)

Campbell, Janet W.

1998-01-01

The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

The use of a MODIS band-ratio algorithm versus a new hybrid approach for estimating colored dissolved organic matter (CDOM)

EPA Science Inventory

Satellite remote sensing offers synoptic and frequent monitoring of optical water quality parameters, such as chlorophyll-a, turbidity, and colored dissolved organic matter (CDOM). While traditional satellite algorithms were developed for the open ocean, these algorithms often do...

VIIRS validation and algorithm development efforts in coastal and inland Waters

NASA Astrophysics Data System (ADS)

Stengel, E.; Ondrusek, M.

2016-02-01

Accurate satellite ocean color measurements in coastal and inland waters are more challenging than open-ocean measurements. Complex water and atmospheric conditions can limit the utilization of remote sensing data in coastal waters where it is most needed. The Coastal Optical Characterization Experiment (COCE) is an ongoing project at NOAA/NESDIS/STAR Satellite Oceanography and Climatology Division. The primary goals of COCE are satellite ocean color validation and application development. Currently, this effort concentrates on the initialization and validation of the Joint Polar Satellite System (JPSS) VIIRS sensor using a Satlantic HyperPro II radiometer as a validation tool. A report on VIIRS performance in coastal waters will be given by presenting comparisons between in situ ground truth measurements and VIIRS retrievals made in the Chesapeake Bay, and inland waters of the Gulf of Mexico and Puerto Rico. The COCE application development effort focuses on developing new ocean color satellite remote sensing tools for monitoring relevant coastal ocean parameters. A new VIIRS total suspended matter algorithm will be presented for the Chesapeake Bay. These activities improve the utility of ocean color satellite data in monitoring and analyzing coastal and oceanic processes. Progress on these activities will be reported.

The Airborne Ocean Color Imager - System description and image processing

NASA Technical Reports Server (NTRS)

Wrigley, Robert C.; Slye, Robert E.; Klooster, Steven A.; Freedman, Richard S.; Carle, Mark; Mcgregor, Lloyd F.

1992-01-01

The Airborne Ocean Color Imager was developed as an aircraft instrument to simulate the spectral and radiometric characteristics of the next generation of satellite ocean color instrumentation. Data processing programs have been developed as extensions of the Coastal Zone Color Scanner algorithms for atmospheric correction and bio-optical output products. The latter include several bio-optical algorithms for estimating phytoplankton pigment concentration, as well as one for the diffuse attenuation coefficient of the water. Additional programs have been developed to geolocate these products and remap them into a georeferenced data base, using data from the aircraft's inertial navigation system. Examples illustrate the sequential data products generated by the processing system, using data from flightlines near the mouth of the Mississippi River: from raw data to atmospherically corrected data, to bio-optical data, to geolocated data, and, finally, to georeferenced data.

Assessment of NPP VIIRS Ocean Color Data Products: Hope and Risk

NASA Technical Reports Server (NTRS)

Turpie, Kevin R.; Meister, Gerhard; Eplee, Gene; Barnes, Robert A.; Franz, Bryan; Patt, Frederick S.; Robinson, Wayne d.; McClain, Charles R.

2010-01-01

For several years, the NASA/Goddard Space Flight Center (GSFC) NPP VIIRS Ocean Science Team (VOST) provided substantial scientific input to the NPP project regarding the use of Visible Infrared Imaging Radiometer Suite (VIIRS) to create science quality ocean color data products. This work has culminated into an assessment of the NPP project and the VIIRS instrument's capability to produce science quality Ocean Color data products. The VOST concluded that many characteristics were similar to earlier instruments, including SeaWiFS or MODIS Aqua. Though instrument performance and calibration risks do exist, it was concluded that programmatic and algorithm issues dominate concerns. Keywords: NPP, VIIRS, Ocean Color, satellite remote sensing, climate data record.

Surface roughness considerations for atmospheric correction of ocean color sensors. I - The Rayleigh-scattering component. II - Error in the retrieved water-leaving radiance

NASA Technical Reports Server (NTRS)

Gordon, Howard R.; Wang, Menghua

1992-01-01

The first step in the Coastal Zone Color Scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering (RS) contribution, L sub r, to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm, L sub r is computed by assuming that the ocean surface is flat. Calculations of the radiance leaving an RS atmosphere overlying a rough Fresnel-reflecting ocean are presented to evaluate the radiance error caused by the flat-ocean assumption. Simulations are carried out to evaluate the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct sun glitter, it is concluded that the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness. This suggests that, in refining algorithms for future sensors, more effort should be focused on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Ocean Color Inferred from Radiometers on Low-Flying Aircraft

PubMed Central

Churnside, James H.; Wilson, James J.

2008-01-01

The color of sunlight reflected from the ocean to orbiting visible radiometers has provided a great deal of information about the global ocean, after suitable corrections are made for atmospheric effects. Similar ocean-color measurements can be made from a low-flying aircraft to get higher spatial resolution and to obtain measurements under clouds. A different set of corrections is required in this case, and we describe algorithms to correct for clouds and sea-surface effects. An example is presented and errors in the corrections discussed. PMID:27879739

Effects of Whitecaps on Satellite-Derived Ocean Color

NASA Technical Reports Server (NTRS)

Frouin, Robert

2000-01-01

During the 3.25 years of the project, various aspects of satellite ocean-color remote sensing were investigated, including effect of whitecaps on atmospheric correction, validity of aerosol models, and evaluation of ocean-color products. Algorithms to estimate pigment concentration and photo-synthetically active radiation (PAR) were developed, and studies of geophysical phenomena, such as the 1998 Asian Dust event, were performed. The influence of solar radiation absorption by phytoplankton on mixed layer dynamics, ocean circulation, and climate was also investigated. The project's results and findings are described.

Stochastic inversion of ocean color data using the cross-entropy method.

PubMed

Salama, Mhd Suhyb; Shen, Fang

2010-01-18

Improving the inversion of ocean color data is an ever continuing effort to increase the accuracy of derived inherent optical properties. In this paper we present a stochastic inversion algorithm to derive inherent optical properties from ocean color, ship and space borne data. The inversion algorithm is based on the cross-entropy method where sets of inherent optical properties are generated and converged to the optimal set using iterative process. The algorithm is validated against four data sets: simulated, noisy simulated in-situ measured and satellite match-up data sets. Statistical analysis of validation results is based on model-II regression using five goodness-of-fit indicators; only R2 and root mean square of error (RMSE) are mentioned hereafter. Accurate values of total absorption coefficient are derived with R2 > 0.91 and RMSE, of log transformed data, less than 0.55. Reliable values of the total backscattering coefficient are also obtained with R2 > 0.7 (after removing outliers) and RMSE < 0.37. The developed algorithm has the ability to derive reliable results from noisy data with R2 above 0.96 for the total absorption and above 0.84 for the backscattering coefficients. The algorithm is self contained and easy to implement and modify to derive the variability of chlorophyll-a absorption that may correspond to different phytoplankton species. It gives consistently accurate results and is therefore worth considering for ocean color global products.

Performance metrics for the assessment of satellite data products: an ocean color case study

PubMed Central

Seegers, Bridget N.; Stumpf, Richard P.; Schaeffer, Blake A.; Loftin, Keith A.; Werdell, P. Jeremy

2018-01-01

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multi-metric and user-dependent approach that can be applied within science, modeling, and resource management communities. PMID:29609296

A synthesis of light absorption properties of the Arctic Ocean: application to semianalytical estimates of dissolved organic carbon concentrations from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Bélanger, S.; Bricaud, A.

2014-06-01

In addition to scattering coefficients, the light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the data sets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database of the Arctic Ocean by pooling the majority of published data sets and merging new data sets. Our results show that the total nonwater absorption coefficients measured in the eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aϕ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semianalytical CDOM absorption algorithm is based on chl a-specific aϕ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Based on statistics, derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semianalytical algorithm for estimating DOC concentrations for river-influenced coastal waters of the Arctic Ocean is presented and applied to satellite ocean color data.

Optimization Of Ocean Color Algorithms: Application To Satellite And In Situ Data Merging. Chapter 9

NASA Technical Reports Server (NTRS)

Maritorena, Stephane; Siegel, David A.; Morel, Andre

2003-01-01

The objective of our program is to develop and validate a procedure for ocean color data merging which is one of the major goals of the SIMBIOS project (McClain et al., 1995). The need for a merging capability is dictated by the fact that since the launch of MODIS on the Terra platform and over the next decade, several global ocean color missions from various space agencies are or will be operational simultaneously. The apparent redundancy in simultaneous ocean color missions can actually be exploited to various benefits. The most obvious benefit is improved coverage (Gregg et al., 1998; Gregg & Woodward, 1998). The patchy and uneven daily coverage from any single sensor can be improved by using a combination of sensors. Beside improved coverage of the global ocean the merging of ocean color data should also result in new, improved, more diverse and better data products with lower uncertainties. Ultimately, ocean color data merging should result in the development of a unified, scientific quality, ocean color time series, from SeaWiFS to NPOESS and beyond. Various approaches can be used for ocean color data merging and several have been tested within the frame of the SIMBIOS program (see e.g. Kwiatkowska & Fargion, 2003, Franz et al., 2003). As part of the SIMBIOS Program, we have developed a merging method for ocean color data. Conversely to other methods our approach does not combine end-products like the subsurface chlorophyll concentration (chl) from different sensors to generate a unified product. Instead, our procedure uses the normalized waterleaving radiances (LwN( )) from single or multiple sensors and uses them in the inversion of a semianalytical ocean color model that allows the retrieval of several ocean color variables simultaneously. Beside ensuring simultaneity and consistency of the retrievals (all products are derived from a single algorithm), this model-based approach has various benefits over techniques that blend end-products (e.g. chlorophyll): 1) it works with single or multiple data sources regardless of their specific bands, 2) it exploits band redundancies and band differences, 3) it accounts for uncertainties in the LwN( ) data and, 4) it provides uncertainty estimates for the retrieved variables.

Assessment of satellite retrieval algorithms for chlorophyll-a concentration under high solar zenith angle

NASA Astrophysics Data System (ADS)

Li, Hao; He, Xianqiang; Bai, Yan; Chen, Xiaoyan; Gong, Fang; Zhu, Qiankun; Hu, Zifeng

2016-10-01

Numerous empirical algorithms have been operationally used to retrieve the global ocean chlorophyll-a concentration (Chla) from ocean color satellite data, e.g., the OC4V4 algorithm for SeaWiFS and OC3M for MODIS. However, the algorithms have been established and validated based on the in situ data mainly measured under low to moderate solar zenith angle (<70°). Currently, with the development of the geostationary satellite ocean color remote sensing which observes from early morning to later afternoon, it is necessary to know whether the empirical Chla algorithms could be applied to high solar zenith angle. In this study, the performances of seven widely-used Chla algorithms under high solar zenith angles, i.e., OC2, OC3M, OC3V, OC4V4, CLARK, OCI, and YOC algorithms, were evaluated using the NOMAD global in situ ocean color dataset. The results showed that the performances of all the seven algorithms decreased significantly under high solar zenith angles as compared to those under low-moderate solar zenith angles. For instance, for the OC4V4 algorithm, the relative percent difference (RPD) and root-mean-square error (RMSE) were 13.78% and 1.66 μg/l for the whole dataset, and 3.95% and 1.49 μg/l for the solar zenith angles ranged from 30° to 40°, respectively. However, the RPD and RMSE increased to 30.45% and 6.10μg/l for solar zenith angle larger than 70°.

Primary analysis of the ocean color remote sensing data of the HY-1B/COCTS

NASA Astrophysics Data System (ADS)

He, Xianqiang; Bai, Yan; Pan, Delu; Zhu, Qiankun; Gong, Fang

2009-01-01

China had successfully launched her second ocean color satellite HY-1B on 11 Apr., 2007, which was the successor of the HY-1A satellite launched on 15 May, 2002. There were two sensors onboard HY-1B, named the Chinese Ocean Color and Temperature Scanner (COCTS) and the Coastal Zone Imager (CZI) respectively, and COCTS was the main sensor. COCTS had not only eight visible and near-infrared wave bands similar to the SeaWiFS, but also two more thermal infrared wave bands to measure the sea surface temperature. Therefore, COCTS had broad application potentiality, such as fishery resource protection and development, coastal monitoring and management and marine pollution monitoring. In this paper, the main characteristics of COCTS were described firstly. Then, using the crosscalibration method, the vicarious calibration of COCTS was carried out by the synchronous remote sensing data of SeaWiFS, and the results showed that COCTS had well linear responses for the visible light bands with the correlation coefficients more than 0.98, however, the performances of the near infrared wavelength bands were not good as visible light bands. Using the vicarious calibration result, the operational atmospheric correction (AC) algorithm of COCTS was developed based on the exact Rayleigh scattering look-up table (LUT), aerosol scattering LUT and atmosphere diffuse transmission LUT generated by the coupled ocean-atmospheric vector radiative transfer numerical model named PCOART. The AC algorithm had been validated by the simulated radiance data at the top-of-atmosphere, and the results showed the errors of the water-leaving reflectance retrieved by the AC algorithm were less than 0.0005, which met the requirement of the exactly atmospheric correction of ocean color remote sensing. Finally, the AC algorithm was applied to the HY-1B/COCTS remote sensing data, and the corresponding ocean color remote sensing products have been generated.

A Semianalytical Ocean Color Inversion Algorithm with Explicit Water Column Depth and Substrate Reflectance Parameterization

NASA Technical Reports Server (NTRS)

Mckinna, Lachlan I. W.; Werdell, P. Jeremy; Fearns, Peter R. C.; Weeks, Scarla J.; Reichstetter, Martina; Franz, Bryan A.; Shea, Donald M.; Feldman, Gene C.

2015-01-01

A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002-2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, at(443), the particulate backscattering coefficient at 443 nm, bbp(443), and the diffuse attenuation coefficient at 488 nm, Kd(488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of at(443), bbp(443), and Kd(443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

Stray-Light Correction of the Marine Optical Buoy

NASA Technical Reports Server (NTRS)

Brown, Steven W.; Johnson, B. Carol; Flora, Stephanie J.; Feinholz, Michael E.; Yarbrough, Mark A.; Barnes, Robert A.; Kim, Yong Sung; Lykke, Keith R.; Clark, Dennis K.

2003-01-01

In ocean-color remote sensing, approximately 90% of the flux at the sensor originates from atmospheric scattering, with the water-leaving radiance contributing the remaining 10% of the total flux. Consequently, errors in the measured top-of-the atmosphere radiance are magnified a factor of 10 in the determination of water-leaving radiance. Proper characterization of the atmosphere is thus a critical part of the analysis of ocean-color remote sensing data. It has always been necessary to calibrate the ocean-color satellite sensor vicariously, using in situ, ground-based results, independent of the status of the pre-flight radiometric calibration or the utility of on-board calibration strategies. Because the atmosphere contributes significantly to the measured flux at the instrument sensor, both the instrument and the atmospheric correction algorithm are simultaneously calibrated vicariously. The Marine Optical Buoy (MOBY), deployed in support of the Earth Observing System (EOS) since 1996, serves as the primary calibration station for a variety of ocean-color satellite instruments, including the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Japanese Ocean Color Temperature Scanner (OCTS) , and the French Polarization and Directionality of the Earth's Reflectances (POLDER). MOBY is located off the coast of Lanai, Hawaii. The site was selected to simplify the application of the atmospheric correction algorithms. Vicarious calibration using MOBY data allows for a thorough comparison and merger of ocean-color data from these multiple sensors.

Quality and Consistency of the NASA Ocean Color Data Record

NASA Technical Reports Server (NTRS)

Franz, Bryan A.

2012-01-01

The NASA Ocean Biology Processing Group (OBPG) recently reprocessed the multimission ocean color time-series from SeaWiFS, MODIS-Aqua, and MODIS-Terra using common algorithms and improved instrument calibration knowledge. Here we present an analysis of the quality and consistency of the resulting ocean color retrievals, including spectral water-leaving reflectance, chlorophyll a concentration, and diffuse attenuation. Statistical analysis of satellite retrievals relative to in situ measurements will be presented for each sensor, as well as an assessment of consistency in the global time-series for the overlapping periods of the missions. Results will show that the satellite retrievals are in good agreement with in situ measurements, and that the sensor ocean color data records are highly consistent over the common mission lifespan for the global deep oceans, but with degraded agreement in higher productivity, higher complexity coastal regions.

A synthesis of light absorption properties of the Pan-Arctic Ocean: application to semi-analytical estimates of dissolved organic carbon concentrations from space

NASA Astrophysics Data System (ADS)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Bélanger, S.; Bricaud, A.

2013-11-01

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean (e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012), the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off North America. In contrast, the relationship between the phytoplankton absorption (aφ(λ)) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific aφ(λ) values (Matsuoka et al., 2013), this result indirectly suggests that CDOM absorption can be appropriately derived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC vs. CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

A Synthesis of Light Absorption Properties of the Arctic Ocean: Application to Semi-analytical Estimates of Dissolved Organic Carbon Concentrations from Space

NASA Technical Reports Server (NTRS)

Matsuoka, A.; Babin, M.; Doxaran, D.; Hooker, S. B.; Mitchell, B. G.; Belanger, S.; Bricaud, A.

2014-01-01

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean [e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012], the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher 74 than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained 75 by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian 76 side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off 77 North America. In contrast, the relationship between the phytoplankton absorption (a()) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific a() values [Matsuoka et al., 2013], this result indirectly suggests that CDOM absorption can be appropriately erived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 6; Special Topics in Ocean Optics Protocols and Appendices; Revised

NASA Technical Reports Server (NTRS)

Mueller, J. L. (Editor); Fargion, Giulietta S. (Editor); McClain, Charles R. (Editor)

2003-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. The document is organized into 6 separate volumes as Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4. Volume I: Introduction, Background and Conventions; Volume II: Instrument Specifications, Characterization and Calibration; Volume III: Radiometric Measurements and Data Analysis Methods; Volume IV: Inherent Optical Properties: Instruments, Characterization, Field Measurements and Data Analysis Protocols; Volume V: Biogeochemical and Bio-Optical Measurements and Data Analysis Methods; Volume VI: Special Topics in Ocean Optics Protocols and Appendices. The earlier version of Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 3 (Mueller and Fargion 2002, Volumes 1 and 2) is entirely superseded by the six volumes of Revision 4 listed above.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Volume 4; Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols; Revised

NASA Technical Reports Server (NTRS)

Mueller, J. L. (Editor); Fargion, Giuletta S. (Editor); McClain, Charles R. (Editor); Pegau, Scott; Zaneveld, J. Ronald V.; Mitchell, B. Gregg; Kahru, Mati; Wieland, John; Stramska, Malgorzat

2003-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. The document is organized into 6 separate volumes as Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4. Volume I: Introduction, Background and Conventions; Volume II: Instrument Specifications, Characterization and Calibration; Volume III: Radiometric Measurements and Data Analysis Methods; Volume IV: Inherent Optical Properties: Instruments, Characterization, Field Measurements and Data Analysis Protocols; Volume V: Biogeochemical and Bio-Optical Measurements and Data Analysis Methods; Volume VI: Special Topics in Ocean Optics Protocols and Appendices. The earlier version of Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 3 (Mueller and Fargion 2002, Volumes 1 and 2) is entirely superseded by the six volumes of Revision 4 listed above.

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4, Volume IV: Inherent Optical Properties: Instruments, Characterizations, Field Measurements and Data Analysis Protocols

NASA Technical Reports Server (NTRS)

Mueller, J. L.; Fargion, G. S.; McClain, C. R. (Editor); Pegau, S.; Zanefeld, J. R. V.; Mitchell, B. G.; Kahru, M.; Wieland, J.; Stramska, M.

2003-01-01

This document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparision and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. The document is organized into 6 separate volumes as Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 4. Volume I: Introduction, Background, and Conventions; Volume II: Instrument Specifications, Characterization and Calibration; Volume III: Radiometric Measurements and Data Analysis Methods; Volume IV: Inherent Optical Properties: Instruments, Characterization, Field Measurements and Data Analysis Protocols; Volume V: Biogeochemical and Bio-Optical Measurements and Data Analysis Methods; Volume VI: Special Topics in Ocean Optics Protocols and Appendices. The earlier version of Ocean Optics Protocols for Satellite Ocean Color Sensor Validation, Revision 3 is entirely superseded by the six volumes of Revision 4 listed above.

Bio-Optical Measurement and Modeling of the California Current and Southern Oceans

NASA Technical Reports Server (NTRS)

Mitchell, B. Gregg; Mitchell, B. Greg

2003-01-01

The SIMBIOS project's principal goals are to validate standard or experimental ocean color products through detailed bio-optical and biogeochemical measurements, and to combine Ocean optical observations with modeling to contribute to satellite vicarious radiometric calibration and algorithm development.

Bidirectional reflectance correction model for coastal water and its application to minimization of uncertainties in satellite and in-situ water leaving radiances at Long Island Sound Coastal Observatory site

NASA Astrophysics Data System (ADS)

Hlaing, Soe Min

Ocean Color data validation is the absolute requirement to provide the steady and reliable Ocean Color data stream. In the validation of Ocean Color data, water-leaving radiances, retrieved from in situ or satellite measurements, need to be compared in very accurate manner. Both in-situ and satellite data to be used in the comparisons are required to be the representative of the typical water and environmental condition at the site without being affected by the unexpected natural and environmental perturbation. As the result, assessments of the uncertainties in the water leaving radiance data must be carried out in the measurement and the every step of data processing procedure. With the hyper- and multi-spectral water leaving radiance data retrieved for the different viewing geometries of the instruments at the Long Island Sound Coastal Observatory (LISCO), uncertainties in the water leaving radiance data and processing procedures have been assessed and quantified. Recommendations and algorithm improvements have been also made to reduce the uncertainties in the processing and validation of Ocean Color data. Particularly, remote sensing reflectance model to correct the bidirectional angular dependencies in both in-situ and satellite data have been proposed. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multi- and hyper-spectral radiometers which have different viewing geometries installed at LISCO. Match-ups and inter-comparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with spectral average improvement of 2.4%. LISCO's time series data has also been used to evaluate improvements in the match-up comparisons of MODIS satellite data when the proposed Bidirectional Reflectance Distribution Function (BRDF) correction is used in lieu of the current algorithm. It has been shown that the discrepancies between coincident in-situ sea-based and satellite data were decreased by 3.15% with the use of the proposed algorithm. Possibility of the application of the developed BRDF algorithm for the open ocean conditions is also considered.

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance

PubMed Central

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2017-01-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), Scdm (units: nm−1), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving Scdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360–500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of Scdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors. PMID:29201583

Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance.

PubMed

Wei, Jianwei; Lee, Zhongping; Ondrusek, Michael; Mannino, Antonio; Tzortziou, Maria; Armstrong, Roy

2016-03-01

The spectral slope of the absorption coefficient of colored dissolved and detrital material (CDM), S cdm (units: nm -1 ), is an important optical parameter for characterizing the absorption spectral shape of CDM. Although highly variable in natural waters, in most remote sensing algorithms, this slope is either kept as a constant or empirically modeled with multiband ocean color in the visible domain. In this study, we explore the potential of semianalytically retrieving S cdm with added ocean color information in the ultraviolet (UV) range between 360 and 400 nm. Unique features of hyperspectral remote sensing reflectance in the UV-visible wavelengths (360-500 nm) have been observed in various waters across a range of coastal and open ocean environments. Our data and analyses indicate that ocean color in the UV domain is particularly sensitive to the variation of the CDM spectral slope. Here, we used a synthesized data set to show that adding UV wavelengths to the ocean color measurements will improve the retrieval of S cdm from remote sensing reflectance considerably, while the spectral band settings of past and current satellite ocean color sensors cannot fully account for the spectral variation of remote sensing reflectance. Results of this effort support the concept to include UV wavelengths in the next generation of satellite ocean color sensors.

Evaluation of a reflectance model used in the SeaWiFS ocean color algorithm: implications for chlorophyll concentration retrievals

NASA Astrophysics Data System (ADS)

Yan, Banghua; Stamnes, Knut; Toratani, Mitsuhiro; Li, Wei; Stamnes, Jakob J.

2002-10-01

For the atmospheric correction of ocean-color imagery obtained over Case I waters with the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) instrument the method currently used to relax the black-pixel assumption in the near infrared (NIR) relies on (1) an approximate model for the nadir NIR remote-sensing reflectance and (2) an assumption that the water-leaving radiance is isotropic over the upward hemisphere. Radiance simulations based on a comprehensive radiative-transfer model for the coupled atmosphere-ocean system and measurements of the nadir remote-sensing reflectance at 670 nm compiled in the SeaWiFS Bio-optical Algorithm Mini-Workshop (SeaBAM) database are used to assess the validity of this method. The results show that (1) it is important to improve the flexibility of the reflectance model to provide more realistic predictions of the nadir NIR water-leaving reflectance for different ocean regions and (2) the isotropic assumption should be avoided in the retrieval of ocean color, if the chlorophyll concentration is larger than approximately 6, 10, and 40 mg m-3 when the aerosol optical depth is approximately 0.05, 0.1, and 0.3, respectively. Finally, we extend our scope to Case II ocean waters to gain insight and enhance our understanding of the NIR aspects of ocean color. The results show that the isotropic assumption is invalid in a wider range than in Case I waters owing to the enhanced water-leaving reflectance resulting from oceanic sediments in the NIR wavelengths.

Ocean Color Optical Property Data Derived from OCTS and POLDER: A Comparison Study

NASA Technical Reports Server (NTRS)

Wang, Menghua; Isaacman, Alice; Franz, Bryan A.; McClain, Charles R.; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

We describe our efforts in studying and comparing the ocean color data derived from the Japanese Ocean Color and Temperature Scanner (OCTS) and the French Polarization and Directionality of the Earth's Reflectances (POLDER). OCTS and POLDER were both on board Japan's Sun-synchronous Advanced Earth Observing Satellite (ADEOS-1) from August 1996 to June 1997, collecting about 10 months of global ocean color data. This provides a unique opportunity for developing methods and strategies for the merging of ocean color data from multiple ocean color sensors. In this paper, we describe our approach in developing consistent data processing algorithms for both OCTS and POLDER and using a common in situ data set to vicariously calibrate the two sensors. Therefore, the OCTS and POLDER-measured radiances are effectively bridged through common in situ measurements. With this approach in processing data from two different sensors, the only differences in the derived products from OCTS and POLDER are the differences inherited from the instrument characteristics. Results show that there are no obvious bias differences between the OCTS and POLDER-derived ocean color products, whereas the differences due to noise, which stem from variations in sensor characteristics, are difficult to correct. It is possible, however, to reduce noise differences with some data averaging schemes. The ocean color data from OCTS and POLDER can therefore be compared and merged in the sense that there is no significant bias between two.

Satellite Ocean Color Validation Using Merchant Ships. Chapter 10

NASA Technical Reports Server (NTRS)

Frouin, Robert; Cutchin, David L.; Deschamps, Pierre-Yves

2001-01-01

A collaborative measurement program for evaluating satellite-derived ocean color has been developed based on ships of opportunity (merchant, oceanographic) and specific instrumentation, the SIMBAD radiometer. The purpose of the measurement program is to complement, in a cost-effective way, dedicated evaluation experiments at sea, which are expensive, cannot be carried out over the full range of expected oceanic and atmospheric conditions, and generally provide a few match-ups. Ships participate in the program on a volunteer basis or at a very small cost, and measurement procedures do not interfere with other ship activities. The SIMBAD radiometer is a portable, easy-to-operate instrument that measures the basic ocean color variables, namely aerosol optical thickness and water-leaving radiance, in typical spectral bands of ocean-color sensors, i.e., 443, 490, 560, 670, and 870 nm. Measuring these variables at the time of satellite overpass is usually sufficient to verify satellite-derived ocean color and to evaluate atmospheric correction algorithms. Any ordinary crew can learn quickly how to make measurements. Importantly, the ship is not required to stop, making it possible to collect data along regular routes traveled by merchant ships in the world's oceans.

Aerosol polarization effects on atmospheric correction and aerosol retrievals in ocean color remote sensing.

PubMed

Wang, Menghua

2006-12-10

The current ocean color data processing system for the Sea-viewing Wide Field-of-View Sensor (SeaWiFS) and the moderate resolution imaging spectroradiometer (MODIS) uses the Rayleigh lookup tables that were generated using the vector radiative transfer theory with inclusion of the polarization effects. The polarization effects, however, are not accounted for in the aerosol lookup tables for the ocean color data processing. I describe a study of the aerosol polarization effects on the atmospheric correction and aerosol retrieval algorithms in the ocean color remote sensing. Using an efficient method for the multiple vector radiative transfer computations, aerosol lookup tables that include polarization effects are generated. Simulations have been carried out to evaluate the aerosol polarization effects on the derived ocean color and aerosol products for all possible solar-sensor geometries and the various aerosol optical properties. Furthermore, the new aerosol lookup tables have been implemented in the SeaWiFS data processing system and extensively tested and evaluated with SeaWiFS regional and global measurements. Results show that in open oceans (maritime environment), the aerosol polarization effects on the ocean color and aerosol products are usually negligible, while there are some noticeable effects on the derived products in the coastal regions with nonmaritime aerosols.

Classification of case-II waters using hyperspectral (HICO) data over North Indian Ocean

NASA Astrophysics Data System (ADS)

Srinivasa Rao, N.; Ramarao, E. P.; Srinivas, K.; Deka, P. C.

2016-05-01

State of the art Ocean color algorithms are proven for retrieving the ocean constituents (chlorophyll-a, CDOM and Suspended Sediments) in case-I waters. However, these algorithms could not perform well at case-II waters because of the optical complexity. Hyperspectral data is found to be promising to classify the case-II waters. The aim of this study is to propose the spectral bands for future Ocean color sensors to classify the case-II waters. Study has been performed with Rrs's of HICO at estuaries of the river Indus and GBM of North Indian Ocean. Appropriate field samples are not available to validate and propose empirical models to retrieve concentrations. The sensor HICO is not currently operational to plan validation exercise. Aqua MODIS data at case-I and Case-II waters are used as complementary to in- situ. Analysis of Spectral reflectance curves suggests the band ratios of Rrs 484 nm and Rrs 581 nm, Rrs 490 nm and Rrs 426 nm to classify the Chlorophyll -a and CDOM respectively. Rrs 610 nm gives the best scope for suspended sediment retrieval. The work suggests the need for ocean color sensors with central wavelength's of 426, 484, 490, 581 and 610 nm to estimate the concentrations of Chl-a, Suspended Sediments and CDOM in case-II waters.

Atmospheric correction of AVIRIS data in ocean waters

NASA Technical Reports Server (NTRS)

Terrie, Gregory; Arnone, Robert

1992-01-01

Hyperspectral data offers unique capabilities for characterizing the ocean environment. The spectral characterization of the composition of ocean waters can be organized into biological and terrigenous components. Biological photosynthetic pigments in ocean waters have unique spectral ocean color signatures which can be associated with different biological species. Additionally, suspended sediment has different scattering coefficients which result in ocean color signatures. Measuring the spatial distributions of these components in the maritime environments provides important tools for understanding and monitoring the ocean environment. These tools have significant applications in pollution, carbon cycle, current and water mass detection, location of fronts and eddies, sewage discharge and fate etc. Ocean color was used from satellite for describing the spatial variability of chlorophyll, water clarity (K(sub 490)), suspended sediment concentration, currents etc. Additionally, with improved atmospheric correction methods, ocean color results produced global products of spectral water leaving radiance (L(sub W)). Ocean color results clearly indicated strong applications for characterizing the spatial and temporal variability of bio-optical oceanography. These studies were largely the results of advanced atmospheric correction techniques applied to multispectral imagery. The atmosphere contributes approximately 80 percent - 90 percent of the satellite received radiance in the blue-green portion of the spectrum. In deep ocean waters, maximum transmission of visible radiance is achieved at 490nm. Conversely, nearly all of the light is absorbed by the water at wavelengths greater than about 650nm and thus appears black. These spectral ocean properties are exploited by algorithms developed for the atmospheric correction used in satellite ocean color processing. The objective was to apply atmospheric correction techniques that were used for procesing satellite Coastal Zone Color Scanner (CZCS) data to AVIRIS data. Quantitative measures of L(sub W) from AVIRIS are compared with ship ground truth data and input into bio-optical models.

A Novel Scoring Metrics for Quality Assurance of Ocean Color Observations

NASA Astrophysics Data System (ADS)

Wei, J.; Lee, Z.

2016-02-01

Interpretation of the ocean bio-optical properties from ocean color observations depends on the quality of the ocean color data, specifically the spectrum of remote sensing reflectance (Rrs). The in situ and remotely measured Rrs spectra are inevitably subject to errors induced by instrument calibration, sea-surface correction and atmospheric correction, and other environmental factors. Great efforts have been devoted to the ocean color calibration and validation. Yet, there exist no objective and consensus criteria for assessment of the ocean color data quality. In this study, the gap is filled by developing a novel metrics for such data quality assurance and quality control (QA/QC). This new QA metrics is not intended to discard "suspicious" Rrs spectra from available datasets. Rather, it takes into account the Rrs spectral shapes and amplitudes as a whole and grades each Rrs spectrum. This scoring system is developed based on a large ensemble of in situ hyperspectral remote sensing reflectance data measured from various aquatic environments and processed with robust procedures. This system is further tested with the NASA bio-Optical Marine Algorithm Data set (NOMAD), with results indicating significant improvements in the estimation of bio-optical properties when Rrs spectra marked with higher quality assurance are used. This scoring system is further verified with simulated data and satellite ocean color data in various regions, and we envision higher quality ocean color products with the implementation of such a quality screening system.

Calibration Uncertainty in Ocean Color Satellite Sensors and Trends in Long-term Environmental Records

NASA Technical Reports Server (NTRS)

Turpie, Kevin R.; Eplee, Robert E., Jr.; Franz, Bryan A.; Del Castillo, Carlos

2014-01-01

Launched in late 2011, the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (NPP) spacecraft is being evaluated by NASA to determine whether this sensor can continue the ocean color data record established through the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and the MODerate resolution Imaging Spectroradiometer (MODIS). To this end, Goddard Space Flight Center generated evaluation ocean color data products using calibration techniques and algorithms established by NASA during the SeaWiFS and MODIS missions. The calibration trending was subjected to some initial sensitivity and uncertainty analyses. Here we present an introductory assessment of how the NASA-produced time series of ocean color is influenced by uncertainty in trending instrument response over time. The results help quantify the uncertainty in measuring regional and global biospheric trends in the ocean using satellite remote sensing, which better define the roles of such records in climate research.

Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

NASA Astrophysics Data System (ADS)

Ryu, Joo-Hyung; Han, Hee-Jeong; Cho, Seongick; Park, Young-Je; Ahn, Yu-Hwan

2012-09-01

GOCI, the world's first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.

Satellite Ocean Biology: Past, Present, Future

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2012-01-01

Since 1978 when the first satellite ocean color proof-of-concept sensor, the Nimbus-7 Coastal Zone Color Scanner, was launched, much progress has been made in refining the basic measurement concept and expanding the research applications of global satellite time series of biological and optical properties such as chlorophyll-a concentrations. The seminar will review the fundamentals of satellite ocean color measurements (sensor design considerations, on-orbit calibration, atmospheric corrections, and bio-optical algorithms), scientific results from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate resolution Imaging Spectroradiometer (MODIS) missions, and the goals of future NASA missions such as PACE, the Aerosol, Cloud, Ecology (ACE), and Geostationary Coastal and Air Pollution Events (GeoCAPE) missions.

Development of the atmospheric correction algorithm for the next generation geostationary ocean color sensor data

NASA Astrophysics Data System (ADS)

Lee, Kwon-Ho; Kim, Wonkook

2017-04-01

The geostationary ocean color imager-II (GOCI-II), designed to be focused on the ocean environmental monitoring with better spatial (250m for local and 1km for full disk) and spectral resolution (13 bands) then the current operational mission of the GOCI-I. GOCI-II will be launched in 2018. This study presents currently developing algorithm for atmospheric correction and retrieval of surface reflectance over land to be optimized with the sensor's characteristics. We first derived the top-of-atmosphere radiances as the proxy data derived from the parameterized radiative transfer code in the 13 bands of GOCI-II. Based on the proxy data, the algorithm has been made with cloud masking, gas absorption correction, aerosol inversion, computation of aerosol extinction correction. The retrieved surface reflectances are evaluated by the MODIS level 2 surface reflectance products (MOD09). For the initial test period, the algorithm gave error of within 0.05 compared to MOD09. Further work will be progressed to fully implement the GOCI-II Ground Segment system (G2GS) algorithm development environment. These atmospherically corrected surface reflectance product will be the standard GOCI-II product after launch.

Remote quantification of Cochlodinium polykrikoides blooms occurring in the East Sea using geostationary ocean color imager (GOCI).

PubMed

Noh, Jae Hoon; Kim, Wonkook; Son, Seung Hyun; Ahn, Jae-Hyun; Park, Young-Je

2018-03-01

Accurate and timely quantification of widespread harmful algal bloom (HAB) distribution is crucial to respond to the natural disaster, minimize the damage, and assess the environmental impact of the event. Although various remote sensing-based quantification approaches have been proposed for HAB since the advent of the ocean color satellite sensor, there have been no algorithms that were validated with in-situ quantitative measurements for the red tide occurring in the Korean seas. Furthermore, since the geostationary ocean color imager (GOCI) became available in June 2010, an algorithm that exploits its unprecedented observation frequency (every hour during the daytime) has been highly demanded to better track the changes in spatial distribution of red tide. This study developed a novel red tide quantification algorithm for GOCI that can estimate hourly chlorophyll-a (Chl a) concentration of Cochlodinium (Margalefidinium) polykrikoides, one of the major red tide species around Korean seas. The developed algorithm has been validated using in-situ Chl a measurements collected from a cruise campaign conducted in August 2013, when a massive C. polykrikoides bloom devastated Korean coasts. The proposed algorithm produced a high correlation (R 2 =0.92) with in-situ Chl a measurements with robust performance also for high Chl a concentration (300mg/m 3 ) in East Sea areas that typically have a relatively low total suspended particle concentration (<0.5mg/m 3 ). Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Atmospheric correction for hyperspectral ocean color sensors

NASA Astrophysics Data System (ADS)

Ibrahim, A.; Ahmad, Z.; Franz, B. A.; Knobelspiesse, K. D.

2017-12-01

NASA's heritage Atmospheric Correction (AC) algorithm for multi-spectral ocean color sensors is inadequate for the new generation of spaceborne hyperspectral sensors, such as NASA's first hyperspectral Ocean Color Instrument (OCI) onboard the anticipated Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite mission. The AC process must estimate and remove the atmospheric path radiance contribution due to the Rayleigh scattering by air molecules and by aerosols from the measured top-of-atmosphere (TOA) radiance. Further, it must also compensate for the absorption by atmospheric gases and correct for reflection and refraction of the air-sea interface. We present and evaluate an improved AC for hyperspectral sensors beyond the heritage approach by utilizing the additional spectral information of the hyperspectral sensor. The study encompasses a theoretical radiative transfer sensitivity analysis as well as a practical application of the Hyperspectral Imager for the Coastal Ocean (HICO) and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensors.

Aerosol Optical Properties over the Oceans: Summary and Interpretation of Shadow-Band Radiometer Data from Six Cruises. Chapter 19

NASA Technical Reports Server (NTRS)

Miller, Mark A.; Reynolds, R. M.; Bartholomew, Mary Jane

2001-01-01

The aerosol scattering component of the total radiance measured at the detectors of ocean color satellites is determined with atmospheric correction algorithms. These algorithms are based on aerosol optical thickness measurements made in two channels that lie in the near-infrared portion of the electromagnetic spectrum. The aerosol properties in the near-infrared region are used because there is no significant contribution to the satellite-measured radiance from the underlying ocean surface in that spectral region. In the visible wavelength bands, the spectrum of radiation scattered from the turbid atmosphere is convolved with the spectrum of radiation scattered from the surface layers of the ocean. The radiance contribution made by aerosols in the visible bands is determined from the near-infrared measurements through the use of aerosol models and radiation transfer codes. Selection of appropriate aerosol models from the near-infrared measurements is a fundamental challenge. There are several challenges with respect to the development, improvement, and evaluation of satellite ocean-color atmospheric correction algorithms. A common thread among these challenges is the lack of over-ocean aerosol data. Until recently, one of the most important limitations has been the lack of techniques and instruments to make aerosol measurements at sea. There has been steady progress in this area over the past five years, and there are several new and promising devices and techniques for data collection. The development of new instruments and the collection of more aerosol data from over the world's oceans have brought the realization that aerosol measurements that can be directly compared with aerosol measurements from ocean color satellite measurements are difficult to obtain. There are two problems that limit these types of comparisons: the cloudiness of the atmosphere over the world's oceans and the limitations of the techniques and instruments used to collect aerosol data from ships. To address the latter, we have developed a new type of shipboard sun photometer.

Improved Chlorophyll-a Algorithm for the Satellite Ocean Color Data in the Northern Bering Sea and Southern Chukchi Sea

NASA Astrophysics Data System (ADS)

Lee, Sang Heon; Ryu, Jongseong; Park, Jung-woo; Lee, Dabin; Kwon, Jae-Il; Zhao, Jingping; Son, SeungHyun

2018-03-01

The Bering and Chukchi seas are an important conduit to the Arctic Ocean and are reported to be one of the most productive regions in the world's oceans in terms of high primary productivity that sustains large numbers of fishes, marine mammals, and sea birds as well as benthic animals. Climate-induced changes in primary production and production at higher trophic levels also have been observed in the northern Bering and Chukchi seas. Satellite ocean color observations could enable the monitoring of relatively long term patterns in chlorophyll-a (Chl-a) concentrations that would serve as an indicator of phytoplankton biomass. The performance of existing global and regional Chl-a algorithms for satellite ocean color data was investigated in the northeastern Bering Sea and southern Chukchi Sea using in situ optical measurements from the Healy 2007 cruise. The model-derived Chl-a data using the previous Chl-a algorithms present striking uncertainties regarding Chl-a concentrations-for example, overestimation in lower Chl-a concentrations or systematic overestimation in the northeastern Bering Sea and southern Chukchi Sea. Accordingly, a simple two band ratio (R rs(443)/R rs(555)) algorithm of Chl-a for the satellite ocean color data was devised for the northeastern Bering Sea and southern Chukchi Sea. The MODIS-derived Chl-a data from July 2002 to December 2014 were produced using the new Chl-a algorithm to investigate the seasonal and interannual variations of Chl-a in the northern Bering Sea and the southern Chukchi Sea. The seasonal distribution of Chl-a shows that the highest (spring bloom) Chl-a concentrations are in May and the lowest are in July in the overall area. Chl-a concentrations relatively decreased in June, particularly in the open ocean waters of the Bering Sea. The Chl-a concentrations start to increase again in August and become quite high in September. In October, Chl-a concentrations decreased in the western area of the Study area and the Alaskan coastal waters. Strong interannual variations are shown in Chl-a concentrations in all areas. There is a slightly increasing trend in Chl-a concentrations in the northern Bering Strait (SECS). This increasing trend may be related to recent increases in the extent and duration of open waters due to the early break up of sea ice and the late formation of sea ice in the Chukchi Sea.

Identification of pixels with stray light and cloud shadow contaminations in the satellite ocean color data processing.

PubMed

Jiang, Lide; Wang, Menghua

2013-09-20

A new flag/masking scheme has been developed for identifying stray light and cloud shadow pixels that significantly impact the quality of satellite-derived ocean color products. Various case studies have been carried out to evaluate the performance of the new cloud contamination flag/masking scheme on ocean color products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). These include direct visual assessments, detailed quantitative case studies, objective statistic analyses, and global image examinations and comparisons. The National Oceanic and Atmospheric Administration (NOAA) Multisensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system has been used in the study. The new stray light and cloud shadow identification method has been shown to outperform the current stray light flag in both valid data coverage and data quality of satellite-derived ocean color products. In addition, some cloud-related flags from the official VIIRS-SNPP data processing software, i.e., the Interface Data Processing System (IDPS), have been assessed. Although the data quality with the IDPS flags is comparable to that of the new flag implemented in the NOAA-MSL12 ocean color data processing system, the valid data coverage from the IDPS is significantly less than that from the NOAA-MSL12 using the new stray light and cloud shadow flag method. Thus, the IDPS flag/masking algorithms need to be refined and modified to reduce the pixel loss, e.g., the proposed new cloud contamination flag/masking can be implemented in IDPS VIIRS ocean color data processing.

Empirical ocean color algorithms and bio-optical properties of the western coastal waters of Svalbard, Arctic

NASA Astrophysics Data System (ADS)

Son, Young-Sun; Kim, Hyun-cheol

2018-05-01

Chlorophyll (Chl) concentration is one of the key indicators identifying changes in the Arctic marine ecosystem. However, current Chl algorithms are not accurate in the Arctic Ocean due to different bio-optical properties from those in the lower latitude oceans. In this study, we evaluated the current Chl algorithms and analyzed the cause of the error in the western coastal waters of Svalbard, which are known to be sensitive to climate change. The NASA standard algorithms showed to overestimate the Chl concentration in the region. This was due to the high non-algal particles (NAP) absorption and colored dissolved organic matter (CDOM) variability at the blue wavelength. In addition, at lower Chl concentrations (0.1-0.3 mg m-3), chlorophyll-specific absorption coefficients were ∼2.3 times higher than those of other Arctic oceans. This was another reason for the overestimation of Chl concentration. OC4 algorithm-based regionally tuned-Svalbard Chl (SC4) algorithm for retrieving more accurate Chl estimates reduced the mean absolute percentage difference (APD) error from 215% to 49%, the mean relative percentage difference (RPD) error from 212% to 16%, and the normalized root mean square (RMS) error from 211% to 68%. This region has abundant suspended matter due to the melting of tidal glaciers. We evaluated the performance of total suspended matter (TSM) algorithms. Previous published TSM algorithms generally overestimated the TSM concentration in this region. The Svalbard TSM-single band algorithm for low TSM range (ST-SB-L) decreased the APD and RPD errors by 52% and 14%, respectively, but the RMS error still remained high (105%).

Development of ocean color algorithms for estimating chlorophyll-a concentrations and inherent optical properties using gene expression programming (GEP).

PubMed

Chang, Chih-Hua

2015-03-09

This paper proposes new inversion algorithms for the estimation of Chlorophyll-a concentration (Chla) and the ocean's inherent optical properties (IOPs) from the measurement of remote sensing reflectance (Rrs). With in situ data from the NASA bio-optical marine algorithm data set (NOMAD), inversion algorithms were developed by the novel gene expression programming (GEP) approach, which creates, manipulates and selects the most appropriate tree-structured functions based on evolutionary computing. The limitations and validity of the proposed algorithms are evaluated by simulated Rrs spectra with respect to NOMAD, and a closure test for IOPs obtained at a single reference wavelength. The application of GEP-derived algorithms is validated against in situ, synthetic and satellite match-up data sets compiled by NASA and the International Ocean Color Coordinate Group (IOCCG). The new algorithms are able to provide Chla and IOPs retrievals to those derived by other state-of-the-art regression approaches and obtained with the semi- and quasi-analytical algorithms, respectively. In practice, there are no significant differences between GEP, support vector regression, and multilayer perceptron model in terms of the overall performance. The GEP-derived algorithms are successfully applied in processing the images taken by the Sea Wide Field-of-view Sensor (SeaWiFS), generate Chla and IOPs maps which show better details of developing algal blooms, and give more information on the distribution of water constituents between different water bodies.

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm

NASA Astrophysics Data System (ADS)

Frouin, Robert; Deschamps, Pierre-Yves; Ramon, Didier; Steinmetz, François

2012-10-01

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

Advances in radiometry for ocean color

USGS Publications Warehouse

Brown, S.W.; Clark, D.K.; Johnson, B.C.; Yoon, H.; Lykke, K.R.; Flora, S.J.; Feinholz, M.E.; Souaidia, N.; Pietras, C.; Stone, T.C.; Yarbrough, M.A.; Kim, Y.S.; Barnes, R.A.; Mueller, J.L.

2004-01-01

We have presented a number of recent developments in radiometry that directly impact the uncertainties achievable in ocean-color research. Specifically, a new (2000) U. S. national irradiance scale, a new LASER-based facility for irradiance and radiance responsivity calibrations, and applications of the LASER facility for the calibration of sun photometers and characterization of spectrographs were discussed. For meaningful long-time-series global chlorophyll-a measurements, all instruments involved in radiometric measurements, including satellite sensors, vicarious calibration sensors, sensors used in the development of bio-optical algorithms and atmospheric characterization need to be fully characterized and corrected for systematic errors, including, but not limited to, stray light. A unique, solid-state calibration source is under development to reduce the radiometric uncertainties in ocean color instruments, in particular below 400 nm. Lunar measurements for trending of on-orbit sensor channel degradation were described. Unprecedented assessments, within 0.1 %, of temporal stability and drift in a satellite sensor's radiance responsivity are achievable with this approach. These developments advance the field of ocean color closer to the desired goal of reducing the uncertainty in the fundamental radiometry to a small component of the overall uncertainty in the derivation of remotely sensed ocean-color data products such as chlorophyll a.

Chlorophyll-a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference

NASA Technical Reports Server (NTRS)

Hu, Chuanmin; Lee, Zhongping; Franz, Bryan

2011-01-01

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.

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

NASA Astrophysics Data System (ADS)

Singh, Rakesh Kumar; Shanmugam, Palanisamy

2018-06-01

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.

Analysis of Photosynthetic Rate and Bio-Optical Components from Ocean Color Imagery

NASA Technical Reports Server (NTRS)

Kiefer, Dale A.; Stramski, Dariusz

1997-01-01

Our research over the last 5 years indicates that the successful transformation of ocean color imagery into maps of bio-optical properties will require continued development and testing of algorithms. In particular improvements in the accuracy of predicting from ocean color imagery the concentration of the bio-optical components of sea as well as the rate of photosynthesis will require progress in at least three areas: (1) we must improve mathematical models of the growth and physiological acclimation of phytoplankton; (2) we must better understand the sources of variability in the absorption and backscattering properties of phytoplankton and associated microparticles; and (3) we must better understand how the radiance distribution just below the sea surface varies as a function sun and sky conditions and inherent optical properties.

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters

NASA Technical Reports Server (NTRS)

Brown, Christopher W.; Brock, John C.

1998-01-01

The successful launch of the National Space Development Agency of Japan (NASDA) Ocean Color and Temperature Sensor (OCTS) in August 1996, and the launch of Orbital Science Corporation's (OSC) Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) in August 1997 signaled the beginning of a new era for ocean color research and application. These data may be used to remotely evaluate 1) water quality, 2) transport of sediments and adhered pollutants, 3) primary production, upon which commercial shellfish and finfish populations depend for food, and 4) harmful algal blooms which pose a threat to public health and economies of affected areas. Several US government agencies have recently expressed interest in monitoring U.S. coastal waters using optical remote sensing. This renewed interest is broadly driven by 1) resource management concerns over the impact of coastward shifts in population and land use on the ecosystems of estuaries, wetlands, nearshore benthic environments and fisheries, 2) recognition of the need to understand short time scale global change due to urbanization of sensitive land-margin ecosystems, and 3) national security issues. Satellite ocean color sensors have the potential to furnish data at the appropriate time and space scales to evaluate and resolve these concerns and problems. In this draft technical memorandum, we outline our progress during the first year of our SIMBIOS project to evaluate ocean color bio-optical algorithms and products generated using OCTS and SeaWiFS data in coastal US waters.

Algorithm Science to Operations for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Visible/Infrared Imager/Radiometer Suite (VIIRS)

NASA Technical Reports Server (NTRS)

Duda, James L.; Barth, Suzanna C

2005-01-01

The VIIRS sensor provides measurements for 22 Environmental Data Records (EDRs) addressing the atmosphere, ocean surface temperature, ocean color, land parameters, aerosols, imaging for clouds and ice, and more. That is, the VIIRS collects visible and infrared radiometric data of the Earth's atmosphere, ocean, and land surfaces. Data types include atmospheric, clouds, Earth radiation budget, land/water and sea surface temperature, ocean color, and low light imagery. This wide scope of measurements calls for the preparation of a multiplicity of Algorithm Theoretical Basis Documents (ATBDs), and, additionally, for intermediate products such as cloud mask, et al. Furthermore, the VIIRS interacts with three or more other sensors. This paper addresses selected and crucial elements of the process being used to convert and test an immense volume of a maturing and changing science code to the initial operational source code in preparation for launch of NPP. The integrity of the original science code is maintained and enhanced via baseline comparisons when re-hosted, in addition to multiple planned code performance reviews.

The NOAA-NASA CZCS Reanalysis Effort

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Conkright, Margarita E.; OReilly, John E.; Patt, Frederick S.; Wang, Meng-Hua; Yoder, James; Casey-McCabe, Nancy; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

Satellite observations of global ocean chlorophyll span over two decades. However, incompatibilities between processing algorithms prevent us from quantifying natural variability. We applied a comprehensive reanalysis to the Coastal Zone Color Scanner (CZCS) archive, called the NOAA-NASA CZCS Reanalysis (NCR) Effort. NCR consisted of 1) algorithm improvement (AI), where CZCS processing algorithms were improved using modernized atmospheric correction and bio-optical algorithms, and 2) blending, where in situ data were incorporated into the CZCS AI to minimize residual errors. The results indicated major improvement over the previously available CZCS archive. Global spatial and seasonal patterns of NCR chlorophyll indicated remarkable correspondence with modern sensors, suggesting compatibility. The NCR permits quantitative analyses of interannual and interdecadal trends in global ocean chlorophyll.

Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm.

PubMed

Lee, ZhongPing; Arnone, Robert; Hu, Chuanmin; Werdell, P Jeremy; Lubac, Bertrand

2010-01-20

Following the theory of error propagation, we developed analytical functions to illustrate and evaluate the uncertainties of inherent optical properties (IOPs) derived by the quasi-analytical algorithm (QAA). In particular, we evaluated the effects of uncertainties of these optical parameters on the inverted IOPs: the absorption coefficient at the reference wavelength, the extrapolation of particle backscattering coefficient, and the spectral ratios of absorption coefficients of phytoplankton and detritus/gelbstoff, respectively. With a systematically simulated data set (46,200 points), we found that the relative uncertainty of QAA-derived total absorption coefficients in the blue-green wavelengths is generally within +/-10% for oceanic waters. The results of this study not only establish theoretical bases to evaluate and understand the effects of the various variables on IOPs derived from remote-sensing reflectance, but also lay the groundwork to analytically estimate uncertainties of these IOPs for each pixel. These are required and important steps for the generation of quality maps of IOP products derived from satellite ocean color remote sensing.

Applications of satellite ocean color sensors for monitoring and predicting harmful algal blooms

USGS Publications Warehouse

Stumpf, Richard P.

2001-01-01

The new satellite ocean color sensors offer a means of detecting and monitoring algal blooms in the ocean and coastal zone. Beginning with SeaWiFS (Sea Wide Field-of-view Sensor) in September 1997, these sensors provide coverage every 1 to 2 days with 1-km pixel view at nadir. Atmospheric correction algorithms designed for the coastal zone combined with regional chlorophyll algorithms can provide good and reproducible estimates of chlorophyll, providing the means of monitoring various algal blooms. Harmful algal blooms (HABs) caused by Karenia brevis in the Gulf of Mexico are particularly amenable to remote observation. The Gulf of Mexico has relatively clear water and K. brevis, in bloom conditions, tends to produce a major portion of the phytoplankton biomass. A monitoring program has begun in the Gulf of Mexico that integrates field data from state monitoring programs with satellite imagery, providing an improved capability for the monitoring of K. brevis blooms.

Radiative transfer simulations of the two-dimensional ocean glint reflectance and determination of the sea surface roughness.

PubMed

Lin, Zhenyi; Li, Wei; Gatebe, Charles; Poudyal, Rajesh; Stamnes, Knut

2016-02-20

An optimized discrete-ordinate radiative transfer model (DISORT3) with a pseudo-two-dimensional bidirectional reflectance distribution function (BRDF) is used to simulate and validate ocean glint reflectances at an infrared wavelength (1036 nm) by matching model results with a complete set of BRDF measurements obtained from the NASA cloud absorption radiometer (CAR) deployed on an aircraft. The surface roughness is then obtained through a retrieval algorithm and is used to extend the simulation into the visible spectral range where diffuse reflectance becomes important. In general, the simulated reflectances and surface roughness information are in good agreement with the measurements, and the diffuse reflectance in the visible, ignored in current glint algorithms, is shown to be important. The successful implementation of this new treatment of ocean glint reflectance and surface roughness in DISORT3 will help improve glint correction algorithms in current and future ocean color remote sensing applications.

Radiative Transfer Simulations of the Two-Dimensional Ocean Glint Reflectance and Determination of the Sea Surface Roughness

NASA Technical Reports Server (NTRS)

Lin, Zhenyi; Li, Wei; Gatebe, Charles; Poudyal, Rajesh; Stamnes, Knut

2016-01-01

An optimized discrete-ordinate radiative transfer model (DISORT3) with a pseudo-two-dimensional bidirectional reflectance distribution function (BRDF) is used to simulate and validate ocean glint reflectances at an infrared wavelength (1036 nm) by matching model results with a complete set of BRDF measurements obtained from the NASA cloud absorption radiometer (CAR) deployed on an aircraft. The surface roughness is then obtained through a retrieval algorithm and is used to extend the simulation into the visible spectral range where diffuse reflectance becomes important. In general, the simulated reflectances and surface roughness information are in good agreement with the measurements, and the diffuse reflectance in the visible, ignored in current glint algorithms, is shown to be important. The successful implementation of this new treatment of ocean glint reflectance and surface roughness in DISORT3 will help improve glint correction algorithms in current and future ocean color remote sensing applications.

Determining phytoplankton community structure from ocean color at the Martha's Vineyard Coastal Observatory (MVCO)

NASA Astrophysics Data System (ADS)

Kramer, S. J.; Sosik, H. M.; Roesler, C. S.

2016-02-01

Satellite remote sensing of ocean color allows for estimates of phytoplankton biomass on broad spatial and temporal scales. Recently, a variety of approaches have been offered for determining phytoplankton taxonomic composition or phytoplankton functional types (PFTs) from remote sensing reflectance. These bio-optical algorithms exploit spectral differences to discriminate waters dominated by different types of cells. However, the efficacy of these models remains difficult to constrain due to limited datasets for detailed validation. In this study, we examined the region around the Martha's Vineyard Coastal Observatory (MVCO), a near-shore location on the New England shelf with optically complex coastal waters. This site offers many methods for detailed validation of ocean color algorithms: an AERONET-OC above-water radiometry system provides sea-truth ocean color observations; time series of absorption and backscattering coefficients are measured; and phytoplankton composition is assessed with a combination of continuous in situ flow cytometry and intermittent discrete sampling for HPLC pigments. Our analysis showed that even models originally parameterized for the Northwest Atlantic perform poorly in capturing the variability in relationships between optical properties and water constituents at coastal sites such as MVCO. We refined models with local parameterizations of variability in absorption and backscattering coefficients, and achieved much better agreement of modeled and observed relationships between predicted spectral reflectance, chlorophyll concentration, and indices of phytoplankton composition such as diatom dominance. Applying these refined models to satellite remote sensing imagery offers the possibility of describing large-scale variations in phytoplankton community structure both at MVCO and on the surrounding shelf over space and time.

Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

NASA Astrophysics Data System (ADS)

Banghua Yan, B.

2016-02-01

Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in combination with the new QA monitoring tool will more efficiently ensure availability and quality of satellite operational OC products from Okeanos system to the user community. The QA tool also will provide much useful information of OC products quality and statistics to the OC user community.

SeaWiFS technical report series. Volume 13: Case studies for SeaWiFS calibration and validation, part 1

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Mcclain, Charles R.; Comiso, Josefino C.; Fraser, Robert S.; Firestone, James K.; Schieber, Brian D.; Yeh, Eueng-Nan; Arrigo, Kevin R.; Sullivan, Cornelius W.

1994-01-01

Although the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Calibration and Validation Program relies on the scientific community for the collection of bio-optical and atmospheric correction data as well as for algorithm development, it does have the responsibility for evaluating and comparing the algorithms and for ensuring that the algorithms are properly implemented within the SeaWiFS Data Processing System. This report consists of a series of sensitivity and algorithm (bio-optical, atmospheric correction, and quality control) studies based on Coastal Zone Color Scanner (CZCS) and historical ancillary data undertaken to assist in the development of SeaWiFS specific applications needed for the proper execution of that responsibility. The topics presented are as follows: (1) CZCS bio-optical algorithm comparison, (2) SeaWiFS ozone data analysis study, (3) SeaWiFS pressure and oxygen absorption study, (4) pixel-by-pixel pressure and ozone correction study for ocean color imagery, (5) CZCS overlapping scenes study, (6) a comparison of CZCS and in situ pigment concentrations in the Southern Ocean, (7) the generation of ancillary data climatologies, (8) CZCS sensor ringing mask comparison, and (9) sun glint flag sensitivity study.

The Proposal for the NASA Sensor Intercalibration and Merger for Biological and Interdisciplinary Oceanic Studies(SIMBIOS) Program, 1995

NASA Technical Reports Server (NTRS)

McClain, Charles; Esaias, Wayne; Feldman, Gene; Gregg, Watson; Hooker, Stanford; Frouin, Robert

2002-01-01

As a result of the Earth Observing System (EOS) restructuring exercise during the last half of fiscal year 1994, the EOS Color mission, which was scheduled to be a data-buy with a 1998 launch was dropped from the EOS mission manifest primarily because of the number of international ocean color missions scheduled for launch in the 1998 time frame. In lieu of a new mission, NASA Goddard Space Flight Center (GSFC) was tasked by NASA Headquarters to develop an ocean color satellite calibration and validation plan for multiple sensors. The objective of the activity was to develop a methodology and operational capability to combine data products from the various ocean color missions in a manner that ensures the best possible global coverage and data quality. The program was called the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project coined from the biological term "symbiosis." This document is the original proposal that was developed and submitted in May 1995. SIMBIOS was approved in 1996 and initiated in 1997 with a project office and technical staff at GSFC and a science team to assist in the development of validation data sets, sensor calibration, atmospheric correction, and bio-optical and data merger algorithms. Since its inception, the SIMBIOS program has resulted in a broad-based international collaboration on the calibration and validation of a number of ocean color satellites.

An Empirical Approach to Ocean Color Data: Reducing Bias and the Need for Post-Launch Radiometric Re-Calibration

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.; O'Reilly, John E.; Esaias, Wayne E.

2009-01-01

A new empirical approach is developed for ocean color remote sensing. Called the Empirical Satellite Radiance-In situ Data (ESRID) algorithm, the approach uses relationships between satellite water-leaving radiances and in situ data after full processing, i.e., at Level-3, to improve estimates of surface variables while relaxing requirements on post-launch radiometric re-calibration. The approach is evaluated using SeaWiFS chlorophyll, which is the longest time series of the most widely used ocean color geophysical product. The results suggest that ESRID 1) drastically reduces the bias of ocean chlorophyll, most impressively in coastal regions, 2) modestly improves the uncertainty, and 3) reduces the sensitivity of global annual median chlorophyll to changes in radiometric re-calibration. Simulated calibration errors of 1% or less produce small changes in global median chlorophyll (less than 2.7%). In contrast, the standard NASA algorithm set is highly sensitive to radiometric calibration: similar 1% calibration errors produce changes in global median chlorophyll up to nearly 25%. We show that 0.1% radiometric calibration error (about 1% in water-leaving radiance) is needed to prevent radiometric calibration errors from changing global annual median chlorophyll more than the maximum interannual variability observed in the SeaWiFS 9-year record (+/- 3%), using the standard method. This is much more stringent than the goal for SeaWiFS of 5% uncertainty for water leaving radiance. The results suggest ocean color programs might consider less emphasis of expensive efforts to improve post-launch radiometric re-calibration in favor of increased efforts to characterize in situ observations of ocean surface geophysical products. Although the results here are focused on chlorophyll, in principle the approach described by ESRID can be applied to any surface variable potentially observable by visible remote sensing.

Future U.S. ocean color missions-OCI, MODIS and HIRIS

NASA Astrophysics Data System (ADS)

Davis, C. O.

The Coastal Zone Color Scanner (CZCS) launched by the National Aeronautics and Space Administration (NASA) on the Nimbus-7 Satellite in 1978 has provided exceptionally valuable data for studies of the productivity of the ocean, fisheries, the detection of oceanic fronts and currents, and the optical properties of the ocean. NASA has been working with the scientific community, the National Oceanographic and Atmospheric Administration (NOAA), France's Centre National d'Etudes Spatiales (CNES), and industry to develop an Ocean Color Imager (OCI), a follow-on instrument which would provide the near real-time and global data necessary to fill these needs in the 1990's. The Earth Observing Satellite Company (EOSAT) is considering flying an ocean and land wide-field color instrument which would meet these needs on Landsat 6 or 7 planned for launch in 1989 and 1991, respectively. It would provide eight ocean color channels for improved atmospheric correction and in-water algorithms, global coverage and near real-time data for operational uses. In the mid 1990's NASA is planning to fly a Moderate Resolution Imaging Spectrometer (MODIS) and a High Resolution Imaging Spectrometer (HIRIS) as part of the Earth Observing System (Eos) on the Polar Platform of the Space Station. These instruments are array spectrometers which would provide full spectral resolution in the visible and infrared. This opens the possibility of separating different groups of phytoplankton, suspended sediments and other substances in the water. Also, HIRIS would have across track pointing ability which will allow high resolution rapid sampling of dynamic coastal areas and estuaries.

An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing

NASA Astrophysics Data System (ADS)

Werdell, P. Jeremy; McKinna, Lachlan I. W.; Boss, Emmanuel; Ackleson, Steven G.; Craig, Susanne E.; Gregg, Watson W.; Lee, Zhongping; Maritorena, Stéphane; Roesler, Collin S.; Rousseaux, Cécile S.; Stramski, Dariusz; Sullivan, James M.; Twardowski, Michael S.; Tzortziou, Maria; Zhang, Xiaodong

2018-01-01

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Reprocessing of the OCTS Global Dataset, a Collaborative Effort Between NASDA and the NASA SIMBIOS Project

NASA Astrophysics Data System (ADS)

Tanaka, T.; Franz, B. A.; Acker, J. G.; Asanuma, I.; Bailey, S.; Eplee, R. E.; Fukushima, H.; Gales, J. M.; Maritorena, S.; Mitomi, Y.; Murakami, H.; O'Reilly, J. E.; Shen, S.; Smith, P.; Wang, M.; Wilding, J.; Woodford, B.

2001-12-01

As a payload on the ADEOS spacecraft, the Ocean Color and Temperature Scanner (OCTS) was launched and operated by the National Space Development Agency (NASDA) of Japan in August of 1996. The OCTS instrument began routine imaging in November of 1996, making it the first operational mission dedicated to the acquisition and monitoring of oceanic chlorophyll concentration on a global scale. Although the ADEOS spacecraft suffered a catastrophic failure less than eleven months after launch, the data collected during the OCTS mission lifetime is of great value to the Earth science community, as it can provide important information on the baseline state of the worlds oceans prior to the El Nino event of 1997-1998. The second global ocean color mission to be launched was the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), which has been collecting global data continuously since September of 1997. The unfortunate gap between the end of OCTS operations and the start of SeaWiFS operations makes direct sensor to sensor comparisons impossible, thus leaving considerable uncertainty in any effort to extend the SeaWiFS global ocean color timeseries back to the pre-1997 El Nino period, or to study the propagation of Kelvin and Rossby waves associated with the transition into El Nino. This uncertainty can result from relative differences in instrument calibrations, as well as differences in the atmospheric correction and bio-optical algorithms employed. The focus of the present work is to minimize the potential differences in the atmospheric correction and bio-optical algorithms between the two sensors, by reprocessing the entire OCTS GAC mission archive using the same software and algorithms employed for standard SeaWiFS processing. The data processing stream will be presented, and OCTS-specific modifications to the algorithms will be discussed. Statistical comparisons between OCTS and SeaWiFS will be shown, and remaining processing issues will be highlighted. Finally, the OCTS product list and data distribution procedures will be provided.

Surface-roughness considerations for atmospheric correction of ocean color sensors. I: The Rayleigh-scattering component.

PubMed

Gordon, H R; Wang, M

1992-07-20

The first step in the coastal zone color scanner (CZCS) atmospheric-correction algorithm is the computation of the Rayleigh-scattering contribution, Lr(r), to the radiance leaving the top of the atmosphere over the ocean. In the present algorithm Lr(r), is computed by assuming that the ocean surface is flat. Computations of the radiance leaving a Rayleigh-scattering atmosphere overlying a rough Fresnel-reflecting ocean are presented to assess the radiance error caused by the flat-ocean assumption. The surface-roughness model is described in detail for both scalar and vector (including polarization) radiative transfer theory. The computations utilizing the vector theory show that the magnitude of the error significantly depends on the assumptions made in regard to the shadowing of one wave by another. In the case of the coastal zone color scanner bands, we show that for moderate solar zenith angles the error is generally below the 1 digital count level, except near the edge of the scan for high wind speeds. For larger solar zenith angles, the error is generally larger and can exceed 1 digital count at some wavelengths over the entire scan, even for light winds. The error in Lr(r) caused by ignoring surface roughness is shown to be the same order of magnitude as that caused by uncertainties of +/- 15 mb in the surface atmospheric pressure or of +/- 50 Dobson units in the ozone concentration. For future sensors, which will have greater radiometric sensitivity, the error caused by the flat-ocean assumption in the computation of Lr(r) could be as much as an order of magnitude larger than the noise-equivalent spectral radiance in certain situations.

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Adrea

2004-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Atmospheric Correction for Satellite Ocean Color Radiometry

NASA Technical Reports Server (NTRS)

Mobley, Curtis D.; Werdell, Jeremy; Franz, Bryan; Ahmad, Ziauddin; Bailey, Sean

2016-01-01

This tutorial is an introduction to atmospheric correction in general and also documentation of the atmospheric correction algorithms currently implemented by the NASA Ocean Biology Processing Group (OBPG) for processing ocean color data from satellite-borne sensors such as MODIS and VIIRS. The intended audience is graduate students or others who are encountering this topic for the first time. The tutorial is in two parts. Part I discusses the generic atmospheric correction problem. The magnitude and nature of the problem are first illustrated with numerical results generated by a coupled ocean-atmosphere radiative transfer model. That code allow the various contributions (Rayleigh and aerosol path radiance, surface reflectance, water-leaving radiance, etc.) to the topof- the-atmosphere (TOA) radiance to be separated out. Particular attention is then paid to the definition, calculation, and interpretation of the so-called "exact normalized water-leaving radiance" and its equivalent reflectance. Part I ends with chapters on the calculation of direct and diffuse atmospheric transmittances, and on how vicarious calibration is performed. Part II then describes one by one the particular algorithms currently used by the OBPG to effect the various steps of the atmospheric correction process, viz. the corrections for absorption and scattering by gases and aerosols, Sun and sky reflectance by the sea surface and whitecaps, and finally corrections for sensor out-of-band response and polarization effects. One goal of the tutorial-guided by teaching needs- is to distill the results of dozens of papers published over several decades of research in atmospheric correction for ocean color remote sensing.

Cal/Val Study for Geostationary Ocean Color Imager

NASA Astrophysics Data System (ADS)

Ryu, J.; Moon, J.; Min, J.; Cho, S.; Ahn, Y.

2009-12-01

GOCI, the first Geostationary Ocean Color Imager, shall be operated in a staring-frame capture mode onboard its Communication Ocean and Meteorological Satellite (COMS) and tentatively scheduled for launch in 2010. The mission concept includes eight visible-to-near-infrared bands, 0.5 km pixel resolution, and a coverage region of 2,500 × 2,500 km2 centered at Korea. The GOCI is expected to provide SeaWiFS quality observations for a single study area with imaging interval of 1 hour from 10 am to 5 pm. Due to optically more complex waters of GOCI swath area, we developed new atmospheric correction and bio-optical algorithms for GOCI. The 1st objective is to compare and validate the water-leaving radiance using the radiometric data from spectroradiometer installed in Ieodo and Gaegeocho ocean research station. The 2nd objective is to calibrate and validate the bio-optical product by GDPS using the Dokdo buoy and in situ measurements. As the result of comparison of spectrum shape using the remote reflectance normalized 555 nm, most of all data was well matched. Validation result of local bio-optical algorithms installed in GDPS showed the less than 20 %.

Estimating the marine signal in the near infrared for atmospheric correction of satellite ocean-color imagery over turbid waters

NASA Astrophysics Data System (ADS)

Bourdet, Alice; Frouin, Robert J.

2014-11-01

The classic atmospheric correction algorithm, routinely applied to second-generation ocean-color sensors such as SeaWiFS, MODIS, and MERIS, consists of (i) estimating the aerosol reflectance in the red and near infrared (NIR) where the ocean is considered black (i.e., totally absorbing), and (ii) extrapolating the estimated aerosol reflectance to shorter wavelengths. The marine reflectance is then retrieved by subtraction. Variants and improvements have been made over the years to deal with non-null reflectance in the red and near infrared, a general situation in estuaries and the coastal zone, but the solutions proposed so far still suffer some limitations, due to uncertainties in marine reflectance modeling in the near infrared or difficulty to extrapolate the aerosol signal to the blue when using observations in the shortwave infrared (SWIR), a spectral range far from the ocean-color wavelengths. To estimate the marine signal (i.e., the product of marine reflectance and atmospheric transmittance) in the near infrared, the proposed approach is to decompose the aerosol reflectance in the near infrared to shortwave infrared into principal components. Since aerosol scattering is smooth spectrally, a few components are generally sufficient to represent the perturbing signal, i.e., the aerosol reflectance in the near infrared can be determined from measurements in the shortwave infrared where the ocean is black. This gives access to the marine signal in the near infrared, which can then be used in the classic atmospheric correction algorithm. The methodology is evaluated theoretically from simulations of the top-of-atmosphere reflectance for a wide range of geophysical conditions and angular geometries and applied to actual MODIS imagery acquired over the Gulf of Mexico. The number of discarded pixels is reduced by over 80% using the PC modeling to determine the marine signal in the near infrared prior to applying the classic atmospheric correction algorithm.

Global Ocean Phytoplankton

NASA Technical Reports Server (NTRS)

Franz, B. A.; Behrenfeld, M. J.; Siegel, D. A.; Werdell, P. J.

2014-01-01

Marine phytoplankton are responsible for roughly half the net primary production (NPP) on Earth, fixing atmospheric CO2 into food that fuels global ocean ecosystems and drives the ocean's biogeochemical cycles. Phytoplankton growth is highly sensitive to variations in ocean physical properties, such as upper ocean stratification and light availability within this mixed layer. Satellite ocean color sensors, such as the Sea-viewing Wide Field-of-view Sensor (SeaWiFS; McClain 2009) and Moderate Resolution Imaging Spectroradiometer (MODIS; Esaias 1998), provide observations of sufficient frequency and geographic coverage to globally monitor physically-driven changes in phytoplankton distributions. In practice, ocean color sensors retrieve the spectral distribution of visible solar radiation reflected upward from beneath the ocean surface, which can then be related to changes in the photosynthetic phytoplankton pigment, chlorophyll- a (Chla; measured in mg m-3). Here, global Chla data for 2013 are evaluated within the context of the 16-year continuous record provided through the combined observations of SeaWiFS (1997-2010) and MODIS on Aqua (MODISA; 2002-present). Ocean color measurements from the recently launched Visible and Infrared Imaging Radiometer Suite (VIIRS; 2011-present) are also considered, but results suggest that the temporal calibration of the VIIRS sensor is not yet sufficiently stable for quantitative global change studies. All MODISA (version 2013.1), SeaWiFS (version 2010.0), and VIIRS (version 2013.1) data presented here were produced by NASA using consistent Chla algorithms.

Are the World's Oceans Optically Different?

NASA Technical Reports Server (NTRS)

Szeto, M.; Werdell, P. J.; Moore, T. S.; Campbell, J. W.

2011-01-01

Regional differences in the Sea-viewing Wide Field-of-view Sensor chlorophyll algorithm uncertainty were observed in a large global data set containing coincident in situ measurements of chlorophyll a concentration (Chla) and spectral radiometry. The uncertainty was found to be systematic when the data were sorted by ocean: Atlantic, Pacific, Southern, and Indian Oceans. Artifacts associated with different instrumentation and analytical methods had been previously ruled out. Given these oceanic biases in the chlorophyll algorithm, we hypothesized that the oceans may be optically different, and their optical differences may be intrinsically related to regional differences in phytoplankton community structure or biogeochemical processes. The oceanic biases, originally observed using radiometric measurements, were independently verified using total absorption measurements in a subset of the data. Moreover, they were explained through oceanic differences in the absorption of colored detrital matter (CDM) and phytoplankton. Both effects were considered together in explaining the ocean biases through a stepwise linear regression analysis. Significant oceanic differences in the amount of CDM and in phytoplankton cell sizes and pigmentation would give rise to optical differences, but we raise a concern for the spatial coverage of the data. We do not suggest the application of ocean-based algorithms but rather emphasize the importance of consolidating regional data sets before reaching this conclusion.

Dissolved Organic Carbon along the Louisiana coast from MODIS and MERIS satellite data

NASA Astrophysics Data System (ADS)

Chaichi Tehrani, N.; D'Sa, E. J.

2012-12-01

Dissolved organic carbon (DOC) plays a critical role in the coastal and ocean carbon cycle. Hence, it is important to monitor and investigate its the distribution and fate in coastal waters. Since DOC cannot be measured directly through satellite remote sensors, chromophoric dissolved organic matter (CDOM) as an optically active fraction of DOC can be used as an alternative proxy to trace DOC concentrations. Here, satellite ocean color data from MODIS, MERIS, and field measurements of CDOM and DOC were used to develop and assess CDOM and DOC ocean color algorithms for coastal waters. To develop a CDOM retrieval algorithm, empirical relationships between CDOM absorption coefficient at 412 nm (aCDOM(412)) and reflectance ratios Rrs(488)/Rrs(555) for MODIS and Rrs(510)/Rrs(560) for MERIS were established. The performance of two CDOM empirical algorithms were evaluated for retrieval of (aCDOM(412)) from MODIS and MERIS in the northern Gulf of Mexico. Further, empirical algorithms were developed to estimate DOC concentration using the relationship between in situ aCDOM(412) and DOC, as well as using the newly developed CDOM empirical algorithms. Accordingly, our results revealed that DOC concentration was strongly correlated to aCDOM (412) for summer and spring-winter periods (r2 = 0.9 for both periods). Then, using the aCDOM(412)-Rrs and the aCDOM(412)-DOC relationships derived from field measurements, a relationship between DOC-Rrs was established for MODIS and MERIS data. The DOC empirical algorithms performed well as indicated by match-up comparisons between satellite estimates and field data (R2=0.52 and 0.58 for MODIS and MERIS for summer period, respectively). These algorithms were then used to examine DOC distribution along the Louisiana coast.

Algorithms for Processing and Analysis of Ocean Color Satellite Data for Coastal Case 2 Waters. Chapter 16

NASA Technical Reports Server (NTRS)

Stumpf, Richard P.; Arnone, Robert A.; Gould, Richard W., Jr.; Ransibrahmanakul, Varis; Tester, Patricia A.

2003-01-01

SeaWiFS has the ability to enhance our understanding of many oceanographic processes. However, its utility in the coastal zone has been limited by valid bio-optical algorithms and by the determination of accurate water reflectances, particularly in the blue bands (412-490 nm), which have a significant impact on the effectiveness of all bio-optical algorithms. We have made advances in three areas: algorithm development (Table 16.1), field data collection, and data applications.

Comparing the Ocean Color Measurements Between MOS and SeaWiFS: A Vicarious Intercalibration Approach for MOS

NASA Technical Reports Server (NTRS)

Wang, Menghua; Franz, Bryan A.

1998-01-01

One of the primary goals of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project is to develop methods for meaningful comparison and possible merging of data products from multiple ocean color missions. The Modular Optoelectronic Scanner (MOS) is a German instrument that was launched in the spring of 1996 on the Indian IRS-P3 satellite. With the successful launch of NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) in the summer of 1997, there are now two ocean color missions in concurrent operation and there is interest within the scientific community to compare data from these two sensors. In this paper, we describe our efforts to retrieve ocean optical properties from both SeaWiFS and MOS using consistent methods. We first briefly review the atmospheric correction, which removes more than 90% of the observed radiances in the visible, and then describe how the atmospheric correction algorithm used for the SeaWiFS data can be modified for application to other ocean color sensors. Next, since the retrieved water-leaving radiances in the visible between MOS and SeaWiFS are significantly different, we developed a vicarious intercalibration method to recalibrate the MOS spectral bands based on the optical properties of the ocean and atmosphere derived from the coincident SeaWiFS measurements. We present and discuss the MOS retrieved ocean optical properties before and after the vicarious calibration, and demonstrate the efficacy of this approach. We show that it is possible and efficient to vicariously intercalibrate sensors between one and another.

Phytoplankton pigment concentrations in the Middle Atlantic Bight - Comparison of ship determinations and CZCS estimates. [Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Gordon, H. R.; Brown, J. W.; Clark, D. K.; Brown, O. B.; Evans, R. H.; Broenkow, W. W.

1983-01-01

The processing algorithms used for relating the apparent color of the ocean observed with the Coastal-Zone Color Scanner on Nimbus-7 to the concentration of phytoplankton pigments (principally the pigment responsible for photosynthesis, chlorophyll-a) are developed and discussed in detail. These algorithms are applied to the shelf and slope waters of the Middle Atlantic Bight and also to Sargasso Sea waters. In all, four images are examined, and the resulting pigment concentrations are compared to continuous measurements made along ship tracks. The results suggest that over the 0.08-1.5 mg/cu m range, the error in the retrieved pigment concentration is of the order of 30-40% for a variety of atmospheric turbidities. In three direct comparisons between ship-measured and satellite-retrieved values of the water-leaving radiance, the atmospheric correction algorithm retrieved the water-leaving radiance with an average error of about 10%. This atmospheric correction algorithm does not require any surface measurements for its application.

Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate.

PubMed

Dierssen, Heidi M

2010-10-05

Phytoplankton biomass and productivity have been continuously monitored from ocean color satellites for over a decade. Yet, the most widely used empirical approach for estimating chlorophyll a (Chl) from satellites can be in error by a factor of 5 or more. Such variability is due to differences in absorption and backscattering properties of phytoplankton and related concentrations of colored-dissolved organic matter (CDOM) and minerals. The empirical algorithms have built-in assumptions that follow the basic precept of biological oceanography--namely, oligotrophic regions with low phytoplankton biomass are populated with small phytoplankton, whereas more productive regions contain larger bloom-forming phytoplankton. With a changing world ocean, phytoplankton composition may shift in response to altered environmental forcing, and CDOM and mineral concentrations may become uncoupled from phytoplankton stocks, creating further uncertainty and error in the empirical approaches. Hence, caution is warranted when using empirically derived Chl to infer climate-related changes in ocean biology. The Southern Ocean is already experiencing climatic shifts and shows substantial errors in satellite-derived Chl for different phytoplankton assemblages. Accurate global assessments of phytoplankton will require improved technology and modeling, enhanced field observations, and ongoing validation of our "eyes in space."

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; Kim, M.; Park, Y. Je; Jeong, U.; Kim, W.; Holben, B.; Eck, T. F.; Lim, J. H.; Song, C. K.

2015-09-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorology Satellites (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm over ocean and land together with validation results during the DRAGON-NE Asia 2012 campaign. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type from selected aerosol models in calculating AOD. Assumed aerosol models are compiled from global Aerosol Robotic Networks (AERONET) inversion data, and categorized according to AOD, FMF, and SSA. Nonsphericity is considered, and unified aerosol models are used over land and ocean. Different assumptions for surface reflectance are applied over ocean and land. Surface reflectance over the ocean varies with geometry and wind speed, while surface reflectance over land is obtained from the 1-3 % darkest pixels in a 6 km × 6 km area during 30 days. In the East China Sea and Yellow Sea, significant area is covered persistently by turbid waters, for which the land algorithm is used for aerosol retrieval. To detect turbid water pixels, TOA reflectance difference at 660 nm is used. GOCI YAER products are validated using other aerosol products from AERONET and the MODIS Collection 6 aerosol data from "Dark Target (DT)" and "Deep Blue (DB)" algorithms during the DRAGON-NE Asia 2012 campaign from March to May 2012. Comparison of AOD from GOCI and AERONET gives a Pearson correlation coefficient of 0.885 and a linear regression equation with GOCI AOD =1.086 × AERONET AOD - 0.041. GOCI and MODIS AODs are more highly correlated over ocean than land. Over land, especially, GOCI AOD shows better agreement with MODIS DB than MODIS DT because of the choice of surface reflectance assumptions. Other GOCI YAER products show lower correlation with AERONET than AOD, but are still qualitatively useful.

Phase 2 development of Great Lakes algorithms for Nimbus-7 coastal zone color scanner

NASA Technical Reports Server (NTRS)

Tanis, Fred J.

1984-01-01

A series of experiments have been conducted in the Great Lakes designed to evaluate the application of the NIMBUS-7 Coastal Zone Color Scanner (CZCS). Atmospheric and water optical models were used to relate surface and subsurface measurements to satellite measured radiances. Absorption and scattering measurements were reduced to obtain a preliminary optical model for the Great Lakes. Algorithms were developed for geometric correction, correction for Rayleigh and aerosol path radiance, and prediction of chlorophyll-a pigment and suspended mineral concentrations. The atmospheric algorithm developed compared favorably with existing algorithms and was the only algorithm found to adequately predict the radiance variations in the 670 nm band. The atmospheric correction algorithm developed was designed to extract needed algorithm parameters from the CZCS radiance values. The Gordon/NOAA ocean algorithms could not be demonstrated to work for Great Lakes waters. Predicted values of chlorophyll-a concentration compared favorably with expected and measured data for several areas of the Great Lakes.

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.; Song, Chul H.; Lim, Jae-Hyun; Song, Chang-Keun

2016-04-01

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Ångström exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 × AERONET AOD - 0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.

GOCI Yonsei Aerosol Retrieval (YAER) Algorithm and Validation During the DRAGON-NE Asia 2012 Campaign

NASA Technical Reports Server (NTRS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Jeong, Ukkyo; Kim, Woogyung; Hong, Hyunkee; Holben, Brent; Eck, Thomas F.;

In situ spectral response of the Arabian Gulf and Sea of Oman coastal waters to bio-optical properties.

PubMed

Al Shehhi, Maryam R; Gherboudj, Imen; Ghedira, Hosni

2017-10-01

Mapping of Chlorophyll-a (Chl-a) over the coastal waters of the Arabian Gulf and the Sea of Oman using the satellite-based observations, such as MODIS (Moderate Resolution Imaging Spectro-radiometer), has shown inferior performance (Chl-a overestimation) than that of deep waters. Studies in the region have shown that this poor performance is due to three reasons: (i) water turbidity (sediments re-suspension), and the presence of colored dissolved organic matter (CDOM), (ii) bottom reflectance and (iii) incapability of the existing atmospheric correction models to reduce the effect of the aerosols from the water leaving radiance. Therefore, this work focuses on investigating the sensitivity of the in situ spectral signatures of these coastal waters to the algal (chlorophyll: Chl-a), non-algal (sediments and CDOM) and the bottom reflectance properties, in absence of contributions from the atmosphere. Consequently, the collected in situ spectral signatures will improve our understanding of Arabian Gulf and Sea of Oman water properties. For this purpose, comprehensive field measurements were carried out between 2013 and 2016, over Abu-Dhabi (Arabian Gulf) and Fujairah (Sea of Oman) where unique water quality data were collected. Based on the in situ water spectral analysis, the bottom reflectance (water depth<20m) are found to degrade the performance of the conventional ocean color algorithms more than the sediment-laden waters where these waters increase the R rs at the blue and red ranges. The increasing presence of CDOM markedly decreases the R rs in the blue range, which is conflicting with the effect of Chl-a. Given the inadequate performance of the widely used ocean-color algorithms (OC3: ocean color 3, OC2: ocean color 2) in retrieving Chl-a in these very shallow coastal waters, therefore, a new algorithm is proposed here based on a 3-bands ratio approach using [R rs (656) -1 -R rs (506) -1 ]×R rs (661). The selected optimum bands (656nm, 506nm, and 661nm) from this approach can be used to retrieve the Chl-a more accurately in these coastal Case II (turbid) waters which are close to the bands of the current missions such as Sentinel-3 OLCI (Ocean and Land Colour Instrument), MODIS, VIIRS (Visible Infrared Imaging Radiometer Suite) and LandSat 8. However, more uniformly distributed data over the Arabian Gulf is required to have a highly accurate regional model for Chl-a retrieval. Copyright © 2017 Elsevier B.V. All rights reserved.

OCTS and SeaWiFS Bio-Optical Algorithm and Product Validation and Intercomparison in US Coastal Waters. Chapter 5

NASA Technical Reports Server (NTRS)

Brown, Christopher W.; Subramaniam, Ajit; Culver, Mary; Brock, John C.

2001-01-01

Monitoring the health of US coastal waters is an important goal of the National Oceanic and Atmospheric Administration (NOAA). Satellite sensors are capable of providing daily synoptic data of large expanses of the US coast. Ocean color sensors, in particular, can be used to monitor the water quality of coastal waters on an operational basis. To appraise the validity of satellite-derived measurements, such as chlorophyll concentration, the bio-optical algorithms used to derive them must be evaluated in coastal environments. Towards this purpose, over 21 cruises in diverse US coastal waters have been conducted. Of these 21 cruises, 12 have been performed in conjunction with and under the auspices of the NASA/Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project. The primary goal of these cruises has been to obtain in-situ measurements of downwelling irradiance, upwelling radiance, and chlorophyll concentrations in order to evaluate bio-optical algorithms that estimate chlorophyll concentration. In this Technical Memorandum, we evaluate the ability of five bio-optical algorithms, including the current Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) algorithm, to estimate chlorophyll concentration in surface waters of the South Atlantic Bight (SAB). The SAB consists of a variety of environments including coastal and continental shelf regimes, Gulf Stream waters, and the Sargasso Sea. The biological and optical characteristics of the region is complicated by temporal and spatial variability in phytoplankton composition, primary productivity, and the concentrations of colored dissolved organic matter (CDOM) and suspended sediment. As such, the SAB is an ideal location to test the robustness of algorithms for coastal use.

The Sensitivity of SeaWiFS Ocean Color Retrievals to Aerosol Amount and Type

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.; Sayer, Andrew M.; Ahmad, Ziauddin; Franz, Bryan A.

2016-01-01

As atmospheric reflectance dominates top-of-the-atmosphere radiance over ocean, atmospheric correction is a critical component of ocean color retrievals. This paper explores the operational Sea-viewing Wide Field-of-View Sensor (SeaWiFS) algorithm atmospheric correction with approximately 13 000 coincident surface-based aerosol measurements. Aerosol optical depth at 440 nm (AOD(sub 440)) is overestimated for AOD below approximately 0.1-0.15 and is increasingly underestimated at higher AOD; also, single-scattering albedo (SSA) appears overestimated when the actual value less than approximately 0.96.AOD(sub 440) and its spectral slope tend to be overestimated preferentially for coarse-mode particles. Sensitivity analysis shows that changes in these factors lead to systematic differences in derived ocean water-leaving reflectance (Rrs) at 440 nm. The standard SeaWiFS algorithm compensates for AOD anomalies in the presence of nonabsorbing, medium-size-dominated aerosols. However, at low AOD and with absorbing aerosols, in situ observations and previous case studies demonstrate that retrieved Rrs is sensitive to spectral AOD and possibly also SSA anomalies. Stratifying the dataset by aerosol-type proxies shows the dependence of the AOD anomaly and resulting Rrs patterns on aerosol type, though the correlation with the SSA anomaly is too subtle to be quantified with these data. Retrieved chlorophyll-a concentrations (Chl) are affected in a complex way by Rrs differences, and these effects occur preferentially at high and low Chl values. Absorbing aerosol effects are likely to be most important over biologically productive waters near coasts and along major aerosol transport pathways. These results suggest that future ocean color spacecraft missions aiming to cover the range of naturally occurring and anthropogenic aerosols, especially at wavelengths shorter than 440 nm, will require better aerosol amount and type constraints.

The interaction of light with phytoplankton in the marine environment

NASA Technical Reports Server (NTRS)

Carder, Kendall L.; Collins, Donald J.; Perry, Mary Jane; Clark, H. Lawrence; Mesias, Jorge M.

1986-01-01

In many regions of the ocean, the phytoplankton population dominates both the attenuation and scattering of light. In other regions, non-phytoplankton contributions to the absorption and scattering may change the remote sensing reflectance and thus affect the ability to interpret remotely sensed ocean color. Hence, variations in the composition of both the phytoplankton population and of the non-phytoplankton material in the water can affect the optical properties of the sea. The effects of these contributions to the remote sensing reflectance and the submarine light field are modeled using scattering and absorption measurements of phytoplankton cultures obtained at the Friday Harbor Laboratory of the University of Washington. These measurements are used to develop regional chlorophyll algorithms specific to the summer waters of Puget Sound for the Coastal Zone Color Scanner, Thematic Mapper and future Ocean Color Imager, and their accuracies are compared for high chlorophyll waters with little or no Gelbstoff, but with variable detrital and suspended material.

Validation of MERIS Ocean Color Algorithms in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Marullo, S.; D'Ortenzio, F.; Ribera D'Alcalà, M.; Ragni, M.; Santoleri, R.; Vellucci, V.; Luttazzi, C.

2004-05-01

Satellite ocean color measurements can contribute, better than any other source of data, to quantify the spatial and time variability of ocean productivity and, tanks to the success of several satellite missions starting with CZCS up to SeaWiFS, MODIS and MERIS, it is now possible to start doing the investigation of interannual variations and compare level of production during different decades ([1],[2]). The interannual variability of the ocean productivity at global and regional scale can be correctly measured providing that chlorophyll estimate are based on well calibrated algorithms in order to avoid regional biases and instrumental time shifts. The calibration and validation of Ocean Color data is then one of the most important tasks of several research projects worldwide ([3], [4]). Algorithms developed to retrieve chlorophyll concentration need a specific effort to define the error ranges associated to the estimates. In particular, the empirical algorithms, calculated on regression with in situ data, require independent records to verify the degree of uncertainties associated. In addition several evidences demonstrated that regional algorithms can improve the accuracy of the satellite chlorophyll estimates [5]. In 2002, Santoleri et al. (SIMBIOS) first showed a significant overestimation of the SeaWiFS derived chlorophyll concentration in Mediterranean Sea when the standard global NASA algorithms (OC4v2 and OC4v4) are used. The same authors [6] proposed two preliminary new algorithms for the Mediterranean Sea (L-DORMA and NL-DORMA) on a basis of a bio-optical data set collected in the basin from 1998 to 2000. In 2002 Bricaud et al., [7] analyzing other bio-optical data collected in the Mediterranean, confirmed the overestimation of the chlorophyll concentration in oligotrophic conditions and proposed a new regional algorithm to be used in case of low concentrations. Recently, the number of in situ observations in the basin was increased, permitting a first evaluation of the DORMA algorithms with data not used for the algorithms empirical coefficient retrieval and an extensive validation of the new MERIS algorithm. Up to now two possible explanations of the fact that the oligotrophic waters of the Mediterranean Sea are greener than would result from their phytoplankton content alone have been proposed. Claustre et al. [8] suggested that the observed distortion effect on the blue to green ratio can be due to the presence of Saharan dust in the upper layers that enhance absorption in the blue and backscattering in the green. DOR2002 also proposed a tentative explanation of the observed distortion effect based on the hypothesis that enhanced CaCO3 concentration, due to relative abundance of coccolithophores in the oligotrophic waters of the Mediterranean Sea, can cause similar results. In this note, we show a first analysis of the performances of two regional Mediterranean OC algorithms based on SeaWiFS bands (the NL-DORMA and Bricaud et al. 2002 algorithms), the standard OC4v4 NASA algorithm and the MERIS algorithm currently used to produce chlorophyll maps for case I waters. Finally we revisit the Claustre et al. (2002) and DOR2002 hypothesis in the light of new measurements recently published by Malinverno et al. [9] and the results of the ADIOS project of EC.

Intersatellite comparisons and evaluations of three ocean color products along the Zhejiang coast, eastern China

NASA Astrophysics Data System (ADS)

Cui, Qiyuan; Wang, Difeng; Gong, Fang; Pan, Delu; Hao, Zengzhou; Wang, Tianyu; Zhu, Qiankun

2017-10-01

With its broad spatial coverage and fine temporal resolution, ocean color remote sensing data represents an effective tool for monitoring large areas of ocean, and has the potential to provide crucial information in coastal waters where routine monitoring is either lacking or unsatisfactory. The semi-analytical or empirical algorithms that work well in Case 1 waters encounter many problems in offshore areas where the water is often optically complex and presents difficulties for atmospheric correction. Zhejiang is one of the most developed provinces in eastern China, and its adjacent seas have been greatly affected by recent rapid economic development. Various islands and semi-closed bays along the Zhejiang coast promote the formation of muddy tidal flats. Moreover, large quantities of terrestrial substances coming down with the Yangtze River and other local rivers also have a great impact on the coastal waters of the province. MODIS, VIIRS and GOCI are three commonly used ocean color sensors covering the East China Sea. Several ocean color products such as remote-sensing reflectance (Rrs) and the concentrations of chlorophyll a (Chl-a) and total suspended matter (TSM) of the above three sensors on the Zhejiang coast have been evaluated. Cloud-free satellite images with synchronous field measurements taken between 2012 and 2015 were used for comparison. It is shown that there is a good correlation between the MODIS and GOCI spectral data, while some outliers were found in the VIIRS images. The low signal-to-noise ratio at short wavelengths in highly turbid waters also reduced the correlation between different sensors. In addition, it was possible to obtain more valid data with GOCI in shallow waters because of the use of an appropriate atmospheric correction algorithm. The standard Chl-a and TSM products of the three satellites were also evaluated, and it was found that the Chl-a and TSM concentrations calculated by the OC3G and Case 2 algorithms, respectively, were more suitable for use in the study area. Moreover, GOCI has been proved to be effective for monitoring the diurnal dynamics in coastal waters, and the concentration of TSM had a good negative correlation with water level. Overall, compared with MODIS and VIIRS, GOCI is more effective for monitoring the fine changes and diurnal dynamics in the seas adjacent to Zhejiang Province.

Simultaneous aerosol/ocean products retrieved during the 2014 SABOR campaign using the NASA Research Scanning Polarimeter (RSP)

NASA Astrophysics Data System (ADS)

Stamnes, S.; Hostetler, C. A.; Ferrare, R. A.; Hair, J. W.; Burton, S. P.; Liu, X.; Hu, Y.; Stamnes, K. H.; Chowdhary, J.; Brian, C.

2017-12-01

The SABOR (Ship-Aircraft Bio-Optical Research) campaign was conducted during the summer of 2014, in the Atlantic Ocean, over the Chesapeake Bay and the eastern coastal region of the United States. The NASA GISS Research Scanning Polarimeter, a multi-angle, multi-spectral polarimeter measured the upwelling polarized radiances from a B200 aircraft. We present results from the new "MAPP" algorithm for RSP that is based on optimal estimation and that can retrieve simultaneous aerosol microphysical properties (including effective radius, single-scattering albedo, and real refractive index) and ocean color products using accurate radiative transfer and Mie calculations. The algorithm was applied to data collected during SABOR to retrieve aerosol microphysics and ocean products for all Aerosols-Above-Ocean (AAO) scenes. The RSP MAPP products are compared against collocated aerosol extinction and backscatter profiles collected by the NASA LaRC airborne High Spectral Resolution Lidar (HSRL-1), including lidar depth profiles of the ocean diffuse attenuation coefficient and the hemispherical backscatter coefficient.

Optical Measurements and Modeling to Estimate Concentrations and Fluxes of Organic Matter in the Southern Ocean

NASA Technical Reports Server (NTRS)

Stramski, Dariusz; Mitchell, B. Greg; Marra, John W. (Technical Monitor)

2001-01-01

This project was a collaboration between two Principal Investigators, Dr. Dariusz Stramski and Dr. Greg Mitchell of Scripps Institution of Oceanography, University of California San Diego. Our overall goal was to conduct optical measurements and modeling to estimate concentrations of organic matter in the Southern Ocean in support of the U.S. JGOFS Process Study in this region. Key variables and processes of high relevance to accomplish the JGOFS goals include time and space resolution of phytoplankton pigments, particulate organic carbon, and the formation and export of organic carbon. Our project focused on establishing the fundamental relationships for parameterization of these variables and processes in terms of the optical properties of seawater, and developing understanding of why the Southern Ocean differs from other low-latitude systems, or has differentiation within. Our approach builds upon historical observations that optical properties provide a useful proxy for key reservoirs of organic matter such as chlorophyll alpha (Chl) and particulate organic carbon (POC) concentrations, which are of relevance to the JGOFS objectives. We carried out detailed studies of in situ and water sample optical properties including spectral reflectance, absorption, beam attenuation, scattering, and backscattering coefficients. We evaluated the ability to estimate Chl from the spectral reflectance (ocean color) in the Southern Ocean. We examined relationships between the ocean optical properties and particulate organic carbon. We developed, for the first time, an algorithm for estimating particulate organic carbon concentration in the surface ocean from satellite imagery of ocean color. With this algorithm, we obtained maps of POC distribution in the Southern Ocean showing the seasonal progression of POC in the austral spring-summer season. We also developed a semianalytical reflectance model for the investigated polar waters based on our field measurements of absorption and backscattering coefficients and Chl-dependent parameterizations of these coefficients. With this model, libraries of expected reflectance spectra for various chlorophyll concentrations can be generated with high spectral resolution for specific oceanic regions. In addition, our semianalytical reflectance model provided insight into the mechanisms which drive the empirical relationships between the ocean color and chlorophyll concentration. Our optical approach to the study of pigment and carbon concentrations will be directly relevant to development of system models and long-term monitoring of the Southern Ocean.

SeaWiFS technical report series. Volume 1: An overview of SeaWiFS and ocean color

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Esaias, Wayne E.; Feldman, Gene C.; Gregg, Watson W.; Mcclain, Charles R.

1992-01-01

The purpose of this series of technical reports is to provide current documentation of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project activities, instrument performance, algorithms, and operations. This documentation is necessary to ensure that critical information related to the quality and calibration of the satellite data is available to the scientific community. SeaWiFS will bring to the ocean community a welcomed and improved renewal of the ocean color remote sensing capability lost when the Nimbus-7 Coastal Zone Color Scanner (CZCS) ceased operating in 1986. The goal of SeaWiFS, scheduled to be launched in August 1993, is to examine oceanic factors that affect global change. Because of the role of phytoplankton in the global carbon cycle, data obtained from SeaWiFS will be used to assess the ocean's role in this cycle, as well as other biogeochemical cycles. SeaWiFS data will be used to help elucidate the magnitude and variability of the annual cycle of primary production by marine phytoplankton and to determine the distribution and timing of spring blooms. The observations will help to visualize the dynamics of ocean and costal currents, the physics of mixing, and the relationships between ocean physics and large-scale patterns of productivity. The data will help fill the gap in ocean biological observations between those of the CZCS and the upcoming Moderate Resolution Imaging Spectrometer (MODIS) on the Earth Observing System-A (EOS-A) satellite.

Ocean Primary Production Estimates from Terra MODIS and Their Dependency on Satellite Chlorophyll Alpha Algorithms

NASA Technical Reports Server (NTRS)

Essias, Wayne E.; Abbott, Mark; Carder, Kendall; Campbell, Janet; Clark, Dennis; Evans, Robert; Brown, Otis; Kearns, Ed; Kilpatrick, Kay; Balch, W.

2003-01-01

Simplistic models relating global satellite ocean color, temperature, and light to ocean net primary production (ONPP) are sensitive to the accuracy and limitations of the satellite estimate of chlorophyll and other input fields, as well as the primary productivity model. The standard MODIS ONPP product uses the new semi-analytic chlorophyll algorithm as its input for two ONPP indexes. The three primary MODIS chlorophyll Q estimates from MODIS, as well as the SeaWiFS 4 chlorophyll product, were used to assess global and regional performance in estimating ONPP for the full mission, but concentrating on 2001. The two standard ONPP algorithms were examined with 8-day and 39 kilometer resolution to quantify chlorophyll algorithm dependency of ONPP. Ancillary data (MLD from FNMOC, MODIS SSTD1, and PAR from the GSFC DAO) were identical. The standard MODIS ONPP estimates for annual production in 2001 was 59 and 58 GT C for the two ONPP algorithms. Differences in ONPP using alternate chlorophylls were on the order of 10% for global annual ONPP, but ranged to 100% regionally. On all scales the differences in ONPP were smaller between MODIS and SeaWiFS than between ONPP models, or among chlorophyll algorithms within MODIS. Largest regional ONPP differences were found in the Southern Ocean (SO). In the SO, application of the semi-analytic chlorophyll resulted in not only a magnitude difference in ONPP (2x), but also a temporal shift in the time of maximum production compared to empirical algorithms when summed over standard oceanic areas. The resulting increase in global ONPP (6-7 GT) is supported by better performance of the semi-analytic chlorophyll in the SO and other high chlorophyll regions. The differences are significant in terms of understanding regional differences and dynamics of ocean carbon transformations.

Simultaneous Measurements of Chlorophyll Concentration by Lidar, Fluorometry, above-Water Radiometry, and Ocean Color MODIS Images in the Southwestern Atlantic.

PubMed

Kampel, Milton; Lorenzzetti, João A; Bentz, Cristina M; Nunes, Raul A; Paranhos, Rodolfo; Rudorff, Frederico M; Politano, Alexandre T

2009-01-01

Comparisons between in situ measurements of surface chlorophyll-a concentration (CHL) and ocean color remote sensing estimates were conducted during an oceanographic cruise on the Brazilian Southeastern continental shelf and slope, Southwestern South Atlantic. In situ values were based on fluorometry, above-water radiometry and lidar fluorosensor. Three empirical algorithms were used to estimate CHL from radiometric measurements: Ocean Chlorophyll 3 bands (OC3M(RAD)), Ocean Chlorophyll 4 bands (OC4v4(RAD)), and Ocean Chlorophyll 2 bands (OC2v4(RAD)). The satellite estimates of CHL were derived from data collected by the MODerate-resolution Imaging Spectroradiometer (MODIS) with a nominal 1.1 km resolution at nadir. Three algorithms were used to estimate chlorophyll concentrations from MODIS data: one empirical - OC3M(SAT), and two semi-analytical - Garver, Siegel, Maritorena version 01 (GSM01(SAT)), and Carder(SAT). In the present work, MODIS, lidar and in situ above-water radiometry and fluorometry are briefly described and the estimated values of chlorophyll retrieved by these techniques are compared. The chlorophyll concentration in the study area was in the range 0.01 to 0.2 mg/m(3). In general, the empirical algorithms applied to the in situ radiometric and satellite data showed a tendency to overestimate CHL with a mean difference between estimated and measured values of as much as 0.17 mg/m(3) (OC2v4(RAD)). The semi-analytical GSM01 algorithm applied to MODIS data performed better (rmse 0.28, rmse-L 0.08, mean diff. -0.01 mg/m(3)) than the Carder and the empirical OC3M algorithms (rmse 1.14 and 0.36, rmse-L 0.34 and 0.11, mean diff. 0.17 and 0.02 mg/m(3), respectively). We find that rmsd values between MODIS relative to the in situ radiometric measurements are < 26%, i.e., there is a trend towards overestimation of R(RS) by MODIS for the stations considered in this work. Other authors have already reported over and under estimation of MODIS remotely sensed reflectance due to several errors in the bio-optical algorithm performance, in the satellite sensor calibration, and in the atmospheric-correction algorithm.

Assessment of remotely sensed chlorophyll-a concentration in Guanabara Bay, Brazil

NASA Astrophysics Data System (ADS)

Oliveira, Eduardo N.; Fernandes, Alexandre M.; Kampel, Milton; Cordeiro, Renato C.; Brandini, Nilva; Vinzon, Susana B.; Grassi, Renata M.; Pinto, Fernando N.; Fillipo, Alessandro M.; Paranhos, Rodolfo

2016-04-01

The Guanabara Bay (GB) is an estuarine system in the metropolitan region of Rio de Janeiro (Brazil), with a surface area of ˜346 km2 threatened by anthropogenic pressure. Remote sensing can provide frequent data for studies and monitoring of water quality parameters, such as chlorophyll-a concentration (Chl-a). Different combination of Medium Resolution Imaging Spectrometer (MERIS) remote sensing reflectance band ratios were used to estimate Chl-a. Standard algorithms such as Ocean Color 3-band, Ocean Color-4 band, fluorescence line height, and maximum chlorophyll index were also tested. The MERIS Chl-a estimates were statistically compared with a dataset of in situ Chl-a (2002 to 2012). Good correlations were obtained with the use of green, red, and near-infrared bands. The best performing algorithm was based on the red (665 nm) and green (560 nm) band ratio, named "RG3" algorithm (r2=0.71, chl-a=62,565*x1.6118). The RG3 was applied to a time series of MERIS images (2003- to 2012). The GB has a high temporal and spatial variability of Chl-a, with highest values found in the wet season (October to March) and in some of the most internal regions of the estuary. Lowest concentrations are found in the central circulation channel due to the flushing of ocean water masses promoted by pumping tide.

Atmospheric correction of SeaWiFS ocean color imagery in the presence of absorbing aerosols off the Indian coast using a neuro-variational method

NASA Astrophysics Data System (ADS)

Brajard, J.; Moulin, C.; Thiria, S.

2008-10-01

This paper presents a comparison of the atmospheric correction accuracy between the standard sea-viewing wide field-of-view sensor (SeaWiFS) algorithm and the NeuroVaria algorithm for the ocean off the Indian coast in March 1999. NeuroVaria is a general method developed to retrieve aerosol optical properties and water-leaving reflectances for all types of aerosols, including absorbing ones. It has been applied to SeaWiFS images of March 1999, during an episode of transport of absorbing aerosols coming from pollutant sources in India. Water-leaving reflectances and aerosol optical thickness estimated by the two methods were extracted along a transect across the aerosol plume for three days. The comparison showed that NeuroVaria allows the retrieval of oceanic properties in the presence of absorbing aerosols with a better spatial and temporal stability than the standard SeaWiFS algorithm. NeuroVaria was then applied to the available SeaWiFS images over a two-week period. NeuroVaria algorithm retrieves ocean products for a larger number of pixels than the standard one and eliminates most of the discontinuities and artifacts associated with the standard algorithm in presence of absorbing aerosols.

Application of in situ observations, high frequency radars, and ocean color, to study suspended matter, particulate carbon, and dissolved organic carbon fluxes in coastal waters of the Barents Sea - the NORDFLUX project

NASA Astrophysics Data System (ADS)

Stramska, Malgorzata; Yngve Børsheim, Knut; Białogrodzka, Jagoda; Cieszyńska, Agata; Ficek, Dariusz; Wereszka, Marzena

2016-04-01

There is still a limited knowledge about suspended and dissolved matter fluxes transported from coastal regions into the open sea regions in the Arctic. The land/sea interface is environmentally important and sensitive to climate change. Important biogeochemical material entering the oceans (including carbon) passes through this interface, but too little is known about the efficiency of this transport. Our goal in the NORDFLUX program is to improve quantitative understanding of the environmental feedbacks involved in these processes through an interdisciplinary study with innovative in situ observations. Completed work includes two in situ experiments in the Norwegian fiord (Porsangerfjorden) in the summers of 2014 and 2015. Experiments used research boat for collection of water samples and in situ bio-optical data, an autonomous glider, mooring with T S sensors, and a high frequency radar system. We have used these data to derive spatial maps of water temperature, salinity, surface currents, chlorophyll fluorescence, dissolved organic matter (DOM) fluorescence, and inherent optical properties (IOPs) of the water. The interpretation of these data in terms of suspended matter concentration and composition is possible by in situ 'calibrations' using water samples from discrete hydrographic stations. Total suspended matter (TSM), particulate carbon (POC and PIC), and dissolved organic carbon (DOC) concentrations together with measured water currents will allow us to estimate reservoirs and fluxes. Concentrations and fluxes will be related to physical conditions and meteorological data. An important aspect of this project is the work on regional ocean color algorithms. Global ocean color (OC) algorithms currently used by NASA do not perform sufficiently well in coastal Case 2 waters. Our data sets will allow us to derive such local algorithms. We will then use these algorithms for interpretation of OC data in terms of TSM concentrations and composition and DOC. After deriving these algorithms, we will analyze historical satellite imagery to assess multiyear trends in concentrations of various water components. This work is still in progress, specific and more detailed results are presented as posters during this meeting. This work was funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support for MS comes from the Institute of Oceanology (IO PAN).

Satellite Ocean-Color Validation Using Ships of Opportunity. Chapter 5

NASA Technical Reports Server (NTRS)

Frouin, Robert; Cutchin, David L.; Gross-Colzy, Lydwine; Poteau, Antoine; Deschamps, Pierre-Yves

2003-01-01

The investigation s main objective is to collect from platforms of opportunity (merchant ships, research vessels) concomitant normalized water-leaving radiance and aerosol optical thickness data over the world s oceans. A global, long-term data set of these variables is needed to verify whether satellite retrievals of normalized water-leaving radiance are within acceptable error limits and, eventually, to adjust atmospheric correction schemes. To achieve this objective, volunteer officers, technicians, and scientists onboard the selected ships collect data from portable SIMBAD and Advanced SIMBAD (SIMBADA) radiometers. These instruments are specifically designed for evaluation of satellite-derived ocean color. They measure radiance in spectral bands typical of ocean-color sensors. The SIMBAD version measures in 5 spectral bands centered at 443, 490, 560, 670, and 870 nm, and the Advanced SIMBAD version in 11 spectral bands centered at 350, 380, 412, 443, 490, 510, 565, 620, 670, 750, and 870 nm. Aerosol optical thickness is obtained by viewing the sun disk like a classic sun photometer. Normalized water-leaving radiance, or marine reflectance, is obtained by viewing the ocean surface through a vertical polarizer in a specific geometry (nadir angle of 45o and relative azimuth angle of 135deg) to minimize direct sun glint and reflected sky radiation. The SIMBAD and SIMBADA data, after proper quality control and processing, are delivered to the SIMBIOS project office for inclusion in the SeaBASS archive. They complement data collected in a similar way by the Laboratoire d'Optique Atmospherique of the University of Lille, France. The SIMBAD and SIMBADA data are used to check the radiometric calibration of satellite ocean-color sensors after launch and to evaluate derived ocean-color variables (i.e., normalized water-leaving radiance, aerosol optical thickness, and aerosol type). Analysis of the SIMBAD and SIMBADA data provides information on the accuracy of satellite retrievals of normalized water-leaving radiance, an understanding of the discrepancies between satellite and in situ data, and algorithms that reduce the discrepancies, contributing to more accurate and consistent global ocean color data sets.

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

NASA Technical Reports Server (NTRS)

Mannino, Antonio

2008-01-01

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Identifying Rhodamine Dye Plume Sources in Near-Shore Oceanic Environments by Integration of Chemical and Visual Sensors

PubMed Central

Tian, Yu; Kang, Xiaodong; Li, Yunyi; Li, Wei; Zhang, Aiqun; Yu, Jiangchen; Li, Yiping

2013-01-01

This article presents a strategy for identifying the source location of a chemical plume in near-shore oceanic environments where the plume is developed under the influence of turbulence, tides and waves. This strategy includes two modules: source declaration (or identification) and source verification embedded in a subsumption architecture. Algorithms for source identification are derived from the moth-inspired plume tracing strategies based on a chemical sensor. The in-water test missions, conducted in November 2002 at San Clemente Island (California, USA) in June 2003 in Duck (North Carolina, USA) and in October 2010 at Dalian Bay (China), successfully identified the source locations after autonomous underwater vehicles tracked the rhodamine dye plumes with a significant meander over 100 meters. The objective of the verification module is to verify the declared plume source using a visual sensor. Because images taken in near shore oceanic environments are very vague and colors in the images are not well-defined, we adopt a fuzzy color extractor to segment the color components and recognize the chemical plume and its source by measuring color similarity. The source verification module is tested by images taken during the CPT missions. PMID:23507823

Neural Network Technique for Global Ocean Color (Chl-a) Estimates Bridging Multiple Satellite Missions

NASA Astrophysics Data System (ADS)

Garraffo, Z. D.; Nadiga, S.; Krasnopolsky, V.; Mehra, A.; Bayler, E. J.; Kim, H. C.; Behringer, D.

2016-02-01

A Neural Network (NN) technique is used to produce consistent global ocean color estimates, bridging multiple satellite ocean color missions by linking ocean color variability - primarily driven by biological processes - with the physical processes of the upper ocean. Satellite-derived surface variables - sea-surface temperature (SST) and sea-surface height (SSH) fields - are used as signatures of upper-ocean dynamics. The NN technique employs adaptive weights that are tuned by applying statistical learning (training) algorithms to past data sets, providing robustness with respect to random noise, accuracy, fast emulations, and fault-tolerance. This study employs Sea-viewing Wide Field-of-View Sensor (SeaWiFS) chlorophyll-a data for 1998-2010 in conjunction with satellite SSH and SST fields. After interpolating all data sets to the same two-degree latitude-longitude grid, the annual mean was removed and monthly anomalies extracted . The NN technique wass trained for even years of that period and tested for errors and bias for the odd years. The NN output are assessed for: (i) bias, (ii) variability, (iii) root-mean-square error (RMSE), and (iv) cross-correlation. A Jacobian is evaluated to estimate the impact of each input (SSH, SST) on the NN chlorophyll-a estimates. The differences between an ensemble of NNs vs a single NN are examined. After the NN is trained for the SeaWiFS period, the NN is then applied and validated for 2005-2015, a period covered by other satellite missions — the Moderate Resolution Imaging Spectroradiometer (MODIS AQUA) and the Visible Imaging Infrared Radiometer Suite (VIIRS).

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Maritorena, S.; Siegel, D. A.; Nelson, N. B.

2004-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. A primary goal is the use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions.

CHLOROPHYLL A DISTRIBUTION IN NARRAGANSETT BAY, RI: USING A SPECTRAL CURVATURE ALGORITHM

EPA Science Inventory

Chlorophyll a, a primary indicator of eutrophication in estuarine waters, varies enough in time and space to create spatial problems when monitored by satellite, and temporal problems when measured with in situ field programs. Using aircraft to sense ocean color of local waters, ...

Adaptation of a Hyperspectral Atmospheric Correction Algorithm for Multi-spectral Ocean Color Data in Coastal Waters. Chapter 3

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Montes, Marcos J.; Davis, Curtiss O.

2003-01-01

This SIMBIOS contract supports several activities over its three-year time-span. These include certain computational aspects of atmospheric correction, including the modification of our hyperspectral atmospheric correction algorithm Tafkaa for various multi-spectral instruments, such as SeaWiFS, MODIS, and GLI. Additionally, since absorbing aerosols are becoming common in many coastal areas, we are making the model calculations to incorporate various absorbing aerosol models into tables used by our Tafkaa atmospheric correction algorithm. Finally, we have developed the algorithms to use MODIS data to characterize thin cirrus effects on aerosol retrieval.

Remote sensing of the diffuse attenuation coefficient of ocean water. [coastal zone color scanner

NASA Technical Reports Server (NTRS)

Austin, R. W.

1981-01-01

A technique was devised which uses remotely sensed spectral radiances from the sea to assess the optical diffuse attenuation coefficient, K (lambda) of near-surface ocean water. With spectral image data from a sensor such as the coastal zone color scanner (CZCS) carried on NIMBUS-7, it is possible to rapidly compute the K (lambda) fields for large ocean areas and obtain K "images" which show synoptic, spatial distribution of this attenuation coefficient. The technique utilizes a relationship that has been determined between the value of K and the ratio of the upwelling radiances leaving the sea surface at two wavelengths. The relationship was developed to provide an algorithm for inferring K from the radiance images obtained by the CZCS, thus the wavelengths were selected from those used by this sensor, viz., 443, 520, 550 and 670 nm. The majority of the radiance arriving at the spacecraft is the result of scattering in the atmospheric and is unrelated to the radiance signal generated by the water. A necessary step in the processing of the data received by the sensor is, therefore, the effective removal of these atmospheric path radiance signals before the K algorithm is applied. Examples of the efficacy of these removal techniques are given together with examples of the spatial distributions of K in several ocean areas.

Specificity of Atmospheric Correction of Satellite Data on Ocean Color in the Far East

NASA Astrophysics Data System (ADS)

Aleksanin, A. I.; Kachur, V. A.

2017-12-01

Calculation errors in ocean-brightness coefficients in the Far Eastern are analyzed for two atmospheric correction algorithms (NIR and MUMM). The daylight measurements in different water types show that the main error component is systematic and has a simple dependence on the magnitudes of the coefficients. The causes of the error behavior are considered. The most probable explanation for the large errors in ocean-color parameters in the Far East is a high concentration of continental aerosol absorbing light. A comparison between satellite and in situ measurements at AERONET stations in the United States and South Korea has been made. It is shown the errors in these two regions differ by up to 10 times upon close water turbidity and relatively high aerosol optical-depth computation precision in the case of using the NIR correction of the atmospheric effect.

Spectral variability of sea surface skylight reflectance and its effect on ocean color.

PubMed

Cui, Ting-Wei; Song, Qing-Jun; Tang, Jun-Wu; Zhang, Jie

2013-10-21

In this study, sea surface skylight spectral reflectance ρ(λ) was retrieved by means of the non-linear spectral optimization method and a bio-optical model. The spectral variability of ρ(λ) was found to be mainly influenced by the uniformity of the incident skylight, and a model is proposed to predict the ρ(λ) spectral dependency based on skylight reflectance at 750 nm. It is demonstrated that using the spectrally variable ρ(λ), rather than a constant, yields an improved agreement between the above-water remote sensing reflectance R(rs)(λ) estimates and concurrent profiling ones. The findings of this study highlight the necessity to re-process the relevant historical above-water data and update ocean color retrieval algorithms accordingly.

BIO-OPTICAL CHARACTERIZATION OF THE DINOFLAGELLATE GYMNODINIUM BREVE AND THE DIATOM THALASSIOSIRA WEISSFLOGII IN OUTDOOR TANKS

EPA Science Inventory

The bio-optical signatures of harmful algal blooms can be used to define ocean color satellite algorithms. We characterized the bio-optical properties of nutrient-replete cultures of the red tide dinoflagellate Gymnodinium breve and the diatom Thalassiosira weissflogii. We cultur...

Uncertainties of Optical Parameters and Their Propagations in an Analytical Ocean Color Inversion Algorithm

DTIC Science & Technology

2010-01-20

34’/ Office of Counsel,Code 1008.3 .( 41 «, • ADOR/Director NCST E. R. Franchi , 7000 Public Affairs (Unclassified/ Unlimited Only), Code 703o...satellite remote sensors are indispensable. To meet this requirement, systematic observations of the biogeochemical prop- erties of global oceans through...average a(550)qAA of each group) for the various a(550) groups. For O(550)QAA < 0.1 m" 1, which covers ~95% of global waters (Bryan Franz, personal com

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance

PubMed Central

Zeng, Chen; Xu, Huiping; Fischer, Andrew M.

2016-01-01

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy. PMID:27941596

Chlorophyll-a Estimation Around the Antarctica Peninsula Using Satellite Algorithms: Hints from Field Water Leaving Reflectance.

PubMed

Zeng, Chen; Xu, Huiping; Fischer, Andrew M

2016-12-07

Ocean color remote sensing significantly contributes to our understanding of phytoplankton distribution and abundance and primary productivity in the Southern Ocean (SO). However, the current SO in situ optical database is still insufficient and unevenly distributed. This limits the ability to produce robust and accurate measurements of satellite-based chlorophyll. Based on data collected on cruises around the Antarctica Peninsula (AP) on January 2014 and 2016, this research intends to enhance our knowledge of SO water and atmospheric optical characteristics and address satellite algorithm deficiency of ocean color products. We collected high resolution in situ water leaving reflectance (±1 nm band resolution), simultaneous in situ chlorophyll-a concentrations and satellite (MODIS and VIIRS) water leaving reflectance. Field samples show that clouds have a great impact on the visible green bands and are difficult to detect because NASA protocols apply the NIR band as a cloud contamination threshold. When compared to global case I water, water around the AP has lower water leaving reflectance and a narrower blue-green band ratio, which explains chlorophyll-a underestimation in high chlorophyll-a regions and overestimation in low chlorophyll-a regions. VIIRS shows higher spatial coverage and detection accuracy than MODIS. After coefficient improvement, VIIRS is able to predict chlorophyll a with 53% accuracy.

OCTS And Seawifs Bio-Optical Algorithm and Product Vaildattion and Intercomparison in US Coastal Waters

NASA Technical Reports Server (NTRS)

Brow, Chirstopher; Subramaniam, Ajit; Culver, Mary; Brock, John C.

2000-01-01

Monitoring the health of U.S. coastal waters is an important goal of the National Oceanic and Atmospheric Administration (NOAA). Satellite sensors are capable of providing daily synoptic data of large expanses of the U.S. coast. Ocean color sensor, in particular, can be used to monitor the water quality of coastal waters on an operational basis. To appraise the validity of satellite-derived measurements, such as chlorophyll concentration, the bio-optical algorithms used to derive them must be evaluated in coastal environments. Towards this purpose, over 21 cruises in diverse U.S. coastal waters have been conducted. Of these 21 cruises, 12 have been performed in conjunction with and under the auspices of the NASA/SIMBIOS Project. The primary goal of these cruises has been to obtain in-situ measurements of downwelling irradiance, upwelling radiance, and chlorophyll concentrations in order to evaluate bio-optical algorithms that estimate chlorophyll concentration. In this Technical Memorandum, we evaluate the ability of five bio-optical algorithms, including the current SeaWiFS algorithm, to estimate chlorophyll concentration in surface waters of the South Atlantic Bight (SAB). The SAB consists of a variety of environments including coastal and continental shelf regimes, Gulf Stream waters, and the Sargasso Sea. The biological and optical characteristics of the region is complicated by temporal and spatial variability in phytoplankton composition, primary productivity, and the concentrations of colored dissolved organic matter (CDOM) and suspended sediment. As such, the SAB is an ideal location to test the robustness of algorithms for coastal use.

An overview of remote sensing of chlorophyll fluorescence

NASA Astrophysics Data System (ADS)

Xing, Xiao-Gang; Zhao, Dong-Zhi; Liu, Yu-Guang; Yang, Jian-Hong; Xiu, Peng; Wang, Lin

2007-03-01

Besides empirical algorithms with the blue-green ratio, the algorithms based on fluorescence are also important and valid methods for retrieving chlorophyll-a concentration in the ocean waters, especially for Case II waters and the sea with algal blooming. This study reviews the history of initial cognitions, investigations and detailed approaches towards chlorophyll fluorescence, and then introduces the biological mechanism of fluorescence remote sensing and main spectral characteristics such as the positive correlation between fluorescence and chlorophyll concentration, the red shift phenomena. Meanwhile, there exist many influence factors that increase complexity of fluorescence remote sensing, such as fluorescence quantum yield, physiological status of various algae, substances with related optical property in the ocean, atmospheric absorption etc. Based on these cognitions, scientists have found two ways to calculate the amount of fluorescence detected by ocean color sensors: fluorescence line height and reflectance ratio. These two ways are currently the foundation for retrieval of chlorophyl l - a concentration in the ocean. As the in-situ measurements and synchronous satellite data are continuously being accumulated, the fluorescence remote sensing of chlorophyll-a concentration in Case II waters should be recognized more thoroughly and new algorithms could be expected.

Seasonal estimates of DOC standing stocks in Apalachicola Bay estuary: Towards a better understanding using field, ocean color and model data

NASA Astrophysics Data System (ADS)

D'Sa, E. J.; Joshi, I.; Osburn, C. L.; Bianchi, T. S.; Ko, D. S.; Oviedo-Vargas, D.; Arellano, A.; Ward, N.

2016-12-01

Apalachicola Bay, a semi-enclosed estuary located in Florida's panhandle, is well known for its water quality and oyster yields. We present the use of combined field and ocean color satellite observations and the outputs of a high-resolution hydrodynamic model to study the influence of physical processes on the distribution and the transport of terrestrially derived CDOM and DOC to shelf waters during the spring and fall of 2015. Determination of DOC stocks were based on the development of a CDOM algorithm (R2 = 0.87, N = 9) for the VIIRS ocean color sensor, and the assessment of CDOM - DOC relationships (R2 = 0.88, N = 13 in March; R2 = 0.83, N = 24 in November) for the Apalachicola Bay. Satellite-derived CDOM and DOC maps together with model-based salinity distributions revealed their spatial extent, sources and transport to the shelf water. Furthermore, strong seasonal influence on DOM distribution in the bay was associated with inputs from Apalachicola and Carrabelle Rivers and the surrounding marshes. Estimates of DOC standing stocks in the bay obtained using ocean color data and high-resolution bathymetry showed relatively higher stocks in November ( 3.71 × 106 kg C, 560 km2) than in March ( 4.07 × 106 kg C, 560 km2) despite lower river discharge in dry season. Results of DOC flux estimates from the bay to coastal waters will also be presented.

Reflectance model for quantifying chlorophyll a in the presence of productivity degradation products

NASA Technical Reports Server (NTRS)

Carder, K. L.; Hawes, S. K.; Steward, R. G.; Baker, K. A.; Smith, R. C.; Mitchell, B. G.

1991-01-01

A reflectance model developed to estimate chlorophyll a concentrations in the presence of marine colored dissolved organic matter, pheopigments, detritus, and bacteria is presented. Nomograms and lookup tables are generated to describe the effects of different mixtures of chlorophyll a and these degradation products on the R(412):R(443) and R(443):R(565) remote-sensing reflectance or irradiance reflectance ratios. These are used to simulate the accuracy of potential ocean color satellite algorithms, assuming that atmospheric effects have been removed. For the California Current upwelling and offshore regions, with chlorophyll a not greater than 1.3 mg/cu m, the average error for chlorophyll a retrievals derived from irradiance reflectance data for degradation product-rich areas was reduced from +/-61 percent to +/-23 percent by application of an algorithm using two reflectance ratios rather than the commonly used algorithm applying a single reflectance ratio.

Water-leaving contribution to polarized radiation field over ocean.

PubMed

Zhai, Peng-Wang; Knobelspiesse, Kirk; Ibrahim, Amir; Franz, Bryan A; Hu, Yongxiang; Gao, Meng; Frouin, Robert

2017-08-07

The top-of-atmosphere (TOA) radiation field from a coupled atmosphere-ocean system (CAOS) includes contributions from the atmosphere, surface, and water body. Atmospheric correction of ocean color imagery is to retrieve water-leaving radiance from the TOA measurement, from which ocean bio-optical properties can be obtained. Knowledge of the absolute and relative magnitudes of water-leaving signal in the TOA radiation field is important for designing new atmospheric correction algorithms and developing retrieval algorithms for new ocean biogeochemical parameters. In this paper we present a systematic sensitivity study of water-leaving contribution to the TOA radiation field, from 340 nm to 865 nm, with polarization included. Ocean water inherent optical properties are derived from bio-optical models for two kinds of waters, one dominated by phytoplankton (PDW) and the other by non-algae particles (NDW). In addition to elastic scattering, Raman scattering and fluorescence from dissolved organic matter in ocean waters are included. Our sensitivity study shows that the polarized reflectance is minimized for both CAOS and ocean signals in the backscattering half plane, which leads to numerical instability when calculating water leaving relative contribution, the ratio between polarized water leaving and CAOS signals. If the backscattering plane is excluded, the water-leaving polarized signal contributes less than 9% to the TOA polarized reflectance for PDW in the whole spectra. For NDW, the polarized water leaving contribution can be as much as 20% in the wavelength range from 470 to 670 nm. For wavelengths shorter than 452 nm or longer than 865 nm, the water leaving contribution to the TOA polarized reflectance is in general smaller than 5% for NDW. For the TOA total reflectance, the water-leaving contribution has maximum values ranging from 7% to 16% at variable wavelengths from 400 nm to 550 nm from PDW. The water leaving contribution to the TOA total reflectance can be as large as 35% for NDW, which is in general peaked at 550 nm. Both the total and polarized reflectances from water-leaving contributions approach zero in the ultraviolet and near infrared bands. These facts can be used as constraints or guidelines when estimating the water leaving contribution to the TOA reflectance for new atmospheric correction algorithms for ocean color imagery.

Water-Leaving Contribution to Polarized Radiation Field Over Ocean

NASA Technical Reports Server (NTRS)

Zhai, Peng-Wang; Knobelspiesse, Kirk D.; Ibrahim, Amir; Franz, Bryan A.; Hu, Yongxiang; Gao, Meng; Frouin, Robert

2017-01-01

The top-of-atmosphere (TOA) radiation field from a coupled atmosphere-ocean system (CAOS) includes contributions from the atmosphere, surface, and water body. Atmo-spheric correction of ocean color imagery is to retrieve water-leaving radiance from the TOA measurement, from which ocean bio-optical properties can be obtained. Knowledge of the ab-solute and relative magnitudes of water-leaving signal in the TOA radiation field is important for designing new atmospheric correction algorithms and developing retrieval algorithms for new ocean biogeochemical parameters. In this paper we present a systematic sensitivity study of water-leaving contribution to the TOA radiation field, from 340 nm to 865 nm, with polarization included. Ocean water inherent optical properties are derived from bio-optical models for two kinds of waters, one dominated by phytoplankton (PDW) and the other by non-algae particles (NDW). In addition to elastic scattering, Raman scattering and fluorescence from dissolved organic matter in ocean waters are included. Our sensitivity study shows that the polarized reflectance is minimized for both CAOS and ocean signals in the backscattering half plane, which leads to numerical instability when calculating water leaving relative contribution, the ratio between polarized water leaving and CAOS signals. If the backscattering plane is excluded, the water-leaving polarized signal contributes less than 9% to the TOA polarized reflectance for PDW in the whole spectra. For NDW, the polarized water leaving contribution can be as much as 20% in the wavelength range from 470 to 670 nm. For wavelengths shorter than 452 nm or longer than 865 nm, the water leaving contribution to the TOA polarized reflectance is in general smaller than 5% for NDW. For the TOA total reflectance, the water-leaving contribution has maximum values ranging from 7% to 16% at variable wavelengths from 400 nm to 550 nm from PDW. The water leaving contribution to the TOA total reflectance can be as large as 35%for NDW, which is in general peaked at 550 nm. Both the total and polarized reflectances from water-leaving contributions approach zero in the ultraviolet and near infrared bands. These facts can be used as constraints or guidelines when estimating the water leaving contribution to the TOA reflectance for new atmospheric correction algorithms for ocean color imagery.

Surface-roughness considerations for atmospheric correction of ocean color sensors. II: Error in the retrieved water-leaving radiance.

PubMed

Gordon, H R; Wang, M

1992-07-20

In the algorithm for the atmospheric correction of coastal zone color scanner (CZCS) imagery, it is assumed that the sea surface is flat. Simulations are carried out to assess the error incurred when the CZCS-type algorithm is applied to a realistic ocean in which the surface is roughened by the wind. In situations where there is no direct Sun glitter (either a large solar zenith angle or the sensor tilted away from the specular image of the Sun), the following conclusions appear justified: (1) the error induced by ignoring the surface roughness is less, similar1 CZCS digital count for wind speeds up to approximately 17 m/s, and therefore can be ignored for this sensor; (2) the roughness-induced error is much more strongly dependent on the wind speed than on the wave shadowing, suggesting that surface effects can be adequately dealt with without precise knowledge of the shadowing; and (3) the error induced by ignoring the Rayleigh-aerosol interaction is usually larger than that caused by ignoring the surface roughness, suggesting that in refining algorithms for future sensors more effort should be placed on dealing with the Rayleigh-aerosol interaction than on the roughness of the sea surface.

Coherent structure coloring: identification of coherent structures from sparse flow trajectories using graph theory

NASA Astrophysics Data System (ADS)

Schlueter, Kristy; Dabiri, John

2016-11-01

Coherent structure identification is important in many fluid dynamics applications, including transport phenomena in ocean flows and mixing and diffusion in turbulence. However, many of the techniques currently available for measuring such flows, including ocean drifter datasets and particle tracking velocimetry, only result in sparse velocity data. This is often insufficient for the use of current coherent structure detection algorithms based on analysis of the deformation gradient. Here, we present a frame-invariant method for detecting coherent structures from Lagrangian flow trajectories that can be sparse in number. The method, based on principles used in graph coloring algorithms, examines a measure of the kinematic dissimilarity of all pairs of flow trajectories, either measured experimentally, e.g. using particle tracking velocimetry; or numerically, by advecting fluid particles in the Eulerian velocity field. Coherence is assigned to groups of particles whose kinematics remain similar throughout the time interval for which trajectory data is available, regardless of their physical proximity to one another. Through the use of several analytical and experimental validation cases, this algorithm is shown to robustly detect coherent structures using significantly less flow data than is required by existing methods. This research was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.

Detection of Coccolithophore Blooms in Ocean Color Satellite Imagery: a Generalized Approach for Use with Multiple Sensors

NASA Technical Reports Server (NTRS)

Moore, Timothy; Dowell, Mark; Franz, Bryan A.

2012-01-01

A generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by the default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cellsmL and 43,000 and 78,000 lithsmL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 19972010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemi- sphere with values of 2.00 106 km2 and 0.75 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75106 km2 is dominated by contributions from the Southern Ocean.

Bio-Optical and Remote Sensing Observations in Chesapeake Bay. Chapter 7

NASA Technical Reports Server (NTRS)

Harding, Lawrence W., Jr.; Magnuson, Andrea

2003-01-01

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements from Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (> 6,500 km2) make retrievals from satellites with a spatial resolution of approx. 1 km (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra.

Relationships between chlorophyll density and ocean radiance as measured by U2/OCS: Algorithms, examples and comparison

NASA Technical Reports Server (NTRS)

Kim, H. H.; Hart, W. D.

1983-01-01

An ocean atmosphere radiative transfer process computation method which is suitable for determining lower boundary ocean albedo and other radiation components from spectral measurements of upwelling radiance taken from a high altitude platform is described. The method was applied to a set of color scanner data taken from slope water of the South Atlantic Bight to determine the influence of cholorophyll-a pigments in the sea on the ratio of upwelling radiance to down welling irradiance as a function of wavelength. The resulting chlorophyll concentrations are compared with measurements made by ships stationed along the flight path.

Assessment of a bidirectional reflectance distribution correction of above-water and satellite water-leaving radiance in coastal waters.

PubMed

Hlaing, Soe; Gilerson, Alexander; Harmel, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

2012-01-10

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm. This confirms the advantages of the proposed model over the current one, demonstrating the need for a specific case 2 water BRDF correction algorithm as well as the feasibility of enhancing performance of current and future satellite ocean color remote sensing missions for monitoring of typical coastal waters. © 2012 Optical Society of America

Retrieving marine inherent optical properties from satellites using temperature and salinity-dependent backscattering by seawater.

PubMed

Werdell, P Jeremy; Franz, Bryan A; Lefler, Jason T; Robinson, Wayne D; Boss, Emmanuel

2013-12-30

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

Retrieving Marine Inherent Optical Properties from Satellites Using Temperature and Salinity-dependent Backscattering by Seawater

NASA Technical Reports Server (NTRS)

Werdell, Paul J.; Franz, Bryan Alden; Lefler, Jason Travis; Robinson, Wayne D.; Boss, Emmanuel

2013-01-01

Time-series of marine inherent optical properties (IOPs) from ocean color satellite instruments provide valuable data records for studying long-term time changes in ocean ecosystems. Semi-analytical algorithms (SAAs) provide a common method for estimating IOPs from radiometric measurements of the marine light field. Most SAAs assign constant spectral values for seawater absorption and backscattering, assume spectral shape functions of the remaining constituent absorption and scattering components (e.g., phytoplankton, non-algal particles, and colored dissolved organic matter), and retrieve the magnitudes of each remaining constituent required to match the spectral distribution of measured radiances. Here, we explore the use of temperature- and salinity-dependent values for seawater backscattering in lieu of the constant spectrum currently employed by most SAAs. Our results suggest that use of temperature- and salinity-dependent seawater spectra elevate the SAA-derived particle backscattering, reduce the non-algal particles plus colored dissolved organic matter absorption, and leave the derived absorption by phytoplankton unchanged.

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

NASA Technical Reports Server (NTRS)

Gregg, W. W.; Behrenfield, M. J.; Hoge, F. E.; Esaias, W. E.; Huang, N. E.; Long, S. R.; McClain, C. R.

2000-01-01

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Decadal Changes in Global Ocean Chlorophyll

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Conkright, Margarita E.; Koblinsky, Chester J. (Technical Monitor)

2001-01-01

The global ocean chlorophyll archive produced by the Coastal Zone Color Scanner (CZCS) was revised using compatible algorithms with the Sea-viewing Wide Field-of-view Sensor (SeaWIFS), and both were blended with in situ data. This methodology permitted a quantitative comparison of decadal changes in global ocean chlorophyll from the CZCS (1979-1986) and SeaWiFS (Sep. 1997-Dec. 2000) records. Global seasonal means of ocean chlorophyll decreased over the two observational segments, by 8% in winter to 16% in autumn. Chlorophyll in the high latitudes was responsible for most of the decadal change. Conversely, chlorophyll concentrations in the low latitudes increased. The differences and similarities of the two data records provide evidence of how the Earth's climate may be changing and how ocean biota respond. Furthermore, the results have implications for the ocean carbon cycle.

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

NASA Technical Reports Server (NTRS)

Mannino, Antonio; Novak, Michael G.; Hooker, Stanford B.; Hyde, Kimberly; Aurin, Dick

2014-01-01

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

The relationship between phytoplankton concentration and light attenuation in ocean waters

NASA Technical Reports Server (NTRS)

Phinney, David A.; Yentsch, Charles S.

1986-01-01

The accuracy of chlorophyll estimates by ocean color algorithms is affected by the variability of particulate attenuation; the presence of dissolved organic matter; and the nonlinear inverse relationship between the attenuation coefficient, K, and chlorophyll. Data collected during the Warm Core Rings Program were used to model the downwelling light field and determine the impact of these errors. A possible mechanism for the nonlinearity of K and chlorophyll is suggested; namely, that changing substrate from nitrate-nitrogen to ammonium causes enhanced blue absorption by photosynthetic phytoplankton in oligotrophic surface waters.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

PubMed

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the “MAPP” algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stamnes, S.; Hostetler, C.; Ferrare, R.

We present an optimal estimation based retrieval framework, the Microphysical Aerosol Properties from Polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High Spectral Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355, 532, and 1064 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ã…ngstrømmore » exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio- Optical Research (SABOR) campaign. For the SABOR campaign, 71% RSP MAPP retrievals fall within 0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.925 and root-mean-square deviation of 0.04. For the TCAP campaign, 55% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.925 and root-mean-square deviation of 0.07. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.96 and a root-mean-square deviation of also 0.07. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar+polarimeter retrieval using both HSRL and RSP measurements.« less

Remote Sensing of Suspended Sediments and Shallow Coastal Waters

NASA Technical Reports Server (NTRS)

Li, Rong-Rong; Kaufman, Yoram J.; Gao, Bo-Cai; Davis, Curtiss O.

2002-01-01

Ocean color sensors were designed mainly for remote sensing of chlorophyll concentrations over the clear open oceanic areas (case 1 water) using channels between 0.4 and 0.86 micrometers. The Moderate Resolution Imaging Spectroradiometer (MODIS) launched on the NASA Terra and Aqua Spacecrafts is equipped with narrow channels located within a wider wavelength range between 0.4 and 2.5 micrometers for a variety of remote sensing applications. The wide spectral range can provide improved capabilities for remote sensing of the more complex and turbid coastal waters (case 2 water) and for improved atmospheric corrections for Ocean scenes. In this article, we describe an empirical algorithm that uses this wide spectral range to identifying areas with suspended sediments in turbid waters and shallow waters with bottom reflections. The algorithm takes advantage of the strong water absorption at wavelengths longer than 1 micrometer that does not allow illumination of sediments in the water or a shallow ocean floor. MODIS data acquired over the east coast of China, west coast of Africa, Arabian Sea, Mississippi Delta, and west coast of Florida are used in this study.

Evaluation of bio-optical algorithms to remotely sense marine primary production from space

NASA Technical Reports Server (NTRS)

Berthelot, Beatrice; Deschamps, Pierre-Yves

1994-01-01

In situ bio-optical measurements from several oceanographic campaigns were analyzed to derive a direct relationship between water column primary production P (sub t) ocean color as expressed by the ratio of reflectances R (sub 1) at 440 nm and R (sub 3) at 550 nm and photosynthetically available radiation (PAR). The study is restricted to the Morel case I waters for which the following algorithm is proposed: log (P(sub f)) = -4.286 - 1.390 log (R(sub 1)/R(sub3)) + 0.621 log (PAR), with P(sub t) in g C m(exp -2)/d and PAR in J m(exp -2)/d. Using this algorithm the rms accuracy of primary production estimate is 0.17 on a logarithmic scale, i.e., a factor of 1.5. Using spectral reflectance measurements in the entire visible spectral range, the central wavelength, spectral bandwidth, and radiometric noise level requirements are investigated for the channels to be used by an ocean color space mission dedicated to estimating global marine primary production and the associated carbon fluxes. Nearly all the useful information is provided by two channels centered at 440 nm and 550 nm, but the accuracy of primary production estimate appears weakly sensitive to spectral bandwidth, which, consequently, may be enlarged by several tens of nanometers. The sensitivity to radiometric noise, on the contrary, is strong, and a noise equivalent reflectance of 0.005 degraded the accuracy on the primary production estimate by a factor 2 (0.14-0.25 on a logarithmic scale). The results should be applicable to evaluating the primary production of oligotrophic and mesotrophic waters, which constitute most of the open ocean.

Evaluation of coastal zone color scanner diffuse attenuation coefficient algorithms for application to coastal waters

NASA Astrophysics Data System (ADS)

Mueller, James L.; Trees, Charles C.; Arnone, Robert A.

1990-09-01

The Coastal Zone Color Scannez (ZCS) and associated atmospheric and in-water algorithms have allowed synoptic analyses of regional and large scale variability of bio-optical properties [phytoplankton pigments and diffuse auenuation coefficient K(490)}. Austin and Petzold (1981) developed a robust in-water K(490) algorithm which related the diffuse attenuation coefficient at one optical depth [1/K(490)] to the ratio of the water-leaving radiances at 443 and 550 nm. Their regression analysis included diffuse attenuation coefficients K(490) up to 0.40 nm, but excluded data from estuarine areas, and other Case II waters, where the optical properties are not predominantly determined by phytoplankton. In these areas, errors are induced in the retrieval of remote sensing K(490) by extremely low water-leaving radiance at 443 nm [Lw(443) as viewed at the sensor may only be 1 or 2 digital counts], and improved cury can be realized using algorithms based on wavelengths where Lw(λ) is larger. Using ocean optical profiles quired by the Visibility Laboratory, algorithms are developed to predict K(490) from ratios of water leaving radiances at 520 and 670, as well as 443 and 550 nm.

Seasonal and Inter-Annual Patterns of Phytoplankton Community Structure in Monterey Bay, CA Derived from AVIRIS Data During the 2013-2015 HyspIRI Airborne Campaign

NASA Astrophysics Data System (ADS)

Palacios, S. L.; Thompson, D. R.; Kudela, R. M.; Negrey, K.; Guild, L. S.; Gao, B. C.; Green, R. O.; Torres-Perez, J. L.

2015-12-01

There is a need in the ocean color community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand ocean biodiversity, to track energy flow through ecosystems, and to identify and monitor for harmful algal blooms. Imaging spectrometer measurements enable use of sophisticated spectroscopic algorithms for applications such as differentiating among coral species, evaluating iron stress of phytoplankton, and discriminating phytoplankton taxa. These advanced algorithms rely on the fine scale, subtle spectral shape of the atmospherically corrected remote sensing reflectance (Rrs) spectrum of the ocean surface. As a consequence, these algorithms are sensitive to inaccuracies in the retrieved Rrs spectrum that may be related to the presence of nearby clouds, inadequate sensor calibration, low sensor signal-to-noise ratio, glint correction, and atmospheric correction. For the HyspIRI Airborne Campaign, flight planning considered optimal weather conditions to avoid flights with significant cloud/fog cover. Although best suited for terrestrial targets, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has enough signal for some coastal chlorophyll algorithms and meets sufficient calibration requirements for most channels. However, the coastal marine environment has special atmospheric correction needs due to error that may be introduced by aerosols and terrestrially sourced atmospheric dust and riverine sediment plumes. For this HyspIRI campaign, careful attention has been given to the correction of AVIRIS imagery of the Monterey Bay to optimize ocean Rrs retrievals for use in estimating chlorophyll (OC3 algorithm) and phytoplankton functional type (PHYDOTax algorithm) data products. This new correction method has been applied to several image collection dates during two oceanographic seasons - upwelling and the warm, stratified oceanic period for 2013 and 2014. These two periods are dominated by either diatom blooms (occasionally toxic) or red tides. Results presented include chlorophyll and phytoplankton community structure and in-water validation data for these dates during these two seasons.

Bidirectional reflectance function in coastal waters: modeling and validation

NASA Astrophysics Data System (ADS)

Gilerson, Alex; Hlaing, Soe; Harmel, Tristan; Tonizzo, Alberto; Arnone, Robert; Weidemann, Alan; Ahmed, Samir

2011-11-01

The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms, specifically tuned for typical coastal waters and other case 2 conditions, are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multi- and hyperspectral radiometers which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths.

Analysis Of AVIRIS Data From LEO-15 Using Tafkaa Atmospheric Correction

NASA Technical Reports Server (NTRS)

Montes, Marcos J.; Gao, Bo-Cai; Davis, Curtiss O.; Moline, Mark

2004-01-01

We previously developed an algorithm named Tafkaa for atmospheric correction of remote sensing ocean color data from aircraft and satellite platforms. The algorithm allows quick atmospheric correction of hyperspectral data using lookup tables generated with a modified version of Ahmad & Fraser s vector radiative transfer code. During the past few years we have extended the capabilities of the code. Current modifications include the ability to account for within scene variation in solar geometry (important for very long scenes) and view geometries (important for wide fields of view). Additionally, versions of Tafkaa have been made for a variety of multi-spectral sensors, including SeaWiFS and MODIS. In this proceeding we present some initial results of atmospheric correction of AVIRIS data from the 2001 July Hyperspectral Coastal Ocean Dynamics Experiment (HyCODE) at LEO-15.

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

NASA Technical Reports Server (NTRS)

Cao, Fang; Fichot, Cedric G.; Hooker, Stanford B.; Miller, William L.

2014-01-01

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This optimized composite set of SeaUVSeaUVc algorithms will provide the optical community with improved ability to quantify the role of solar UV radiation in photochemical and photobiological processes in the ocean.

Generalized ocean color inversion model for retrieving marine inherent optical properties.

PubMed

Werdell, P Jeremy; Franz, Bryan A; Bailey, Sean W; Feldman, Gene C; Boss, Emmanuel; Brando, Vittorio E; Dowell, Mark; Hirata, Takafumi; Lavender, Samantha J; Lee, ZhongPing; Loisel, Hubert; Maritorena, Stéphane; Mélin, Fréderic; Moore, Timothy S; Smyth, Timothy J; Antoine, David; Devred, Emmanuel; d'Andon, Odile Hembise Fanton; Mangin, Antoine

2013-04-01

Ocean color measured from satellites provides daily, global estimates of marine inherent optical properties (IOPs). Semi-analytical algorithms (SAAs) provide one mechanism for inverting the color of the water observed by the satellite into IOPs. While numerous SAAs exist, most are similarly constructed and few are appropriately parameterized for all water masses for all seasons. To initiate community-wide discussion of these limitations, NASA organized two workshops that deconstructed SAAs to identify similarities and uniqueness and to progress toward consensus on a unified SAA. This effort resulted in the development of the generalized IOP (GIOP) model software that allows for the construction of different SAAs at runtime by selection from an assortment of model parameterizations. As such, GIOP permits isolation and evaluation of specific modeling assumptions, construction of SAAs, development of regionally tuned SAAs, and execution of ensemble inversion modeling. Working groups associated with the workshops proposed a preliminary default configuration for GIOP (GIOP-DC), with alternative model parameterizations and features defined for subsequent evaluation. In this paper, we: (1) describe the theoretical basis of GIOP; (2) present GIOP-DC and verify its comparable performance to other popular SAAs using both in situ and synthetic data sets; and, (3) quantify the sensitivities of their output to their parameterization. We use the latter to develop a hierarchical sensitivity of SAAs to various model parameterizations, to identify components of SAAs that merit focus in future research, and to provide material for discussion on algorithm uncertainties and future emsemble applications.

Generalized Ocean Color Inversion Model for Retrieving Marine Inherent Optical Properties

NASA Technical Reports Server (NTRS)

Werdell, P. Jeremy; Franz, Bryan A.; Bailey, Sean W.; Feldman, Gene C.; Boss, Emmanuel; Brando, Vittorio E.; Dowell, Mark; Hirata, Takafumi; Lavender, Samantha J.; Lee, ZhongPing;

Inter-annual Variability in Global Suspended Particulate Inorganic Carbon Inventory Using Space-based Measurements

NASA Astrophysics Data System (ADS)

Hopkins, J.; Balch, W. M.; Henson, S.; Poulton, A. J.; Drapeau, D.; Bowler, B.; Lubelczyk, L.

2016-02-01

Coccolithophores, the single celled phytoplankton that produce an outer covering of calcium carbonate coccoliths, are considered to be the greatest contributors to the global oceanic particulate inorganic carbon (PIC) pool. The reflective coccoliths scatter light back out from the ocean surface, enabling PIC concentration to be quantitatively estimated from ocean color satellites. Here we use datasets of AQUA MODIS PIC concentration from 2003-2014 (using the recently-revised PIC algorithm), as well as statistics on coccolithophore vertical distribution derived from cruises throughout the world ocean, to estimate the average global (surface and integrated) PIC standing stock and its associated inter-annual variability. In addition, we divide the global ocean into Longhurst biogeochemical provinces, update the PIC biomass statistics and identify those regions that have the greatest inter-annual variability and thus may exert the greatest influence on global PIC standing stock and the alkalinity pump.

Remote Sensing of Ocean Color

NASA Astrophysics Data System (ADS)

Dierssen, Heidi M.; Randolph, Kaylan

The oceans cover over 70% of the earth's surface and the life inhabiting the oceans play an important role in shaping the earth's climate. Phytoplankton, the microscopic organisms in the surface ocean, are responsible for half of the photosynthesis on the planet. These organisms at the base of the food web take up light and carbon dioxide and fix carbon into biological structures releasing oxygen. Estimating the amount of microscopic phytoplankton and their associated primary productivity over the vast expanses of the ocean is extremely challenging from ships. However, as phytoplankton take up light for photosynthesis, they change the color of the surface ocean from blue to green. Such shifts in ocean color can be measured from sensors placed high above the sea on satellites or aircraft and is called "ocean color remote sensing." In open ocean waters, the ocean color is predominantly driven by the phytoplankton concentration and ocean color remote sensing has been used to estimate the amount of chlorophyll a, the primary light-absorbing pigment in all phytoplankton. For the last few decades, satellite data have been used to estimate large-scale patterns of chlorophyll and to model primary productivity across the global ocean from daily to interannual timescales. Such global estimates of chlorophyll and primary productivity have been integrated into climate models and illustrate the important feedbacks between ocean life and global climate processes. In coastal and estuarine systems, ocean color is significantly influenced by other light-absorbing and light-scattering components besides phytoplankton. New approaches have been developed to evaluate the ocean color in relationship to colored dissolved organic matter, suspended sediments, and even to characterize the bathymetry and composition of the seafloor in optically shallow waters. Ocean color measurements are increasingly being used for environmental monitoring of harmful algal blooms, critical coastal habitats (e.g., seagrasses, kelps), eutrophication processes, oil spills, and a variety of hazards in the coastal zone.

Automated navigation assessment for earth survey sensors using island targets

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Woodward, Robert H.; Gregg, Watson W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Monitoring of hourly variations in coastal water turbidity using the geostationary ocean color imager (GOCI)

NASA Astrophysics Data System (ADS)

Choi, J.; Ryu, J.

2011-12-01

Temporal variations of suspended sediment concentration (SSC) in coastal water are the key to understanding the pattern of sediment movement within coastal area, in particular, such as in the west coast of the Korean Peninsula which is influenced by semi-diurnal tides. Remote sensing techniques can effectively monitor the distribution and dynamic changes in seawater properties across wide areas. Thus, SSC on the sea surface has been investigated using various types of satellite-based sensors. An advantage of Geostationary Ocean Color Imager (GOCI), the world's first geostationary ocean color observation satellite, over other ocean color satellite images is that it can obtain data every hour during the day and makes it possible to monitor the ocean in real time. In this study, hourly variations in turbidity on the coastal waters were estimated quantitatively using GOCI. Thirty three water samples were obtained on the coastal water surface in southern Gyeonggi Bay, located on the west coast of Korea. Water samples were filtered using 25-mm glass fiber filters (GF/F) for the estimation of SSC. The radiometric characteristics of the surface water, such as the total water-leaving radiance (LwT, W/m2/nm/sr), the sky radiance (Lsky, W/m2/nm/sr) and the downwelling irradiance, were also measured at each sampling location. In situ optical properties of the surface water were converted into remote sensing reflectance (Rrs) and then were used to develop an algorithm to generate SSC images in the study area. GOCI images acquired on the same day as the samples acquisition were used to generate the map of turbidity and to estimate the difference in SSC displayed in each image. The estimation of the time-series variation in SSC in a coastal, shallow-water area affected by tides was successfully achieved using GOCI data that had been acquired at hourly intervals during the daytime.

NASA COAST and OCEANIA Airborne Missions in Support of Ecosystem and Water Quality Research in the Coastal Zone

NASA Technical Reports Server (NTRS)

Guild, Liane S.; Hooker, Stanford B.; Kudela, Raphael; Morrow, John; Russell, Philip; Myers, Jeffrey; Dunagan, Stephen; Palacios, Sherry; Livingston, John; Negrey, Kendra;

Ocean Color and Earth Science Data Records

NASA Astrophysics Data System (ADS)

Maritorena, S.

2014-12-01

The development of consistent, high quality time series of biogeochemical products from a single ocean color sensor is a difficult task that involves many aspects related to pre- and post-launch instrument calibration and characterization, stability monitoring and the removal of the contribution of the atmosphere which represents most of the signal measured at the sensor. It is even more challenging to build Climate Data Records (CDRs) or Earth Science Data Records (ESDRs) from multiple sensors as design, technology and methodologies (bands, spectral/spatial resolution, Cal/Val, algorithms) differ from sensor to sensor. NASA MEaSUREs, ESA Climate Change Initiative (CCI) and IOCCG Virtual Constellation are some of the underway efforts that investigate or produce ocean color CDRs or ESDRs from the recent and current global missions (SeaWiFS, MODIS, MERIS). These studies look at key aspects of the development of unified data records from multiple sensors, e.g. the concatenation of the "best" individual records vs. the merging of multiple records or band homogenization vs. spectral diversity. The pros and cons of the different approaches are closely dependent upon the overall science purpose of the data record and its temporal resolution. While monthly data are generally adequate for biogeochemical modeling or to assess decadal trends, higher temporal resolution data records are required to look into changes in phenology or the dynamics of phytoplankton blooms. Similarly, short temporal resolution (daily to weekly) time series may benefit more from being built through the merging of data from multiple sensors while a simple concatenation of data from individual sensors might be better suited for longer temporal resolution (e.g. monthly time series). Several Ocean Color ESDRs were developed as part of the NASA MEaSUREs project. Some of these time series are built by merging the reflectance data from SeaWiFS, MODIS-Aqua and Envisat-MERIS in a semi-analytical ocean color model that generates both merged reflectance and merged biogeochemical products. The benefits and limitations of this merging approach to develop ESDRs will be presented and discussed along with those of alternative approaches.

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Franz, Bryan A.

2016-01-01

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

Variability in global ocean phytoplankton distribution over 1979-2007

NASA Astrophysics Data System (ADS)

Masotti, I.; Alvain, S.; Moulin, C.; Antoine, D.

2009-04-01

Recently, reanalysis of long-term ocean color data (CZCS and SeaWiFS; Antoine et al., 2005) has shown that world ocean average phytoplankton chlorophyll levels show an increase of 20% over the last two decades. It is however unknown whether this increase is associated with a change in the distribution of phytoplankton groups or if it simply corresponds to an increase of the productivity. Within the framework of the GLOBPHY project, the distribution of the phytoplankton groups was monitored by applying the PHYSAT method (Alvain et al., 2005) to the historical ocean color data series from CZCS, OCTS and SeaWiFS sensors. The PHYSAT algorithm allows identification of several phytoplankton, like nanoeucaryotes, prochlorococcus, synechococcus and diatoms. Because both sensors (OCTS-SeaWiFS) are very similar, OCTS data were processed with the standard PHYSAT algorithm to cover the 1996-1997 period during which a large El Niño event occurred, just before the SeaWiFS era. Our analysis of this dataset (1996-2006) evidences a strong variability in the distribution of phytoplankton groups at both regional and global scales. In the equatorial region (0°-5°S), a three-fold increase of nanoeucaryotes frequency was detected in opposition to a two-fold decrease of synechococcus during the early stages of El Niño conditions (May-June 1997, OCTS). The impact of this El Niño is however not confined to the Equatorial Pacific and has affected the global ocean. The processing of CZCS data with PHYSAT has required several adaptations of this algorithm due to the lower performances and the reduced number of spectral bands of the sensor. Despites higher uncertainties, the phytoplankton groups distribution obtained with CZCS is globally consistent with that of SeaWiFS. A comparison of variability in global phytoplankton distribution between 1979-1982 (CZCS) and 1999-2002 (SeaWiFS) suggests an increase in nanoeucaryotes at high latitudes (>40°) and in the equatorial region (10°S-10°N ) for prochlorococcus and synechococcus during 1999-2002. Our results show variability in global ocean phytoplankton distribution over a 20-year timescale. Strong variability observed over the inter-annual and inter-decadal scales are shown and tentatively explained using environmental variables.

Diurnal changes in ocean color in coastal waters

NASA Astrophysics Data System (ADS)

Arnone, Robert; Vandermeulen, Ryan; Ladner, Sherwin; Ondrusek, Michael; Kovach, Charles; Yang, Haoping; Salisbury, Joseph

2016-05-01

Coastal processes can change on hourly time scales in response to tides, winds and biological activity, which can influence the color of surface waters. These temporal and spatial ocean color changes require satellite validation for applications using bio-optical products to delineate diurnal processes. The diurnal color change and capability for satellite ocean color response were determined with in situ and satellite observations. Hourly variations in satellite ocean color are dependent on several properties which include: a) sensor characterization b) advection of water masses and c) diurnal response of biological and optical water properties. The in situ diurnal changes in ocean color in a dynamic turbid coastal region in the northern Gulf of Mexico were characterized using above water spectral radiometry from an AErosol RObotic NETwork (AERONET -WavCIS CSI-06) site that provides up to 8-10 observations per day (in 15-30 minute increments). These in situ diurnal changes were used to validate and quantify natural bio-optical fluctuations in satellite ocean color measurements. Satellite capability to detect changes in ocean color was characterized by using overlapping afternoon orbits of the VIIRS-NPP ocean color sensor within 100 minutes. Results show the capability of multiple satellite observations to monitor hourly color changes in dynamic coastal regions that are impacted by tides, re-suspension, and river plume dispersion. Hourly changes in satellite ocean color were validated with in situ observation on multiple occurrences during different times of the afternoon. Also, the spatial variability of VIIRS diurnal changes shows the occurrence and displacement of phytoplankton blooms and decay during the afternoon period. Results suggest that determining the temporal and spatial changes in a color / phytoplankton bloom from the morning to afternoon time period will require additional satellite coverage periods in the coastal zone.

Removal of atmospheric effects from satellite imagery of the oceans.

PubMed

Gordon, H R

1978-05-15

In attempting to observe the color of the ocean from satellites, it is necessary to remove the effects of atmospheric and sea surface scattering from the upward radiance at high altitude in order to observe only those photons which were backscattered out of the ocean and hence contain information about subsurface conditions. The observations that (1) the upward radiance from the unwanted photons can be divided into those resulting from Rayleigh scattering alone and those resulting from aerosol scattering alone, (2) the aerosol scattering phase function should be nearly independent of wavelength, and (3) the Rayleigh component can be computed without a knowledge of the sea surface roughness are combined to yield an algorithm for removing a large portion of this unwanted radiance from satellite imagery of the ocean. It is assumed that the ocean is totally absorbing in a band of wavelengths around 750 nm and shown that application of the proposed algorithm to correct the radiance at a wavelength lambda requires only the ratio () of the aerosol optical thickness at lambda to that at about 750 nm. The accuracy to which the correction can be made as a function of the accuracy to which can be found is in detail. A possible method of finding from satellite measurements alone is suggested.

The SeaDAS Processing and Analysis System: SeaWiFS, MODIS, and Beyond

NASA Astrophysics Data System (ADS)

MacDonald, M. D.; Ruebens, M.; Wang, L.; Franz, B. A.

2005-12-01

The SeaWiFS Data Analysis System (SeaDAS) is a comprehensive software package for the processing, display, and analysis of ocean data from a variety of satellite sensors. Continuous development and user support by programmers and scientists for more than a decade has helped to make SeaDAS the most widely used software package in the world for ocean color applications, with a growing base of users from the land and sea surface temperature community. Full processing support for past (CZCS, OCTS, MOS) and present (SeaWiFS, MODIS) sensors, and anticipated support for future missions such as NPP/VIIRS, enables end users to reproduce the standard ocean archive product suite distributed by NASA's Ocean Biology Processing Group (OBPG), as well as a variety of evaluation and intermediate ocean, land, and atmospheric products. Availability of the processing algorithm source codes and a software build environment also provide users with the tools to implement custom algorithms. Recent SeaDAS enhancements include synchronization of MODIS processing with the latest code and calibration updates from the MODIS Calibration Support Team (MCST), support for all levels of MODIS processing including Direct Broadcast, a port to the Macintosh OS X operating system, release of the display/analysis-only SeaDAS-Lite, and an extremely active web-based user support forum.

Mission to Planet Earth. The living ocean: Observing ocean color from space

NASA Technical Reports Server (NTRS)

1994-01-01

Measurements of ocean color are part of NASA's Mission to Planet Earth, which will assess how the global environment is changing. Using the unique perspective available from space, NASA will observe, monitor, and study large-scale environmental processes, focusing on quantifying climate change. NASA will distribute the results of these studies to researchers worldwide to furnish a basis for informed decisions on environmental protection and economic policy. This information packet includes discussion on the reasons for measuring ocean color, the carbon cycle and ocean color, priorities for global climate research, and SeWiFS (sea-viewing wide field-of-view sensor) global ocean color measurements.

Retrieval of total suspended particulate matter in highly turbid Hangzhou Bay waters based on geostationary ocean color imager

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Jiahang; He, Xianqiang; Chen, Tieqiao; Zhu, Feng; Wang, Yihao; Hao, Zengzhou; Chen, Peng

2017-10-01

Hangzhou Bay waters are often characterized by extremely high total suspended particulate matter (TSM) concentration due to terrestrial inputs, bottom sediment resuspension and human activities. The spatial-temporal variability of TSM directly contributes to the transport of carbon, nutrients, pollutants, and other materials. Therefore, it is essential to maintain and monitor sedimentary environment in coastal waters. Traditional field sampling methods limit observation capability for insufficient spatial-temporal resolution. Thus, it is difficult to synoptically monitor high diurnal dynamics of TSM. However, the in-orbit operation of the world's first geostationary satellite ocean color sensor, GOCI, thoroughly changes this situation with hourly observations of covered area. Taking advantage of GOCI high spatial-temporal resolution, we generated TSM maps from GOCI Level-1B data after atmospheric correction based on six TSM empirical algorithms. Validation of GOCI-retrieved normalized water-leaving radiances and TSM concentration was presented in comparison with matched-up in-situ measurements. The mean absolute percentage differences of those six TSM regional algorithms were 24.52%, 163.93%, 195.50%, 70.50%, 121.02%, 82.72%, respectively. In addition, the discrepancy reasons were presented, taking more factors such as diversified satellite data, various study area, and different research season into consideration. It is effective and indispensable to monitor and catch the diurnal dynamics of TSM in Hangzhou Bay coastal waters, with hourly GOCI observations data and appropriate inversion algorithm.

Classification of Hyperspectral or Trichromatic Measurements of Ocean Color Data into Spectral Classes.

PubMed

Prasad, Dilip K; Agarwal, Krishna

2016-03-22

We propose a method for classifying radiometric oceanic color data measured by hyperspectral satellite sensors into known spectral classes, irrespective of the downwelling irradiance of the particular day, i.e., the illumination conditions. The focus is not on retrieving the inherent optical properties but to classify the pixels according to the known spectral classes of the reflectances from the ocean. The method compensates for the unknown downwelling irradiance by white balancing the radiometric data at the ocean pixels using the radiometric data of bright pixels (typically from clouds). The white-balanced data is compared with the entries in a pre-calibrated lookup table in which each entry represents the spectral properties of one class. The proposed approach is tested on two datasets of in situ measurements and 26 different daylight illumination spectra for medium resolution imaging spectrometer (MERIS), moderate-resolution imaging spectroradiometer (MODIS), sea-viewing wide field-of-view sensor (SeaWiFS), coastal zone color scanner (CZCS), ocean and land colour instrument (OLCI), and visible infrared imaging radiometer suite (VIIRS) sensors. Results are also shown for CIMEL's SeaPRISM sun photometer sensor used on-board field trips. Accuracy of more than 92% is observed on the validation dataset and more than 86% is observed on the other dataset for all satellite sensors. The potential of applying the algorithms to non-satellite and non-multi-spectral sensors mountable on airborne systems is demonstrated by showing classification results for two consumer cameras. Classification on actual MERIS data is also shown. Additional results comparing the spectra of remote sensing reflectance with level 2 MERIS data and chlorophyll concentration estimates of the data are included.

VIIRS On-Orbit Calibration for Ocean Color Data Processing

NASA Technical Reports Server (NTRS)

Eplee, Robert E., Jr.; Turpie, Kevin R.; Fireman, Gwyn F.; Meister, Gerhard; Stone, Thomas C.; Patt, Frederick S.; Franz, Bryan; Bailey, Sean W.; Robinson, Wayne D.; McClain, Charles R.

2012-01-01

The NASA VIIRS Ocean Science Team (VOST) has the task of evaluating Suomi NPP VIIRS ocean color data for the continuity of the NASA ocean color climate data records. The generation of science quality ocean color data products requires an instrument calibration that is stable over time. Since the VIIRS NIR Degradation Anomaly directly impacts the bands used for atmospheric correction of the ocean color data (Bands M6 and M7), the VOST has adapted the VIIRS on-orbit calibration approach to meet the ocean science requirements. The solar diffuser calibration time series and the solar diffuser stability monitor time series have been used to derive changes in the instrument response and diffuser reflectance over time for bands M1-M11.

Development of Finer Spatial Resolution Optical Properties from MODIS

DTIC Science & Technology

2008-02-04

infrared (SWIR) channels at 1240 nm and 2130 run. The increased resolution spectral Rrs channels are input into bio-optical algorithms (Quasi...processes. Additionally, increased resolution is required for validation of ocean color products in coastal regions due to the shorter spatial scales of...with in situ Rrs data to determine the "best" method in coastal regimes. We demonstrate that finer resolution is required for validation of coastal

Sampling Biases in MODIS and SeaWiFS Ocean Chlorophyll Data

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Casey, Nancy W.

2007-01-01

Although modem ocean color sensors, such as MODIS and SeaWiFS are often considered global missions, in reality it takes many days, even months, to sample the ocean surface enough to provide complete global coverage. The irregular temporal sampling of ocean color sensors can produce biases in monthly and annual mean chlorophyll estimates. We quantified the biases due to sampling using data assimilation to create a "truth field", which we then sub-sampled using the observational patterns of MODIS and SeaWiFS. Monthly and annual mean chlorophyll estimates from these sub-sampled, incomplete daily fields were constructed and compared to monthly and annual means from the complete daily fields of the assimilation model, at a spatial resolution of 1.25deg longitude by 0.67deg latitude. The results showed that global annual mean biases were positive, reaching nearly 8% (MODIS) and >5% (SeaWiFS). For perspective the maximum interannual variability in the SeaWiFS chlorophyll record was about 3%. Annual mean sampling biases were low (<3%) in the midlatitudes (between -40deg and 40deg). Low interannual variability in the global annual mean sampling biases suggested that global scale trend analyses were valid. High latitude biases were much higher than the global annual means, up to 20% as a basin annual mean, and over 80% in some months. This was the result of the high solar zenith angle exclusion in the processing algorithms. Only data where the solar angle is <75deg are permitted, in contrast to the assimilation which samples regularly over the entire area and month. High solar zenith angles do not facilitate phytoplankton photosynthesis and consequently low chlorophyll concentrations occurring here are missed by the data sets. Ocean color sensors selectively sample in locations and times of favorable phytoplankton growth, producing overestimates of chlorophyll. The biases derived from lack of sampling in the high latitudes varied monthly, leading to artifacts in the apparent seasonal cycle from ocean color sensors. A false secondary peak in chlorophyll occurred in May-August, which resulted from lack of sampling in the Antarctic.

Validation of Carbon Flux and Related Products for SIMBIOS: The CARIACO Continental Margin Time Series and the Orinoco River Plume. Chapter 15

NASA Technical Reports Server (NTRS)

Muller-Karger, Frank; Hu, Chuanmin; Akl, John P.; Varela, Ramon

2001-01-01

Between 1997 and 2000, this Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) investigation collected bio-optical measurements in the Southeastern Caribbean Sea and the tropical western Atlantic to help understand the color of coastal and continental shelf waters. Specifically, bio-optical data were collected to complement an oceanographic time series maintained within the Cariaco Basin, a site affected by seasonal coastal upwelling. Bio-optical data were also collected within the plume of the Orinoco River during seasonal extremes in discharge. This program focused on providing data to the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and SIMBIOS Projects for validating SeaWiFS products. The data are unique in that they provide a substantial number of observations on repeated seasonal cycles for the SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) bio-optical database. An important aspect of this SIMBIOS investigation was a focus on proper interpretation of ocean color remote sensing data from coastal and continental shelf environments. With this goal in mind, ocean color satellite data from a variety and locations and from different satellite sensors were examined to understand spatial and temporal variability in pigment concentrations, and also to conduct an in-depth study of current atmospheric correction and bio-optical algorithms.

Enhance field water-color measurements with a Secchi disk and its implication for fusion of active and passive ocean-color remote sensing.

PubMed

Lee, Zhongping; Shang, Shaoling; Du, Keping; Liu, Bingyi; Lin, Gong; Wei, Jianwei; Li, Xiaolong

2018-05-01

Inversion of the total absorption (a) and backscattering coefficients of bulk water through a fusion of remote sensing reflectance (R rs ) and Secchi disk depth (Z SD ) is developed. An application of such a system to a synthesized wide-range dataset shows a reduction of ∼3 folds in the uncertainties of inverted a(λ) (in a range of ∼0.01-6.8  m -1 ) from R rs (λ) for the 350-560 nm range. Such a fusion is further proposed to process concurrent active (ocean LiDAR) and passive (ocean-color) measurements, which can lead to nearly "exact" analytical inversion of an R rs spectrum. With such a fusion, it is found that the uncertainty in the inverted total a in the 350-560 nm range could be reduced to ∼2% for the synthesized data, which can thus significantly improve the derivation of a coefficients of other varying components. Although the inclusion of Z SD places an extra constraint in the inversion of R rs , no apparent improvement over the quasi-analytical algorithm (QAA) was found when the fusion of Z SD and R rs was applied to a field dataset, which calls for more accurate determination of the absorption coefficients from water samples.

Estimates of phytoplankton class-specific and total primary production in the Mediterranean Sea from satellite ocean color observations

NASA Astrophysics Data System (ADS)

Uitz, Julia; Stramski, Dariusz; Gentili, Bernard; D'Ortenzio, Fabrizio; Claustre, Hervé

2012-06-01

An approach that combines a recently developed procedure for improved estimation of surface chlorophyll a concentration (Chlsurf) from ocean color and a phytoplankton class-specific bio-optical model was used to examine primary production in the Mediterranean Sea. Specifically, this approach was applied to the 10 year time series of satellite Chlsurfdata from the Sea-viewing Wide Field-of-view Sensor. We estimated the primary production associated with three major phytoplankton classes (micro, nano, and picophytoplankton), which also yielded new estimates of the total primary production (Ptot). These estimates of Ptot (e.g., 68 g C m-2 yr-1for the entire Mediterranean basin) are lower by a factor of ˜2 and show a different seasonal cycle when compared with results from conventional approaches based on standard ocean color chlorophyll algorithm and a non-class-specific primary production model. Nanophytoplankton are found to be dominant contributors to Ptot (43-50%) throughout the year and entire basin. Micro and picophytoplankton exhibit variable contributions to Ptot depending on the season and ecological regime. In the most oligotrophic regime, these contributions are relatively stable all year long with picophytoplankton (˜32%) playing a larger role than microphytoplankton (˜22%). In the blooming regime, picophytoplankton dominate over microphytoplankton most of the year, except during the spring bloom when microphytoplankton (27-38%) are considerably more important than picophytoplankton (20-27%).

Sensor-independent approach to the vicarious calibration of satellite ocean color radiometry.

PubMed

Franz, Bryan A; Bailey, Sean W; Werdell, P Jeremy; McClain, Charles R

2007-08-01

The retrieval of ocean color radiometry from space-based sensors requires on-orbit vicarious calibration to achieve the level of accuracy desired for quantitative oceanographic applications. The approach developed by the NASA Ocean Biology Processing Group (OBPG) adjusts the integrated instrument and atmospheric correction system to retrieve normalized water-leaving radiances that are in agreement with ground truth measurements. The method is independent of the satellite sensor or the source of the ground truth data, but it is specific to the atmospheric correction algorithm. The OBPG vicarious calibration approach is described in detail, and results are presented for the operational calibration of SeaWiFS using data from the Marine Optical Buoy (MOBY) and observations of clear-water sites in the South Pacific and southern Indian Ocean. It is shown that the vicarious calibration allows SeaWiFS to reproduce the MOBY radiances and achieve good agreement with radiometric and chlorophyll a measurements from independent in situ sources. We also find that the derived vicarious gains show no significant temporal or geometric dependencies, and that the mission-average calibration reaches stability after approximately 20-40 high-quality calibration samples. Finally, we demonstrate that the performance of the vicariously calibrated retrieval system is relatively insensitive to the assumptions inherent in our approach.

Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry.

PubMed

Dall'Olmo, Giorgio; Brewin, Robert J W; Nencioli, Francesco; Organelli, Emanuele; Lefering, Ina; McKee, David; Röttgers, Rüdiger; Mitchell, Catherine; Boss, Emmanuel; Bricaud, Annick; Tilstone, Gavin

2017-11-27

Measurements of the absorption coefficient of chromophoric dissolved organic matter (ay) are needed to validate existing ocean-color algorithms. In the surface open ocean, these measurements are challenging because of low ay values. Yet, existing global datasets demonstrate that ay could contribute between 30% to 50% of the total absorption budget in the 400-450 nm spectral range, thus making accurate measurement of ay essential to constrain these uncertainties. In this study, we present a simple way of determining ay using a commercially-available in-situ spectrophotometer operated in underway mode. The obtained ay values were validated using independent collocated measurements. The method is simple to implement, can provide measurements with very high spatio-temporal resolution, and has an accuracy of about 0.0004 m -1 and a precision of about 0.0025 m -1 when compared to independent data (at 440 nm). The only limitation for using this method at sea is that it relies on the availability of relatively large volumes of ultrapure water. Despite this limitation, the method can deliver the ay data needed for validating and assessing uncertainties in ocean-colour algorithms.

Long-term evaluation of three satellite ocean color algorithms for identifying harmful algal blooms (Karenia brevis) along the west coast of Florida: A matchup assessment

PubMed Central

Carvalho, Gustavo A.; Minnett, Peter J.; Banzon, Viva F.; Baringer, Warner; Heil, Cynthia A.

2011-01-01

We present a simple algorithm to identify Karenia brevis blooms in the Gulf of Mexico along the west coast of Florida in satellite imagery. It is based on an empirical analysis of collocated matchups of satellite and in situ measurements. The results of this Empirical Approach is compared to those of a Bio-optical Technique – taken from the published literature – and the Operational Method currently implemented by the NOAA Harmful Algal Bloom Forecasting System for K. brevis blooms. These three algorithms are evaluated using a multi-year MODIS data set (from July, 2002 to October, 2006) and a long-term in situ database. Matchup pairs, consisting of remotely-sensed ocean color parameters and near-coincident field measurements of K. brevis concentration, are used to assess the accuracy of the algorithms. Fair evaluation of the algorithms was only possible in the central west Florida shelf (i.e. between 25.75°N and 28.25°N) during the boreal Summer and Fall months (i.e. July to December) due to the availability of valid cloud-free matchups. Even though the predictive values of the three algorithms are similar, the statistical measure of success in red tide identification (defined as cell counts in excess of 1.5 × 104 cells L−1) varied considerably (sensitivity—Empirical: 86%; Bio-optical: 77%; Operational: 26%), as did their effectiveness in identifying non-bloom cases (specificity—Empirical: 53%; Bio-optical: 65%; Operational: 84%). As the Operational Method had an elevated frequency of false-negative cases (i.e. presented low accuracy in detecting known red tides), and because of the considerable overlap between the optical characteristics of the red tide and non-bloom population, only the other two algorithms underwent a procedure for further inspecting possible detection improvements. Both optimized versions of the Empirical and Bio-optical algorithms performed similarly, being equally specific and sensitive (~70% for both) and showing low levels of uncertainties (i.e. few cases of false-negatives and false-positives: ~30%)—improved positive predictive values (~60%) were also observed along with good negative predictive values (~80%). PMID:22180667

SeaWiFS Technical Report Series. Volume 29; The SeaWiFS CZCS-Type Pigment Algorithm

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Aiken, James; Moore, Gerald F.; Trees, Charles C.; Clark, Dennis K.

1995-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission will provide operational ocean color that will be superior to the previous Coastal Zone Color Sensor (CZCS) proof-of-concept mission. An algorithm is needed that exploits the full functionality of SeaWiFS whilst remaining compatible in concept with algorithms used for the CZCS. This document describes the theoretical rationale of radiance band-ratio methods for determining chlorophyll-a and other important biogeochemical parameters, and their implementation for the SeaWIFS mission. Pigment interrelationships are examined to explain the success of the CZCS algorithms. In the context where chlorophyll-a absorbs only weakly at 520 nm, the success of the 520 nm to 550 nm CZCS band ratio needs to be explained. This is explained by showing that in pigment data from a range of oceanic provinces chlorophyll-a (absorbing at less than 490 nm), carotenoids (absorbing at greater than 460 nm), and total pigment are highly correlated. Correlations within pigment groups particularly photoprotectant and photosynthetic carotenoids are less robust. The sources of variability in optical data are examined using the NIMBUS Experiment Team (NET) bio-optical data set and bio-optical model. In both the model and NET data, the majority of the variance in the optical data is attributed to variability in pigment (chlorophyll-a), and total particulates, with less than 5% of the variability resulting from pigment assemblage. The relationships between band ratios and chlorophyll is examined analytically, and a new formulation based on a dual hyperbolic model is suggested which gives a better calibration curve than the conventional log-log linear regression fit. The new calibration curve shows the 490:555 ratio is the best single-band ratio and is the recommended CZCS-type pigment algorithm. Using both the model and NET data, a number of multiband algorithms are developed; the best of which is an algorithm based on the 443:555 and 490:555 ratios. From model data, the form of potential algorithms for other products, such as total particulates and dissolved organic matter (DOM), are suggested.

SeaWiFS Technical Report Series. Volume 29: SeaWiFS CZCS-type pigment algorithm

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Aiken, James; Moore, Gerald F.; Trees, Charles C.; Clark, Dennis K.

1995-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission will provide operational ocean color that will be superior to the previous Coastal Zone Color Sensor (CZCS) proof-of-concept mission. an algorithm is needed that exploits the full functionality of SeaWiFS whilst remaining compatible in concept with algorithms used for the CZCS. This document describes the theoretical rationale of radiance band-radio methods for determining chlorophyll alpha and other important biogeochemical parameters, and their implementation for the SeaWiFS mission. Pigment interrelationships are examined to explain the success of the CZCS algorithms. In the context where chlorophyll alpha absorbs only weakly at 520 nm, the success of the 520 nm to 550 nm CZCS band ratio needs to be explained. This is explained by showing that in pigment data from a range of oceanic provinces chlorophyll alpha (absorbing at less than 490 nm), carotenoids (absorbing at greater than 460 nm), and total pigment are highly correlated. Correlations within pigment groups particularly photoprotectant and photosynthetic carotenoids are less robust. The sources of variability in optical data re examined using the NIMBUS Experiment Team (NET) bio-optical data set and bio-optical model. In both the model and NET data, the majority of the variance in the optical data is attributed to variability in pigment (chlorophyll alpha, and total particulates, with less than 5% of the variability resulting from pigment assemblage. The relationships between band ratios and chlorophyll is examined analytically, and a new formulation based on a dual hyperbolic model is suggested which gives a better calibration curve than the conventional log-log linear regression fit. The new calibration curve shows that 490:555 ratio is the best single-band ratio and is the recommended CZCS-type pigment algorithm. Using both the model and NET data, a number of multiband algorithms are developed; the best of which is an algorithm based on the 443:555 and 490:555 ratios. From model data, the form of potential algorithms for other products, such as total particulates and dissolved organic matter (DOM), are suggested.

Role of oceanic air bubbles in atmospheric correction of ocean color imagery.

PubMed

Yan, Banghua; Chen, Bingquan; Stamnes, Knut

2002-04-20

Ocean color is the radiance that emanates from the ocean because of scattering by chlorophyll pigments and particles of organic and inorganic origin. Air bubbles in the ocean also scatter light and thus contribute to the water-leaving radiance. This additional water-leaving radiance that is due to oceanic air bubbles could violate the black pixel assumption at near-infrared wavelengths and be attributed to chlorophyll in the visible. Hence, the accuracy of the atmospheric correction required for the retrieval of ocean color from satellite measurements is impaired. A comprehensive radiative transfer code for the coupled atmosphere--ocean system is employed to assess the effect of oceanic air bubbles on atmospheric correction of ocean color imagery. This effect is found to depend on the wavelength-dependent optical properties of oceanic air bubbles as well as atmospheric aerosols.

Role of oceanic air bubbles in atmospheric correction of ocean color imagery

NASA Astrophysics Data System (ADS)

Yan, Banghua; Chen, Bingquan; Stamnes, Knut

2002-04-01

Ocean color is the radiance that emanates from the ocean because of scattering by chlorophyll pigments and particles of organic and inorganic origin. Air bubbles in the ocean also scatter light and thus contribute to the water-leaving radiance. This additional water-leaving radiance that is due to oceanic air bubbles could violate the black pixel assumption at near-infrared wavelengths and be attributed to chlorophyll in the visible. Hence, the accuracy of the atmospheric correction required for the retrieval of ocean color from satellite measurements is impaired. A comprehensive radiative transfer code for the coupled atmosphere-ocean system is employed to assess the effect of oceanic air bubbles on atmospheric correction of ocean color imagery. This effect is found to depend on the wavelength-dependent optical properties of oceanic air bubbles as well as atmospheric aerosols.

Ocean color - Availability of the global data set

NASA Technical Reports Server (NTRS)

Feldman, Gene; Kuring, Norman; Ng, Carolyn; Esaias, Wayne; Mcclain, Chuck; Elrod, Jane; Maynard, Nancy; Endres, Dan

1989-01-01

The use of satellite observations of ocean color to provide reliable estimates of marine phytoplankton biomass on synoptic scales is examined. An overview is given of the Coastal Zone Color Scanner data processing system. The archiving and distribution of ocean color data are discussed, and NASA-sponsored archive sites are listed.

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Siegel, D. A.; Maritorena, S.; Nelson, N. B.

2003-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-theart ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case I1 environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. The PnB field program started in the summer of 1996. At each of the 7 PnB stations, a complete verification bio-geo-optical data set is collected. Included are redundant measures of apparent optical properties (remote sensing reflectance and diffuse attenuation spectra), as well as in situ profiles of spectral absorption, beam attenuation and backscattering coefficients. Water samples are analyzed for component in vivo absorption spectra, fluorometric chlorophyll, phytoplankton pigment (by the SDSU CHORS laboratory), and inorganic nutrient concentrations (Table 1). A primary goal is to use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). In support of this goal, we have also been addressing SeaWiFS ocean color and AVHRR SST imagery (Otero and Siegel, 2003). We also are using the PnB data set to address time/space variability of water masses in the Santa Barbara Channel and its relationship to the 1997/1998 El Niiio. However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance, LwN(h), correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions. Last, we remain active in outreach activities.

Plumes and Blooms: Modeling the Case II Waters of the Santa Barbara Channel. Chapter 15

NASA Technical Reports Server (NTRS)

Siegel, D. A.; Maritorena, S.; Nelson, N. B.

2003-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. The PnB field program started in the summer of 1996. At each of the 7 PnB stations, a complete verification bio-geo-optical data set is collected. Included are redundant measures of apparent optical properties (remote sensing reflectance and diffuse attenuation spectra), as well as in situ profiles of spectral absorption, beam attenuation and backscattering coefficients. Water samples are analyzed for component in vivo absorption spectra, fluorometric chlorophyll, phytoplankton pigment (by the SDSU CHORS laboratory), and inorganic nutrient concentrations. A primary goal is to use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). In support of this goal, we have also been addressing SeaWiFS ocean color and AVHRR SST imagery. We also are using the PnB data set to address time/space variability of water masses in the Santa Barbara Channel and its relationship to the 1997/1998 El Nino. However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance, L(sub wN)(lambda), correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions. Last, we remain active in outreach activities.

SeaWiFS calibration and validation plan, volume 3

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Mcclain, Charles R.; Esaias, Wayne E.; Barnes, William; Guenther, Bruce; Endres, Daniel; Mitchell, B. Greg; Barnes, Robert

1992-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will be the first ocean-color satellite since the Nimbus-7 Coastal Zone Color Scanner (CZCS), which ceased operation in 1986. Unlike the CZCS, which was designed as a proof-of-concept experiment, SeaWiFS will provide routine global coverage every 2 days and is designed to provide estimates of photosynthetic concentrations of sufficient accuracy for use in quantitative studies of the ocean's primary productivity and biogeochemistry. A review of the CZCS mission is included that describes that data set's limitations and provides justification for a comprehensive SeaWiFS calibration and validation program. To accomplish the SeaWiFS scientific objectives, the sensor's calibration must be constantly monitored, and robust atmospheric corrections and bio-optical algorithms must be developed. The plan incorporates a multi-faceted approach to sensor calibration using a combination of vicarious (based on in situ observations) and onboard calibration techniques. Because of budget constraints and the limited availability of ship resources, the development of the operational algorithms (atmospheric and bio-optical) will rely heavily on collaborations with the Earth Observing System (EOS), the Moderate Resolution Imaging Spectrometer (MODIS) oceans team, and projects sponsored by other agencies, e.g., the U.S. Navy and the National Science Foundation (NSF). Other elements of the plan include the routine quality control of input ancillary data (e.g., surface wind, surface pressure, ozone concentration, etc.) used in the processing and verification of the level-0 (raw) data to level-1 (calibrated radiances), level-2 (derived products), and level-3 (gridded and averaged derived data) products.

Sensitivity of Calibration Gains to Ocean Color Processing in Coastal and Open Waters Using Ensembles Members for NPP-VIIRS

DTIC Science & Technology

2014-07-01

a different impact on spectral normalized water leaving radiances and the derived ocean color products (inherent optical properties, chlorophyll ). We...leaving radiances and the derived ocean color products (inherent optical properties, chlorophyll ). We evaluated the influence of gains from open and...34gain" on ocean color products. These products include the spectral Remote Sensing Reflectance (RRS), chlorophyll concentration, and Inherent Optical

SeaWiFS Postlaunch Technical Report Series. Volume 2; AMT-5 Cruise Report

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Aiken, James; Cummings, Denise G.; Gibb, Stuart W.; Rees, Nigel W.; Woodd-Walker, Rachel; Woodward, E. Malcolm S.; Woolfenden, James; Berthon, Jean-Francois;

NASA In Situ Data Needs to Support the Operational Calibration and Validation of Ocean Color Satellite Data Products

NASA Technical Reports Server (NTRS)

Werdel, P. Jeremy

2012-01-01

Calibrating ocean color satellite instruments and validating their data products requires temporal and spatial abundances of high quality in situ oceanographic data. The Consortium for Ocean Leadership Ocean Observing Initiative (OOl) is currently implementing a distributed array of in-water sensors that could provide a significant contribution to future ocean color activities. This workshop will scope the optimal way to use and possibly supplement the planned OOl infrastructure to maximize its utility and relevance for calibration and validation activities that support existing and planned NASA ocean color missions. Here, I present the current state of the art of NASA validation of ocean color data products, with attention to autonomous time-series (e.g., the AERONET -OC network of above-water radiometers), and outline NASA needs for data quality assurance metrics and adherence to community-vetted data collection protocols

Seasonal and Inter-Annual Patterns of Chlorophyll and Phytoplankton Community Structure in Monterey Bay, CA Derived from AVIRIS Data During the 2013-2015 HyspIRI Airborne Campaign

NASA Astrophysics Data System (ADS)

Palacios, S. L.; Thompson, D. R.; Kudela, R. M.; Negrey, K.; Guild, L. S.; Gao, B. C.; Green, R. O.; Torres-Perez, J. L.

2016-02-01

There is a need in the ocean color community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand ocean biodiversity, track energy flow through ecosystems, and identify and monitor for harmful algal blooms. Imaging spectrometer measurements enable the use of sophisticated spectroscopic algorithms for applications such as differentiating among coral species and discriminating phytoplankton taxa. These advanced algorithms rely on the fine scale, subtle spectral shape of the atmospherically corrected remote sensing reflectance (Rrs) spectrum of the ocean surface. Consequently, these algorithms are sensitive to inaccuracies in the retrieved Rrs spectrum that may be related to the presence of nearby clouds, inadequate sensor calibration, low sensor signal-to-noise ratio, glint correction, and atmospheric correction. For the HyspIRI Airborne Campaign, flight planning considered optimal weather conditions to avoid flights with significant cloud/fog cover. Although best suited for terrestrial targets, the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) has enough signal for some coastal chlorophyll algorithms and meets sufficient calibration requirements for most channels. The coastal marine environment has special atmospheric correction needs due to error introduced by aerosols and terrestrially sourced atmospheric dust and riverine sediment plumes. For this HyspIRI campaign, careful attention has been given to the correction of AVIRIS imagery of the Monterey Bay to optimize ocean Rrs retrievals to estimate chlorophyll (OC3) and phytoplankton functional type (PHYDOTax) data products. This new correction method has been applied to several image collection dates during two oceanographic seasons in 2013 and 2014. These two periods are dominated by either diatom blooms or red tides. Results to be presented include chlorophyll and phytoplankton community structure and in-water validation data for these dates during the two seasons.

Evaluation of VIIRS ocean color products

NASA Astrophysics Data System (ADS)

Wang, Menghua; Liu, Xiaoming; Jiang, Lide; Son, SeungHyun; Sun, Junqiang; Shi, Wei; Tan, Liqin; Naik, Puneeta; Mikelsons, Karlis; Wang, Xiaolong; Lance, Veronica

2014-11-01

The Suomi National Polar-orbiting Partnership (SNPP) was successfully launched on October 28, 2011. The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP, which has 22 spectral bands (from visible to infrared) similar to the NASA's Moderate Resolution Imaging Spectroradiometer (MODIS), is a multi-disciplinary sensor providing observations for the Earth's atmosphere, land, and ocean properties. In this paper, we provide some evaluations and assessments of VIIRS ocean color data products, or ocean color Environmental Data Records (EDR), including normalized water-leaving radiance spectra nLw(λ) at VIIRS five spectral bands, chlorophyll-a (Chl-a) concentration, and water diffuse attenuation coefficient at the wavelength of 490 nm Kd(490). Specifically, VIIRS ocean color products derived from the NOAA Multi-Sensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system are evaluated and compared with MODIS ocean color products and in situ measurements. MSL12 is now NOAA's official ocean color data processing system for VIIRS. In addition, VIIRS Sensor Data Records (SDR or Level- 1B data) have been evaluated. In particular, VIIRS SDR and ocean color EDR have been compared with a series of in situ data from the Marine Optical Buoy (MOBY) in the waters off Hawaii. A notable discrepancy of global deep water Chl-a derived from MODIS and VIIRS between 2012 and 2013 is observed. This discrepancy is attributed to the SDR (or Level-1B data) calibration issue and particularly related to VIIRS green band at 551 nm. To resolve this calibration issue, we have worked on our own sensor calibration by combining the lunar calibration effect into the current calibration method. The ocean color products derived from our new calibrated SDR in the South Pacific Gyre show that the Chl-a differences between 2012 and 2013 are significantly reduced. Although there are still some issues, our results show that VIIRS is capable of providing high-quality global ocean color products in support of science research and operational applications. The VIIRS evaluation and monitoring results can be found at the website: http://www.star.nesdis.noaa.gov/sod/mecb/color/index.html.

Variability of particulate organic carbon concentration in the north polar Atlantic based on ocean color observations with Sea-viewing Wide Field-of-view Sensor (SeaWiFS)

NASA Technical Reports Server (NTRS)

Stramska, Malgorzata; Stramski, Dariusz

2005-01-01

We use satellite data from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) to investigate distributions of particulate organic carbon (POC) concentration in surface waters of the north polar Atlantic Ocean during the spring summer season (April through August) over a 6-year period from 1998 through 2003. By use of field data collected at sea, we developed regional relationships for the purpose of estimating POC from remote-sensing observations of ocean color. Analysis of several approaches used in the POC algorithm development and match-up analysis of coincident in situ derived and satellite-derived estimates of POC resulted in selection of an algorithm that is based on the blue-to-green ratio of remote-sensing reflectance R(sub rs) (or normalized water-leaving radiance L(sub wn)). The application of the selected algorithm to a 6-year record of SeaWiFS monthly composite data of L(sub wn) revealed patterns of seasonal and interannual variability of POC in the study region. For example, the results show a clear increase of POC throughout the season. The lowest values, generally less than 200 mg per cubic meters, and at some locations often less than 50 mg per cubic meters, were observed in April. In May and June, POC can exceed 300 or even 400 mg per cubic meters in some parts of the study region. Patterns of interannual variability are intricate, as they depend on the geographic location within the study region and particular time of year (month) considered. By comparing the results averaged over the entire study region and the entire season (April through August) for each year separately, we found that the lowest POC occurred in 2001 and the highest POC occurred in 2002 and 1999.

Diurnal changes in ocean color sensed in satellite imagery

NASA Astrophysics Data System (ADS)

Arnone, Robert; Vandermuelen, Ryan; Soto, Inia; Ladner, Sherwin; Ondrusek, Michael; Yang, Haoping

2017-07-01

Measurements of diurnal changes in ocean color in turbid coastal regions in the Gulf of Mexico were characterized using above water spectral radiometry from a National Aeronautics and Space Administration (aerosol robotic network-WaveCIS CSI-06) site that can provide 8 to 10 observations per day. Satellite capability to detect diurnal changes in ocean color was characterized using hourly overlapping afternoon orbits of the visual infrared imaging radiometer suite (VIIRS) Suomi National Polar-orbiting Partnership ocean color sensor and validated with in situ observations. The monthly cycle of diurnal changes was investigated for different water masses using VIIRS overlaps. Results showed the capability of satellite observations to monitor hourly color changes in coastal regions that can be impacted by vertical movement of optical layers, in response to tides, resuspension, and river plume dispersion. The spatial variability of VIIRS diurnal changes showed the occurrence and displacement of phytoplankton blooming and decaying processes. The diurnal change in ocean color was above 20%, which represents a 30% change in chlorophyll-a. Seasonal changes in diurnal ocean color for different water masses suggest differences in summer and winter responses to surface processes. The diurnal changes observed using satellite ocean color can be used to define the following: surface processes associated with biological activity, vertical changes in optical depth, and advection of water masses.

The color metamerism evaluation of paint based on ocean spectrum

NASA Astrophysics Data System (ADS)

Chen, Zhongwei; Huang, Hao; Liao, Ningfang

2018-03-01

The surface color of the sea is affected by many factors and will be different the due to the material difference in the sea. And the difference will be reflected in the ocean spectrum. If the paint materials of a ship can simulate the ocean surface color and the ocean spectrum at the same time. This will minimize the metamerism. In this paper, the method of metamerism is used to evaluate paint based on ocean spectrum, so that the color of the material affected by the light source will be reflected in the metamerism index.

Influence of CDOM and particle composition on ocean color of the Eastern New Caledonia Lagoon during the CALIOPE cruises

NASA Astrophysics Data System (ADS)

Dupouy, Cécile; Röttgers, Rüdiger; Tedetti, Marc; Martias, Chloe; Murakami, Hiroshi; Doxaran, David; Lantoine, Francois; Rodier, Martine; Favareto, Luciane; Kampel, Milton; Goutx, Madeleine; Frouin, Robert J.

2014-11-01

Ocean color of tropical lagoons is dependent on bathymetry and bottom type, as well as input of coastal living and mineral particles and chromophoric dissolved organic matter (CDOM). The New Caledonia lagoon lies in the Southwestern Tropical Pacific around 21° 30'S and 166° 30'E, with a great marine biodiversity in UNESCO Heritage coral reefs, benthic sea grass, and benthic communities. They are largely connected to the open ocean in the southern and eastern parts, but only by narrow passes in the southwest part. The trophic state is linked to spatial variations in flushing times. High run offs due to rain carrying abundant chromophoric dissolved organic matter (CDOM) and particle loads may greatly impact the functioning of ecosystems while rivers and sewage effluents may induce localized impacts. Two oceanographic cruises (CALIOPE 1 in 2011 and CALIOPE 2 in 2014) were carried out off the Eastern Coast of New Caledonia during a calm dry period and during high winds, respectively. Multi- and hyper-spectral marine reflectance was measured with a SIMBADA instrument and a TRIOS radiometer system, together with inherent optical properties (total and CDOM absorption coefficients with a PSICAM, in situ absorption and scattering with an AC9, backscattering with a Hydroscat-6). Fluorescence of CDOM (EEM/PARAFAC) was measured on collected 0.2 μm filtered samples. In 2014, Satlantic and FieldSpec hyper-spectral radiometers were available for in-water profiling of upwelling radiance and downwelling irradiance and above-water reflectance measurements, respectively. Inherent and apparent optical data from the two cruises are compared and used to estimate ocean color algorithms performance and evaluate a Linear Matrix Inversion method, providing tools for remote sensing on this highly under-sampled coastal region of New Caledonia.

Satellite Remote Sensing Studies of Biological and Biogeochemical Processing in the Ocean

NASA Technical Reports Server (NTRS)

Vernet, Maria

2001-01-01

The remote sensing of phycoerythrin-containing phytoplankton by ocean color was evaluated. Phycoerythrin (PE) can be remotely sensed by three methods: surface reflectance (Sathyendranath et al. 1994), by laser-activated fluorescence (Hoge and Swift 1986) and by passive fluorescence (Letelier et al. 1996). In collaboration with Dr. Frank Hoge and Robert Swift during Dr. Maria Vernet's tenure as Senior Visiting Scientist at Wallops Island, the active and passive methods were studied, in particular the detection of PE fluorescence and spectral reflectance from airborne LIDAR (AOL). Airborne instrumentation allows for more detailed and flexible sampling of the ocean surface than satellites thus providing the ideal platform to test model and develop algorithms than can later be applied to ocean color by satellites such as TERRA and AQUA. Dr. Vernet's contribution to the Wallops team included determination of PE in the water column, in conjunction with AOL flights in the North Atlantic Bight. In addition, a new flow-through fluorometer for PE determination by fluorescence was tested and calibrated. Results: several goals were achieved during this period. Cruises to the California Current, North Atlantic Bight, Gulf of Maine and Chesapeake Bay provided sampling under different oceanographic and optical conditions. The ships carried the flow-through fluorometer and samples for the determination of PE were obtained from the flow-through flow. The AOL was flown over the ship's track, usually several flights during the cruise, weather permitting.

FLIPPER: Validation for Remote Ocean Imaging

NASA Technical Reports Server (NTRS)

2006-01-01

one of the determining factors in the planet s ability to support life is the same factor that makes the Blue Planet blue: water. Therefore, NASA researchers have a focused interest in understanding Earth s oceans and their ability to continue sustaining life. A critical objective in this study is to understand the global processes that control the changes of carbon and associated living elements in the oceans. Since oceans are so large, one of the most widely used methods of this research is remote sensing, using satellites to observe changes in the ocean color that may be indicative of changes occurring at the surface. Major changes in carbon are due to photosynthesis conducted by phytoplankton, showing, among other things, which areas are sustaining life. Although valuable for large-scale pictures of an ocean, remote sensing really only provides a surface, and therefore incomplete, depiction of that ocean s sustainability. True and complete testing of the water requires local testing in conjunction with the satellite images in order to generate the necessary algorithm parameters to calculate ocean health. For this reason, NASA has spearheaded research to provide onsite validation for its satellite imagery surveys.

Suspended sediment concentration and optical property observations of mixed-turbidity, coastal waters through multispectral ocean color inversion

EPA Science Inventory

Multispectral satellite ocean color data from high-turbidity areas of the coastal ocean contain information about the surface concentrations and optical properties of suspended sediments and colored dissolved organic matter (CDOM). Empirical and semi-analytical inversion algorit...

SeaWinds - Oceans, Land, Polar Regions

NASA Technical Reports Server (NTRS)

1999-01-01

The SeaWinds scatterometer on the QuikScat satellite makes global radar measurements -- day and night, in clear sky and through clouds. The radar data over the oceans provide scientists and weather forecasters with information on surface wind speed and direction. Scientists also use the radar measurements directly to learn about changes in vegetation and ice extent over land and polar regions.

This false-color image is based entirely on SeaWinds measurements obtained over oceans, land, and polar regions. Over the ocean, colors indicate wind speed with orange as the fastest wind speeds and blue as the slowest. White streamlines indicate the wind direction. The ocean winds in this image were measured by SeaWinds on September 20, 1999. The large storm in the Atlantic off the coast of Florida is Hurricane Gert. Tropical storm Harvey is evident as a high wind region in the Gulf of Mexico, while farther west in the Pacific is tropical storm Hilary. An extensive storm is also present in the South Atlantic Ocean near Antarctica.

The land image was made from four days of SeaWinds data with the aid of a resolution enhancement algorithm developed by Dr. David Long at Brigham Young University. The lightest green areas correspond to the highest radar backscatter. Note the bright Amazon and Congo rainforests compared to the dark Sahara desert. The Amazon River is visible as a dark line running horizontally though the bright South American rain forest. Cities appear as bright spots on the images, especially in the U.S. and Europe.

The image of Greenland and the north polar ice cap was generated from data acquired by SeaWinds on a single day. In the polar region portion of the image, white corresponds to the largest radar return, while purple is the lowest. The variations in color in Greenland and the polar ice cap reveal information about the ice and snow conditions present.

NASA's Earth Science Enterprise is a long-term research and technology program designed to examine Earth's land, oceans, atmosphere, ice and life as a total integrated system. JPL is a division of the California Institute of Technology, Pasadena, CA.

Measurements of ocean color

NASA Technical Reports Server (NTRS)

Hovis, W. A.

1972-01-01

An airborne instrument for determining ocean color and measurements made with the instrument are discussed. It was concluded that a clear relationship exists between the chlorophyll concentration and the color of the water. High altitude measurements from 50,000 feet are described and the effects of atmospheric scattering on the energy reaching the sensor are examined. The measured spectrum of ocean color at high and low altitudes is plotted.

Ocean Color Data at the Goddard DAAC

NASA Technical Reports Server (NTRS)

1999-01-01

The apparent color of the ocean is determined by the interactions of incident light with substances or particles present in the water. The most significant constituents are free-floating photosynthetic organisms (phytoplankton) and inorganic particulates. Phytoplankton contain chlorophyll, which absorbs light at blue and red wavelengths and transmits in the green. Particulate matter can reflect and absorb light, which reduces the clarity (light transmission) of the water. Substances dissolved in water can also affect its color. Observations of ocean color from space, utilizing sensors specially designed to detect the small amount of light radiating from the sea surface, provide a global picture of the patterns of biological productivity in the world's oceans. For that reason, ocean color remote sensing data is a vital resource for biological oceanography. Unlike the limited area of the ocean that can be investigated from a research ship, data from a satellite sensor covers a large region and provides a comprehensive view of the marine environment.

SeaWiFS technical report series. Volume 17: Ocean color in the 21st century. A strategy for a 20-year time series

NASA Technical Reports Server (NTRS)

Abbott, Mark R.; Brown, Otis B.; Evans, Robert H.; Gordon, Howard R.; Carder, Kendall L.; Mueller-Karger, Frank E.; Esaias, Wayne E.; Hooker, Stanford B.; Firestone, Elaine R.

1994-01-01

Beginning with the upcoming launch of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), there should be almost continuous measurements of ocean color for nearly 20 years if all of the presently planned national and international missions are implemented. This data set will present a unique opportunity to understand the coupling of physical and biological processes in the world ocean. The presence of multiple ocean color sensors will allow the eventual development of an ocean color observing system that is both cost effective and scientifically based. This report discusses the issues involved and makes recommendations intended to ensure the maximum scientific return from this unique set of planned ocean color missions. An executive summary is included with this document which briefly discusses the primary issues and suggested actions to be considered.

Satellite Ocean Color: Present Status, Future Challenges

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; McClain, Charles R.; Zukor, Dorothy J. (Technical Monitor)

2001-01-01

We are midway into our 5th consecutive year of nearly continuous, high quality ocean color observations from space. The Ocean Color and Temperature Scanner/Polarization and Directionality of the Earth's Reflectances (OCTS/POLDER: Nov. 1996 - Jun. 1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS: Sep. 1997 - present), and now the Moderate Resolution Imaging Spectrometer (MODIS: Sep. 2000 - present) have and are providing unprecedented views of chlorophyll dynamics on global scales. Global synoptic views of ocean chlorophyll were once a fantasy for ocean color scientists. It took nearly the entire 8-year lifetime of limited Coastal Zone Color Scanner (CZCS) observations to compile seasonal climatologies. Now SeaWIFS produces comparably complete fields in about 8 days. For the first time, scientists may observe spatial and temporal variability never before seen in a synoptic context. Even more exciting, we are beginning to plausibly ask questions of interannual variability. We stand at the beginning of long-time time series of ocean color, from which we may begin to ask questions of interdecadal variability and climate change. These are the scientific questions being addressed by users of the 18-year Advanced Very High Resolution Radiometer time series with respect to terrestrial processes and ocean temperatures. The nearly 5-year time series of ocean color observations now being constructed, with possibilities of continued observations, can put us at comparable standing with our terrestrial and physical oceanographic colleagues, and enable us to understand how ocean biological processes contribute to, and are affected by global climate change.

Validation Test Report for the Automated Optical Processing System (AOPS) Version 4.12

DTIC Science & Technology

2015-09-03

NPP) with the VIIRS sensor package as well as data from the Geostationary Ocean Color Imager (GOCI) sensor, aboard the Communication Ocean and...capability • Prepare the NRT Geostationary Ocean Color Imager (GOCI) data stream for integration into operations. • Improvements in sensor...Navy (DON) Environmental Data Records (EDRs) Expeditionary Warfare (EXW) Geostationary Ocean Color Imager (GOCI) Gulf of Mexico (GOM) Hierarchical

Validation Test Report for the Automated Optical Processing System (AOPS) Version 4.12

DTIC Science & Technology

2015-09-03

the Geostationary Ocean Color Imager (GOCI) sensor, aboard the Communication Ocean and Meteorological Satellite (COMS) satellite. Additionally, this...this capability works in conjunction with AOPS • Improvements to the AOPS mosaicking capability • Prepare the NRT Geostationary Ocean Color Imager...Warfare (EXW) Geostationary Ocean Color Imager (GOCI) Gulf of Mexico (GOM) Hierarchical Data Format (HDF) Integrated Data Processing System (IDPS

High Frequency, Long Time Series Measurements from the Bermuda Testbed Mooring in Support of SIMBIOS. Chapter 8

NASA Technical Reports Server (NTRS)

Dickey, Tommy; Dobeck, Laura; Sigurdson, David; Zedler, Sarah; Manov, Derek; Yu, Xuri

2001-01-01

It has been recognized that optical moorings are important platforms for the validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS). It was recommended that optical moorings be maintained in order to: (1) provide long-term time series comparisons between in situ and SeaWIFS measurements of normalized water-leaving radiance; (2) develop and test algorithms for pigment biomass and phytoplankton primary productivity; and (3) provide long-term, virtually continuous in situ observations which can be used to determine and optimize the accuracy of derived satellite products. These applications require the use of in situ radiometers for long periods of time to evaluate and correct for inherent satellite undersampling (aliasing and biasing) and degradation of satellite color sensors (e.g., drifts as experienced by the Coastal Zone Color Scanner). The Bermuda Testbed Mooring (BTM) program was initiated in 1994 at a site located about 80km southeast of Bermuda in waters of about 4530 m depth. In August 1997, with NASA's support, we started to provide the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program with large volumes of high frequency, long-term time-series bio-optical data from the BTM for SeaWiFS satellite ocean color groundtruthing and algorithm development. This NASA supported portion of the BTM activity spanned three years and covered five BTM deployments. During these three years, the quality of radiometric data has improved dramatically. Excellent agreement between BTM moored data and both SeaWiFS and nearby ship profile radiometric data demonstrate that technical advances in the moored optical observations have reduced the major difficulties that moored platforms face: biofouling and less frequent calibration.

Inversion Schemes to Retrieve Atmospheric and Oceanic Parameters from SeaWiFS Data

NASA Technical Reports Server (NTRS)

Deschamps, P.-Y.; Frouin, R.

1997-01-01

The investigation focuses on two key issues in satellite ocean color remote sensing, namely the presence of whitecaps on the sea surface and the validity of the aerosol models selected for the atmospheric correction of SeaWiFS data. Experiments were designed and conducted at the Scripps Institution of Oceanography to measure the optical properties of whitecaps and to study the aerosol optical properties in a typical mid-latitude coastal environment. CIMEL Electronique sunphotometers, now integrated in the AERONET network, were also deployed permanently in Bermuda and in Lanai, calibration/validation sites for SeaWiFS and MODIS. Original results were obtained on the spectral reflectance of whitecaps and on the choice of aerosol models for atmospheric correction schemes and the type of measurements that should be made to verify those schemes. Bio-optical algorithms to remotely sense primary productivity from space were also evaluated, as well as current algorithms to estimate PAR at the earth's surface.

NASA COAST and OCEANIA Airborne Missions Support Ecosystem and Water Quality Research in the Coastal Zone

NASA Technical Reports Server (NTRS)

Guild, Liane; Kudela, Raphael; Hooker, Stanford; Morrow, John; Russell, Philip; Palacios, Sherry; Livingston, John M.; Negrey, Kendra; Torres-Perez, Juan; Broughton, Jennifer

2014-01-01

NASA has a continuing requirement to collect high-quality in situ data for the vicarious calibration of current and next generation ocean color satellite sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal is to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. The imaging spectrometer (Headwall) is optimized in the blue spectral domain to emphasize remote sensing of marine and freshwater ecosystems. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data are accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research.

Assessment and application of AirMSPI high-resolution multiangle imaging photo-polarimetric observations for atmospheric correction

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Xu, F.; Garay, M. J.; Seidel, F. C.; Diner, D. J.

2016-02-01

Water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Modern improvements have been developed in ocean color retrieval algorithms to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean. In addition, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error in the retrieved water leaving radiance. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The Airborne Multiangle SpectroPolarimetric Imager-1 (AirMSPI-1) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI typically acquires observations of a target area at 9 view angles between ±67° at 10 m resolution. AirMSPI spectral channels are centered at 355, 380, 445, 470, 555, 660, and 865 nm, with 470, 660, and 865 reporting linear polarization. We have developed a retrieval code that employs a coupled Markov Chain (MC) and adding/doubling radiative transfer method for joint retrieval of aerosol properties and water leaving radiance from AirMSPI polarimetric observations. We tested prototype retrievals by comparing the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentrations to values reported by the USC SeaPRISM AERONET-OC site off the coast of California. The retrieval then was applied to a variety of costal regions in California to evaluate variability in the water-leaving radiance under different atmospheric conditions. We will present results, and will discuss algorithm sensitivity and potential applications for future space-borne coastal monitoring.

Mapping the low salinity Changjiang Diluted Water using satellite-retrieved colored dissolved organic matter (CDOM) in the East China Sea during high river flow season

NASA Astrophysics Data System (ADS)

Sasaki, Hiroaki; Siswanto, Eko; Nishiuchi, Kou; Tanaka, Katsuhisa; Hasegawa, Toru; Ishizaka, Joji

2008-02-01

Absorption coefficients of colored dissolved organic matter (CDOM) [a g(λ)] were measured and relationship with salinity was derived in the East China Sea (ECS) during summer when amount of the Changjiang River discharge is large. Low salinity Changjiang Diluted Water (CDW) was observed widely in the shelf region and was considered to be the main origin of CDOM, resulting in a strong relationship between salinity and a g(λ). Error of satellite a g(λ) estimated by the present ocean color algorithm could be corrected by satellite-retrieved chlorophyll data. Satellite-retrieved salinity could be predicted with about +/-1.0 accuracy from satellite a g(λ) and the relation between salinity and a g(λ). Our study suggests that satellite-derived a g(λ) can be an indicator of the low salinity CDW during summer.

Validation Test Report for the Automated Optical Processing System (AOPS) Version 4.10

DTIC Science & Technology

2015-08-25

Geostationary Ocean Color Imager (GOCI) sensors. AOPS enables exploitation of multiple space-borne ocean color satellite sensors to provide optical...package as well as from the Geostationary Ocean Color Imager (GOCI) sensor aboard the Communication Ocean and Meteorological Satellite (COMS) satellite... GEOstationary Coastal and Air Pollution Events (GEO-CAPE) mission and provided to NRL courtesy of Mike Ondrusek and Zhongping Lee. AOP and IOP data were

Simple aerosol correction technique based on the spectral relationships of the aerosol multiple-scattering reflectances for atmospheric correction over the oceans.

PubMed

Ahn, Jae-Hyun; Park, Young-Je; Kim, Wonkook; Lee, Boram

2016-12-26

An estimation of the aerosol multiple-scattering reflectance is an important part of the atmospheric correction procedure in satellite ocean color data processing. Most commonly, the utilization of two near-infrared (NIR) bands to estimate the aerosol optical properties has been adopted for the estimation of the effects of aerosols. Previously, the operational Geostationary Color Ocean Imager (GOCI) atmospheric correction scheme relies on a single-scattering reflectance ratio (SSE), which was developed for the processing of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data to determine the appropriate aerosol models and their aerosol optical thicknesses. The scheme computes reflectance contributions (weighting factor) of candidate aerosol models in a single scattering domain then spectrally extrapolates the single-scattering aerosol reflectance from NIR to visible (VIS) bands using the SSE. However, it directly applies the weight value to all wavelengths in a multiple-scattering domain although the multiple-scattering aerosol reflectance has a non-linear relationship with the single-scattering reflectance and inter-band relationship of multiple scattering aerosol reflectances is non-linear. To avoid these issues, we propose an alternative scheme for estimating the aerosol reflectance that uses the spectral relationships in the aerosol multiple-scattering reflectance between different wavelengths (called SRAMS). The process directly calculates the multiple-scattering reflectance contributions in NIR with no residual errors for selected aerosol models. Then it spectrally extrapolates the reflectance contribution from NIR to visible bands for each selected model using the SRAMS. To assess the performance of the algorithm regarding the errors in the water reflectance at the surface or remote-sensing reflectance retrieval, we compared the SRAMS atmospheric correction results with the SSE atmospheric correction using both simulations and in situ match-ups with the GOCI data. From simulations, the mean errors for bands from 412 to 555 nm were 5.2% for the SRAMS scheme and 11.5% for SSE scheme in case-I waters. From in situ match-ups, 16.5% for the SRAMS scheme and 17.6% scheme for the SSE scheme in both case-I and case-II waters. Although we applied the SRAMS algorithm to the GOCI, it can be applied to other ocean color sensors which have two NIR wavelengths.

The Yellow Sea [high res

NASA Image and Video Library

2015-02-27

Remote sensing of ocean color in the Yellow Sea can be a challenge. Phytoplankton, suspended sediments, and dissolved organic matter color the water while various types of aerosols modify those colors before they are "seen" by orbiting radiometers. The Aqua-MODIS data used to create the above image were collected on February 24, 2015. NASA's OceanColor Web is supported by the Ocean Biology Processing Group (OBPG) at NASA's Goddard Space Flight Center. Our responsibilities include the collection, processing, calibration, validation, archive and distribution of ocean-related products from a large number of operational, satellite-based remote-sensing missions providing ocean color, sea surface temperature and sea surface salinity data to the international research community since 1996. Credit: NASA/Goddard/Ocean Color NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Comment on 'Aerosol and Rayleigh radiance contributions to Coastal Zone Colour Scanner images' by Eckstein and Simpson

NASA Technical Reports Server (NTRS)

Gordon, H. R.; Evans, R. H.

1993-01-01

In a recent paper Eckstein and Simpson describe what they believe to be serious difficulties and/or errors with the CZCS (Coastal Zone Color Scanner) processing algorithms based on their analysis of seven images. Here we point out that portions of their analysis, particularly those dealing with multiple scattered Rayleigh radiance, are incorrect. We also argue that other problems they discuss have already been addressed in the literature. Finally, we suggest that many apparent artifacts in CZCS-derived pigment fields are likely to be due to inadequacies in the sensor band set or to poor radiometric stability, both of which will be remedied with the next generation of ocean color sensors.

Applications of Geostationary Ocean Color Imager (GOCI) observations

NASA Astrophysics Data System (ADS)

Park, Y. J.

2016-02-01

Ocean color remote-sensing technique opened a new era for biological oceanography by providing the global distribution of phytoplankton biomass every a few days. It has been proved useful for a variety of applications in coastal waters as well as oceanic waters. However, most ocean color sensors deliver less than one image per day for low and middle latitude areas, and this once a day image is insufficient to resolve transient or high frequency processes. Korean Geostationary Ocean Color Imager (GOCI), the first ever ocean color instrument operated on geostationary orbit, is collecting ocean color radiometry (OCR) data (multi-band radiances at the visible to NIR spectral wavelengths) since July, 2010. GOCI has an unprecedented capability to provide eight OCR images a day with a 500m resolution for the North East Asian seas Monitoring the spatial and temporal variability is important to understand many processes occurring in open ocean and coastal environments. With a series of images consecutively acquired by GOCI, we are now able to look into (sub-)diurnal variabilities of coastal ocean color products such as phytoplankton biomass, suspended particles concentrations, and primary production. The eight images taken a day provide another way to derive maps of ocean current velocity. Compared to polar orbiters, GOCI delivers more frequent images with constant viewing angle, which enables to better monitor and thus respond to coastal water issues such as harmful algal blooms, floating green and brown algae. The frequent observation capability for local area allows us to respond timely to natural disasters and hazards. GOCI images are often useful to identify sea fog, sea ice, wild fires, volcanic eruptions, transport of dust aerosols, snow covered area, etc.

Ocean color modeling: Parameterization and interpretation

NASA Astrophysics Data System (ADS)

Feng, Hui

The ocean color as observed near the water surface is determined mainly by dissolved and particulate substances, known as "optically-active constituents," in the upper water column. The goal of ocean color modeling is to interpret an ocean color spectrum quantitatively to estimate the suite of optically-active constituents near the surface. In recent years, ocean color modeling efforts have been centering upon three major optically-active constituents: chlorophyll concentration, colored dissolved organic matter, and scattering particulates. Many challenges are still being faced in this arena. This thesis generally addresses and deals with some critical issues in ocean color modeling. In chapter one, an extensive literature survey on ocean color modeling is given. A general ocean color model is presented to identify critical candidate uncertainty sources in modeling the ocean color. The goal for this thesis study is then defined as well as some specific objectives. Finally, a general overview of the dissertation is portrayed, defining each of the follow-up chapters to target some relevant objectives. In chapter two, a general approach is presented to quantify constituent concentration retrieval errors induced by uncertainties in inherent optical property (IOP) submodels of a semi-analytical forward model. Chlorophyll concentrations are retrieved by inverting a forward model with nonlinear IOPs. The study demonstrates how uncertainties in individual IOP submodels influence the accuracy of the chlorophyll concentration retrieval at different chlorophyll concentration levels. The important finding for this study shows that precise knowledge of spectral shapes of IOP submodels is critical for accurate chlorophyll retrieval, suggesting an improvement in retrieval accuracy requires precise spectral IOP measurements. In chapter three, three distinct inversion techniques, namely, nonlinear optimization (NLO), principal component analysis (PCA) and artificial neural network (ANN) are compared to assess their inversion performances to retrieve optically-active constituents for a complex nonlinear bio-optical system simulated by a semi-analytical ocean color model. A well-designed simulation scheme was implemented to simulate waters of different bio-optical complexity, and then the three inversion methods were applied to these simulated datasets for performance evaluation. In chapter four, an approach is presented for optimally parameterizing an irradiance reflectance model on the basis of a bio-optical dataset made at 45 stations in the Tokyo Bay and nearby regions between 1982 and 1984. (Abstract shortened by UMI.)

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

NASA Technical Reports Server (NTRS)

Limbacher, James A.; Kahn, Ralph A.

2017-01-01

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Updated MISR dark water research aerosol retrieval algorithm - Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections

NASA Astrophysics Data System (ADS)

Limbacher, James A.; Kahn, Ralph A.

2017-04-01

As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m-3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov-Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mg m-3, MISR and MODIS show very good agreement: r = 0. 96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Theoretical and experimental analysis of laser altimeters for barometric measurements over the ocean

NASA Technical Reports Server (NTRS)

Tsai, B. M.; Gardner, C. S.

1984-01-01

The statistical characteristics and the waveforms of ocean-reflected laser pulses are studied. The received signal is found to be corrupted by shot noise and time-resolved speckle. The statistics of time-resolved speckle and its effects on the timing accuracy of the receiver are studied in the general context of laser altimetry. For estimating the differential propagation time, various receiver timing algorithms are proposed and their performances evaluated. The results indicate that, with the parameters of a realistic altimeter, a pressure measurement accuracy of a few millibars is feasible. The data obtained from the first airborne two-color laser altimeter experiment are processed and analyzed. The results are used to verify the pressure measurement concept.

Study on the cloud detection of GOCI by using the simulated surface reflectance from BRDF-model for the land application and meteorological utilization

NASA Astrophysics Data System (ADS)

Kim, Hye-Won; Yeom, Jong-Min; Woo, Sun-Hee; Chae, Tae-Byeong

2016-04-01

COMS (Communication, Ocean, and Meteorological Satellite) was launched at French Guiana Kourou space center on 27 June 2010. Geostationary Ocean Color Imager (GOCI), which is the first ocean color geostationary satellite in the world for observing the ocean phenomena, is able to obtain the scientific data per an hour from 00UTC to 07UTC. Moreover, the spectral channels of GOCI would enable not only monitoring for the ocean, but for extracting the information of the land surface over the Korean Peninsula, Japan, and Eastern China. Since it is extremely important to utilize GOCI data accurately for the land application, cloud pixels over the surface have to be removed. Unfortunately, infra-red (IR) channels that can easily detect the water vapor with the cloud top temperature, are not included in the GOCI sensor. In this paper, the advanced cloud masking algorithm will be proposed with visible and near-IR (NIR) bands that are within GOCI bands. The main obstacle of cloud masking with GOCI is how to handle the high variable surface reflectance, which is mainly depending on the solar zenith angle. In this study, we use semi-empirical BRDF model to simulate the surface reflectance by using 16 day composite cloudy free image. When estimating the simulated surface reflectance, same geometry for GOCI observation was applied. The simulated surface reflectance is used to discriminate cloud areas especially for the thin cloud and shows more reasonable result than original threshold methods.

The Living Ocean. SeaWiFS: Studying Ocean Color from Space. Teacher's Guide with Activities

NASA Technical Reports Server (NTRS)

1994-01-01

This educational document, designed for grades 9 to 10, discusses the observation of oceans from space. Topics covered include ocean color, the role of phytoplankton, the carbon cycle, and the greenhouse effect. Activities and discussion questions are presented.

Some Insights of Spectral Optimization in Ocean Color Inversion

NASA Technical Reports Server (NTRS)

Lee, Zhongping; Franz, Bryan; Shang, Shaoling; Dong, Qiang; Arnone, Robert

2011-01-01

In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented.

Statistical Evaluation of VIIRS Ocean Color Products

NASA Astrophysics Data System (ADS)

Mikelsons, K.; Wang, M.; Jiang, L.

2016-02-01

Evaluation and validation of satellite-derived ocean color products is a complicated task, which often relies on precise in-situ measurements for satellite data quality assessment. However, in-situ measurements are only available in comparatively few locations, expensive, and not for all times. In the open ocean, the variability in spatial and temporal scales is longer, and the water conditions are generally more stable. We use this fact to perform extensive statistical evaluations of consistency for ocean color retrievals based on comparison of retrieved data at different times, and corresponding to various retrieval parameters. We have used the NOAA Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system for ocean color product data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS). We show the results for statistical dependence of normalized water-leaving radiance spectra with respect to various parameters of retrieval geometry, such as solar- and sensor-zenith angles, as well as physical variables, such as wind speed, air pressure, ozone amount, water vapor, etc. In most cases, the results show consistent retrievals within the relevant range of retrieval parameters, showing a good performance with the MSL12 in the open ocean. The results also yield the upper bounds of solar- and sensor-zenith angles for reliable ocean color retrievals, and also show a slight increase of VIIRS-derived normalized water-leaving radiances with wind speed and water vapor concentration.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

NASA Astrophysics Data System (ADS)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Calibration Adjustments to the MODIS Aqua Ocean Color Bands

NASA Technical Reports Server (NTRS)

Meister, Gerhard

2012-01-01

After the end of the SeaWiFS mission in 2010 and the MERIS mission in 2012, the ocean color products of the MODIS on Aqua are the only remaining source to continue the ocean color climate data record until the VIIRS ocean color products become operational (expected for summer 2013). The MODIS on Aqua is well beyond its expected lifetime, and the calibration accuracy of the short wavelengths (412nm and 443nm) has deteriorated in recent years_ Initially, SeaWiFS data were used to improve the MODIS Aqua calibration, but this solution was not applicable after the end of the SeaWiFS mission_ In 2012, a new calibration methodology was applied by the MODIS calibration and support team using desert sites to improve the degradation trending_ This presentation presents further improvements to this new approach. The 2012 reprocessing of the MODIS Aqua ocean color products is based on the new methodology.

Automated Sargassum Detection for Landsat Imagery

NASA Astrophysics Data System (ADS)

McCarthy, S.; Gallegos, S. C.; Armstrong, D.

2016-02-01

We implemented a system to automatically detect Sargassum, a floating seaweed, in 30-meter LANDSAT-8 Operational Land Imager (OLI) imagery. Our algorithm for Sargassum detection is an extended form of Hu's approach to derive a floating algae index (FAI) [1]. Hu's algorithm was developed for Moderate Resolution Imaging Spectroradiometer (MODIS) data, but we extended it for use with the OLI bands centered at 655, 865, and 1609 nm, which are comparable to the MODIS bands located at 645, 859, and 1640 nm. We also developed a high resolution true color product to mask cloud pixels in the OLI scene by applying a threshold to top of the atmosphere (TOA) radiances in the red (655 nm), green (561 nm), and blue (443 nm) wavelengths, as well as a method for removing false positive identifications of Sargassum in the imagery. Hu's algorithm derives a FAI for each Sargassum identified pixel. Our algorithm is currently set to only flag the presence of Sargassum in an OLI pixel by classifying any pixel with a FAI > 0.0 as Sargassum. Additionally, our system geo-locates the flagged Sargassum pixels identified in the OLI imagery into the U.S. Navy Global HYCOM model grid. One element of the model grid covers an area 0.125 degrees of latitude by 0.125 degrees of longitude. To resolve the differences in spatial coverage between Landsat and HYCOM, a scheme was developed to calculate the percentage of pixels flagged within the grid element and if above a threshold, it will be flagged as Sargassum. This work is a part of a larger system, sponsored by NASA/Applied Science and Technology Project at J.C. Stennis Space Center, to forecast when and where Sargassum will land on shore. The focus area of this work is currently the Texas coast. Plans call for extending our efforts into the Caribbean. References: [1] Hu, Chuanmin. A novel ocean color index to detect floating algae in the global oceans. Remote Sensing of Environment 113 (2009) 2118-2129.

Atmospheric correction over coastal waters using multilayer neural networks

NASA Astrophysics Data System (ADS)

Fan, Y.; Li, W.; Charles, G.; Jamet, C.; Zibordi, G.; Schroeder, T.; Stamnes, K. H.

2017-12-01

Standard atmospheric correction (AC) algorithms work well in open ocean areas where the water inherent optical properties (IOPs) are correlated with pigmented particles. However, the IOPs of turbid coastal waters may independently vary with pigmented particles, suspended inorganic particles, and colored dissolved organic matter (CDOM). In turbid coastal waters standard AC algorithms often exhibit large inaccuracies that may lead to negative water-leaving radiances (Lw) or remote sensing reflectance (Rrs). We introduce a new atmospheric correction algorithm for coastal waters based on a multilayer neural network (MLNN) machine learning method. We use a coupled atmosphere-ocean radiative transfer model to simulate the Rayleigh-corrected radiance (Lrc) at the top of the atmosphere (TOA) and the Rrs just above the surface simultaneously, and train a MLNN to derive the aerosol optical depth (AOD) and Rrs directly from the TOA Lrc. The SeaDAS NIR algorithm, the SeaDAS NIR/SWIR algorithm, and the MODIS version of the Case 2 regional water - CoastColour (C2RCC) algorithm are included in the comparison with AERONET-OC measurements. The results show that the MLNN algorithm significantly improves retrieval of normalized Lw in blue bands (412 nm and 443 nm) and yields minor improvements in green and red bands. These results indicate that the MLNN algorithm is suitable for application in turbid coastal waters. Application of the MLNN algorithm to MODIS Aqua images in several coastal areas also shows that it is robust and resilient to contamination due to sunglint or adjacency effects of land and cloud edges. The MLNN algorithm is very fast once the neural network has been properly trained and is therefore suitable for operational use. A significant advantage of the MLNN algorithm is that it does not need SWIR bands, which implies significant cost reduction for dedicated OC missions. A recent effort has been made to extend the MLNN AC algorithm to extreme atmospheric conditions (i.e. heavy polluted continental aerosols) over coastal areas by including additional aerosol and ocean models to generate the training dataset. Preliminary tests show very good results. Results of applying the extended MLNN algorithm to VIIRS images over the Yellow Sea and East China Sea areas with extreme atmospheric and marine conditions will be provided.

Integrating Ocean Color Observations and Nowcast/Forecast of Bio-Optical Properties into the Naval Research Laboratory Coastal Ocean Model (NCOM)

DTIC Science & Technology

2006-09-30

Jolliff, J. K., J.C. Kindle, B. Penta, R . Arnone, Z. Lee, C. Rowley (2005), Towards an Ocean Color Data Assimilation System: Analysis of Ocean Color...and Hydrodynamic Processes, Eos Trans., AGU, 87(36), Ocean Sci. Meet. Suppl., Abstract OS53K-04 Jolliff, J.K., J.C. Kindle, B. Penta, R . Arnone, Z...WQ(N 0.10,..--------~ r ------------------, B) BOOM O.!Or---------------------------, C)NWC ··Q·41 Znm ··Q·443nm ··Q·490nm " 0 ·5 !Onm .. a ·SSSnm

Sun and Sky Radiance Measurements and Data Analysis Protocols. Chapter 5

NASA Technical Reports Server (NTRS)

Frouin, Robert; Holben, Brent; Miller, Mark; Pietras, Christophe; Porter, John; Voss, Ken

2001-01-01

This chapter is concerned with two types of radiometric measurements essential to verify atmospheric correction algorithms and to calibrate vicariously satellite ocean color sensors. The first type is a photometric measurement of the direct solar beam to determine the optical thickness of the atmosphere. The intensity of the solar beam can be measured directly, or obtained indirectly from measurements of diffuse global upper hemispheric irradiance. The second type is a measurement of the solar aureole and sky radiance distribution using a CCD camera, or a scanning radiometer viewing in and perpendicular to the solar principal plane. From the two types of measurements, the optical properties of aerosols, highly variable in space and time, can be derived. Because of the high variability, the aerosol properties should be known at the time of satellite overpass. Atmospheric optics measurements, however, are not easy to perform at sea, from a ship or any platform. This complicates the measurement protocols and data analysis. Some instrumentation cannot be deployed at sea, and is limited to island and coastal sites. In the following, measurement protocols are described for radiometers commonly used to measure direct atmospheric transmittance and sky radiance, namely standard sun photometers, fast-rotating shadow-band radiometers, automated sky scanning systems, and CCD cameras. Methods and procedures to analyze and quality control the data are discussed, as well as proper measurement strategies for evaluation of atmospheric correction algorithms and satellite-derived ocean color.

Remote sensing estimation of terrestrially derived colored dissolved organic matterinput to the Arctic Ocean

NASA Astrophysics Data System (ADS)

Li, J.; Yu, Q.; Tian, Y. Q.

2017-12-01

The DOC flux from land to the Arctic Ocean has remarkable implication on the carbon cycle, biogeochemical & ecological processes in the Arctic. This lateral carbon flux is required to be monitored with high spatial & temporal resolution. However, the current studies in the Arctic regions were obstructed by the factors of the low spatial coverages. The remote sensing could provide an alternative bio-optical approach to field sampling for DOC dynamics monitoring through the observation of the colored dissolved organic matter (CDOM). The DOC and CDOM were found highly correlated based on the analysis of the field sampling data from the Arctic-GRO. These provide the solid foundation of the remote sensing observation. In this study, six major Arctic Rivers (Yukon, Kolyma, Lena, Mackenzie, Ob', Yenisey) were selected to derive the CDOM dynamics along four years. Our newly developed SBOP algorithm was applied to the large Landsat-8 OLI image data (nearly 100 images) for getting the high spatial resolution results. The SBOP algorithm is the first approach developing for the Shallow Water Bio-optical properties estimation. The CDOM absorption derived from the satellite images were verified with the field sampling results with high accuracy (R2 = 0.87). The distinct CDOM dynamics were found in different Rivers. The CDOM absorptions were found highly related to the hydrological activities and the terrestrially environmental dynamics. Our study helps to build the reliable system for studying the carbon cycle at Arctic regions.

Refinement of Protocols for Measuring the Apparent Optical Properties of Seawater. Chapter 8

NASA Technical Reports Server (NTRS)

Hooker, Stanford B.; Zibordi, Giuseppe; Berthon, Jean-Francois; Nirek, Andre; Antoine, David

2003-01-01

Ocean color satellite missions, like the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) or the Moderate Resolution Imaging Spectroradiometer (MODIS) projects, are tasked with acquiring a global ocean color data set, validating and monitoring the accuracy and quality of the data, processing the radiometric data into geophysical units using a set of atmospheric and bio-optical algorithms, and distributing the final products to the scientific community. The long-standing requirement of the SeaWiFS Project, for example, is to produce spectral water-leaving radiances, LW(lambda), to within 5% absolute (lambda denotes wavelength) and chlorophyll a concentrations to within 35% (Hooker and Esaias 1993), and most ocean color sensors have the same or similar requirements. Although a diverse set of activities are required to ensure the accuracy requirements are met (Hooker and McClain 2000), the perspective here is with field observations. The accurate determination of upper ocean apparent optical properties (AOPs) is essential for the vicarious calibration of ocean color data and the validation of the derived data products, because the sea-truth measurements are used to evaluate the satellite observations (Hooker and McClain 2000). The uncertainties with in situ AOP measurements have various sources: a) the sampling procedures used in the field, including the environmental conditions encountered; b) the absolute characterization of the radiometers in the laboratory; c) the conversion of the light signals to geophysical units in a processing scheme, and d) the stability of the radiometers in the harsh environment they are subjected to during transport and use. Assuming ideal environmental conditions, so this aspect can be neglected, the SeaWiFS ground-truth uncertainty budget can only be satisfied if each uncertainty is on the order of 1-2%, or what is generally referred to as 1% radiometry. In recent years, progress has been made in estimating the magnitude of some of these uncertainties and in defining procedures for minimizing them. For the SeaWiFS Project, the first step was to convene a workshop to draft the SeaWiFS Ocean Optics Protocols (hereafter referred to as the Protocols). The Protocols initially adhered to the Joint Global Ocean Flux Study (JGOFS) sampling procedures (JGOFS 1991) and defined the standards for optical measurements to be used in SeaWiFS calibration and validation activities (Mueller and Austin 1992). Over time, the Protocols were revised (Mueller and Austin 1995), and then recurringly updated on essentially an annual basis (Mueller 2000, 2002, and 2003) as part of the Sensor Inter-comparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project. 98

Assimilation of SeaWiFS Ocean Chlorophyll Data into a Three-Dimensional Global Ocean Model

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

2005-01-01

Assimilation of satellite ocean color data is a relatively new phenomenon in ocean sciences. However, with routine observations from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), launched in late 1997, and now with new data from the Moderate Resolution Imaging Spectroradometer (MODIS) Aqua, there is increasing interest in ocean color data assimilation. Here SeaWiFS chlorophyll data were assimilated with an established thre-dimentional global ocean model. The assimilation improved estimates of hlorophyll and primary production relative to a free-run (no assimilation) model. This represents the first attempt at ocean color data assimilation using NASA satellites in a global model. The results suggest the potential of assimilation of satellite ocean chlorophyll data for improving models.

An Overview of SIMBIOS Program Activities and Accomplishments. Chapter 1

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; McClain, Charles R.

2003-01-01

The SIMBIOS Program was conceived in 1994 as a result of a NASA management review of the agency's strategy for monitoring the bio-optical properties of the global ocean through space-based ocean color remote sensing. At that time, the NASA ocean color flight manifest included two data buy missions, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Earth Observing System (EOS) Color, and three sensors, two Moderate Resolution Imaging Spectroradiometers (MODIS) and the Multi-angle Imaging Spectro-Radiometer (MISR), scheduled for flight on the EOS-Terra and EOS-Aqua satellites. The review led to a decision that the international assemblage of ocean color satellite systems provided ample redundancy to assure continuous global coverage, with no need for the EOS Color mission. At the same time, it was noted that non-trivial technical difficulties attended the challenge (and opportunity) of combining ocean color data from this array of independent satellite systems to form consistent and accurate global bio-optical time series products. Thus, it was announced at the October 1994 EOS Interdisciplinary Working Group meeting that some of the resources budgeted for EOS Color should be redirected into an intercalibration and validation program (McClain et al., 2002).

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Decadal Changes in Global Ocean Annual Primary Production

NASA Technical Reports Server (NTRS)

Gregg, Watson; Conkright, Margarita E.; Behrenfeld, Michael J.; Ginoux, Paul; Casey, Nancy W.; Koblinsky, Chester J. (Technical Monitor)

2002-01-01

The Sea-viewing Wide Field-of-View Sensor (SeaWiFS) has produced the first multi-year time series of global ocean chlorophyll observations since the demise of the Coastal Zone Color Scanner (CZCS) in 1986. Global observations from 1997-present from SeaWiFS combined with observations from 1979-1986 from the CZCS should in principle provide an opportunity to observe decadal changes in global ocean annual primary production, since chlorophyll is the primary driver for estimates of primary production. However, incompatibilities between algorithms have so far precluded quantitative analysis. We have developed and applied compatible processing methods for the CZCS, using modern advances in atmospheric correction and consistent bio-optical algorithms to advance the CZCS archive to comparable quality with SeaWiFS. We applied blending methodologies, where in situ data observations are incorporated into the CZCS and SeaWiFS data records, to provide improvement of the residuals. These re-analyzed, blended data records provide maximum compatibility and permit, for the first time, a quantitative analysis of the changes in global ocean primary production in the early-to-mid 1980's and the present, using synoptic satellite observations. An intercomparison of the global and regional primary production from these blended satellite observations is important to understand global climate change and the effects on ocean biota. Photosynthesis by chlorophyll-containing phytoplankton is responsible for biotic uptake of carbon in the oceans and potentially ultimately from the atmosphere. Global ocean annual primary decreased from the CZCS record to SeaWiFS, by nearly 6% from the early 1980s to the present. Annual primary production in the high latitudes was responsible for most of the decadal change. Conversely, primary production in the low latitudes generally increased, with the exception of the tropical Pacific. The differences and similarities of the two data records provide evidence of how the Earth's climate may be changing and how ocean biota respond. Furthermore, the results have implications for the ocean carbon cycle.

A review of ocean chlorophyll algorithms and primary production models

NASA Astrophysics Data System (ADS)

Li, Jingwen; Zhou, Song; Lv, Nan

2015-12-01

This paper mainly introduces the five ocean chlorophyll concentration inversion algorithm and 3 main models for computing ocean primary production based on ocean chlorophyll concentration. Through the comparison of five ocean chlorophyll inversion algorithm, sums up the advantages and disadvantages of these algorithm,and briefly analyzes the trend of ocean primary production model.

Color object detection using spatial-color joint probability functions.

PubMed

Luo, Jiebo; Crandall, David

2006-06-01

Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm that can detect arbitrary objects in unconstrained images; instead, algorithms typically must be customized for each specific object. Consequently, it typically requires a large number of exemplars (for rigid objects) or a large amount of human intuition (for nonrigid objects) to develop a robust algorithm. We present a robust algorithm designed to detect a class of compound color objects given a single model image. A compound color object is defined as having a set of multiple, particular colors arranged spatially in a particular way, including flags, logos, cartoon characters, people in uniforms, etc. Our approach is based on a particular type of spatial-color joint probability function called the color edge co-occurrence histogram. In addition, our algorithm employs perceptual color naming to handle color variation, and prescreening to limit the search scope (i.e., size and location) for the object. Experimental results demonstrated that the proposed algorithm is insensitive to object rotation, scaling, partial occlusion, and folding, outperforming a closely related algorithm based on color co-occurrence histograms by a decisive margin.

Monitoring terrestrial dissolved organic carbon export at land-water interfaces using remote sensing

NASA Astrophysics Data System (ADS)

Yu, Q.; Li, J.; Tian, Y. Q.

2017-12-01

Carbon flux from land to oceans and lakes is a crucial component of carbon cycling. However, this lateral carbon flow at land-water interface is often neglected in the terrestrial carbon cycle budget, mainly because observations of the carbon dynamics are very limited. Monitoring CDOM/DOC dynamics using remote sensing and assessing DOC export from land to water remains a challenge. Current CDOM retrieval algorithms in the field of ocean color are not simply applicable to inland aquatic ecosystems since they were developed for coarse resolution ocean-viewing imagery and less complex water types in open-sea. We developed a new semi-analytical algorithm, called SBOP (Shallow water Bio-Optical Properties algorithm) to adapt to shallow inland waters. SBOP was first developed and calibrated based on in situ hyperspectral radiometer data. Then we applied it to the Landsat-8 OLI images and evaluated the effectiveness of the multispectral images on inversion of CDOM absorption based on our field sampling at the Saginaw Bay in the Lake Huron. The algorithm performances (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay; R2 = 0.80 in the northeastern US lakes) is promising and we conclude the CDOM absorption can be derived from Landsat-8 OLI image in both optically deep and optically shallow waters with high accuracy. Our method addressed challenges on employing appropriate atmospheric correction, determining bottom reflectance influence for shallow waters, and improving for bio-optical properties retrieval, as well as adapting to both hyperspectral and the multispectral remote sensing imagery. Over 100 Landsat-8 images in Lake Huron, northeastern US lakes, and the Arctic major rivers were processed to understand the CDOM spatio-temporal dynamics and its associated driving factors.

NASA Oceanic Processes Program, Fiscal Year 1981

NASA Technical Reports Server (NTRS)

1982-01-01

Summaries are included for Nimbus 7, Seasat, TIROS-N, Altimetry, Color Radiometry, in situ data collection systems, Synthetic Aperture Radar (SAR)/Open Ocean, SAR/Sea Ice, Scatterometry, National Oceanic Satellite System, Free Flying Imaging Radar Experiment, TIROS-N/Scatterometer and/or ocean color scanner, and Ocean Topography Experiment. Summaries of individual research projects sponsored by the Ocean Processes Program are given. Twelve investigations for which contracting services are provided by NOAA are included.

Ocean color imagery: Coastal zone color scanner

NASA Technical Reports Server (NTRS)

Hovis, W. A.

1975-01-01

Investigations into the feasibility of sensing ocean color from high altitude for determination of chlorophyll and sediment distributions were carried out using sensors on NASA aircraft, coordinated with surface measurements carried out by oceanographic vessels. Spectrometer measurements in 1971 and 1972 led to development of an imaging sensor now flying on a NASA U-2 and the Coastal Zone Color Scanner to fly on Nimbus G in 1978. Results of the U-2 effort show the imaging sensor to be of great value in sensing pollutants in the ocean.

Merging Ocean Color Data from Multiple Missions. Chapter 12

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

2001-01-01

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, the National Aeronautics and Space Administration (NASA) and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data. Seven of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), and MODIS-PM. In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic pigment concentrations (i.e., phytoplankton abundance) and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans. Any individual ocean color mission is limited in ocean coverage due to sun glint and clouds. For example, one of the first proposed missions, the SeaWiFS, can provide about 45% coverage of the global ocean in four days and only about 15% in one day.

NOAA activities in support of in situ validation observations for satellite ocean color products and related ocean science research

NASA Astrophysics Data System (ADS)

Lance, V. P.; DiGiacomo, P. M.; Ondrusek, M.; Stengel, E.; Soracco, M.; Wang, M.

2016-02-01

The NOAA/STAR ocean color program is focused on "end-to-end" production of high quality satellite ocean color products. In situ validation of satellite data is essential to produce the high quality, "fit for purpose" ocean color products that support users and applications in all NOAA line offices, as well as external (both applied and research) users. The first NOAA/OMAO (Office of Marine and Aviation Operations) sponsored research cruise dedicated to VIIRS SNPP validation was completed aboard the NOAA Ship Nancy Foster in November 2014. The goals and objectives of the 2014 cruise are highlighted in the recently published NOAA/NESDIS Technical Report. A second dedicated validation cruise is planned for December 2015 and will have been completed by the time of this meeting. The goals and objectives of the 2015 cruise will be discussed in the presentation. Participants and observations made will be reported. The NOAA Ocean Color Calibration/Validation (Cal/Val) team also works collaboratively with others programs. A recent collaboration with the NOAA Ocean Acidification program on the East Coast Ocean Acidification (ECOA) cruise during June-July 2015, where biogeochemical and optical measurements were made together, allows for the leveraging of in situ observations for satellite validation and for their use in the development of future ocean acidification satellite products. Datasets from these cruises will be formally archived at NOAA and Digital Object Identifier (DOI) numbers will be assigned. In addition, the NOAA Coast/OceanWatch Program is working to establish a searchable database. The beta version will begin with cruise data and additional in situ calibration/validation related data collected by the NOAA Ocean Color Cal/Val team members. A more comprehensive searchable NOAA database, with contributions from other NOAA ocean observation platforms and cruise collaborations is envisioned. Progress on these activities will be reported.

The Marine Resources Experiment Program (MAREX)

NASA Technical Reports Server (NTRS)

1982-01-01

The Satellite Ocean Color Science Working Group was established to consider the scientific utility of repeated satellite measurements of ocean color, especially for measuring global ocean chlorophyll and for studying the fate of global primary productivity in the sea. Results of the group's deliberations are presented. The scientific requirements are given for ocean color data from a CZCS follow on sensor in order to address global primary productivity, fishery, and carbon storage problems. Some specific experiments, called the marine resource experiment and designed to determine critical nutrient fluxes, photosynthetic rates, and primary productivity and biomass, are outlined.

Characteristic vector analysis as a technique for signature extraction of remote ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1977-01-01

Characteristic vector analysis is being used to extract spectral signatures of suspended matter in the ocean from remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor), a multispectral scanner. Spectral signatures appear to be obtainable either directly from characteristic vectors or through a transformation of these eigenvectors. Quantification of the suspended matter associated with each resulting signature seems feasible using associated coefficients generated by the technique. This paper presents eigenvectors associated with algae, 'sediment', acid waste, sewage sludge, and oil. The results suggest an efficient method of transmitting from satellites multispectral data of pollution in our oceans.

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

NASA Astrophysics Data System (ADS)

Shanmugam, Palanisamy; He, Xianqiang; Singh, Rakesh Kumar; Varunan, Theenathayalan

2018-05-01

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.

SeaWiFS technical report series. Volume 21: The heritage of SeaWiFS. A retrospective on the CZCS NIMBUS Experiment Team (NET) program

NASA Technical Reports Server (NTRS)

Acker, James G.; Hooker, Stanford B.; Firestone, Elaine R.

1994-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission is based on the scientific heritage of the Coastal Zone Color Scanner (CZCS), a proof-of-concept instrument carried on the National Aeronautics and Space Administration (NASA) NIMBUS-7 environmental satellite for the purpose of measuring upwelling radiance from the ocean surface. The CZCS mission provided the first observations of ocean color from space, and over the mission lifetime of 1978-1986, allowed oceanographers an initial opportunity to observe the variable patterns of global biological productivity. One of the key elements of the CZCS mission was the formation of the CZCS NIMBUS Experiment Team (NET), a group of optical physicists and biological oceanographers. The CZCS NET was designated to validate the accuracy of the CZCS radiometric measurements and to connect the instrument's measurements to standard measures of oceanic biological productivity and optical seawater clarity. In the period following the cessation of CZCS observations, some of the insight and experience gained by the CZCS NET activity has dissipated as several proposed follow-on sensors failed to achieve active status. The Sea WiFS mission will be the first dedicated orbital successor to CZCS it in turn precedes observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) of the Earth Observing System (EOS). Since the CZCS NET experience is an important model for Sea WiFS and MODIS surface truth efforts, this document is intended to provide a comprehensive review of the validation of oceanographic data for the first orbital ocean color sensor mission. This document also summarizes the history of the CZCS NET activities. The references listed in the Bibliography are a listing of published scientific research which relied upon the CZCS BET algorithms, or research which was conducted on the basis of CZCS mission elements.

First Autonomous Bio-Optical Profiling Float in the Gulf of Mexico Reveals Dynamic Biogeochemistry in Deep Waters

PubMed Central

Green, Rebecca E.; Bower, Amy S.; Lugo-Fernández, Alexis

2014-01-01

Profiling floats equipped with bio-optical sensors well complement ship-based and satellite ocean color measurements by providing highly-resolved time-series data on the vertical structure of biogeochemical processes in oceanic waters. This is the first study to employ an autonomous profiling (APEX) float in the Gulf of Mexico for measuring spatiotemporal variability in bio-optics and hydrography. During the 17-month deployment (July 2011 to December 2012), the float mission collected profiles of temperature, salinity, chlorophyll fluorescence, particulate backscattering (bbp), and colored dissolved organic matter (CDOM) fluorescence from the ocean surface to a depth of 1,500 m. Biogeochemical variability was characterized by distinct depth trends and local “hot spots”, including impacts from mesoscale processes associated with each of the water masses sampled, from ambient deep waters over the Florida Plain, into the Loop Current, up the Florida Canyon, and eventually into the Florida Straits. A deep chlorophyll maximum (DCM) occurred between 30 and 120 m, with the DCM depth significantly related to the unique density layer ρ = 1023.6 (R2 = 0.62). Particulate backscattering, bbp, demonstrated multiple peaks throughout the water column, including from phytoplankton, deep scattering layers, and resuspension. The bio-optical relationship developed between bbp and chlorophyll (R2 = 0.49) was compared to a global relationship and could significantly improve regional ocean-color algorithms. Photooxidation and autochthonous production contributed to CDOM distributions in the upper water column, whereas in deep water, CDOM behaved as a semi-conservative tracer of water masses, demonstrating a tight relationship with density (R2 = 0.87). In the wake of the Deepwater Horizon oil spill, this research lends support to the use of autonomous drifting profilers as a powerful tool for consideration in the design of an expanded and integrated observing network for the Gulf of Mexico. PMID:24992646

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking †

PubMed Central

Kiku, Daisuke; Okutomi, Masatoshi

2017-01-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. PMID:29194407

Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking.

PubMed

Monno, Yusuke; Kiku, Daisuke; Tanaka, Masayuki; Okutomi, Masatoshi

2017-12-01

Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking.

GOCI Level-2 Processing Improvements and Cloud Motion Analysis

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.

2015-01-01

The Ocean Biology Processing Group has been working with the Korean Institute of Ocean Science and Technology (KIOST) to process geosynchronous ocean color data from the GOCI (Geostationary Ocean Color Instrument) aboard the COMS (Communications, Ocean and Meteorological Satellite). The level-2 processing program, l2gen has GOCI processing as an option. Improvements made to that processing are discussed here as well as a discussion about cloud motion effects.

Remote-sensing reflectance determinations in the coastal ocean environment: impact of instrumental characteristics and environmental variability.

PubMed

Toole, D A; Siegel, D A; Menzies, D W; Neumann, M J; Smith, R C

2000-01-20

Three independent ocean color sampling methodologies are compared to assess the potential impact of instrumental characteristics and environmental variability on shipboard remote-sensing reflectance observations from the Santa Barbara Channel, California. Results indicate that under typical field conditions, simultaneous determinations of incident irradiance can vary by 9-18%, upwelling radiance just above the sea surface by 8-18%, and remote-sensing reflectance by 12-24%. Variations in radiometric determinations can be attributed to a variety of environmental factors such as Sun angle, cloud cover, wind speed, and viewing geometry; however, wind speed is isolated as the major source of uncertainty. The above-water approach to estimating water-leaving radiance and remote-sensing reflectance is highly influenced by environmental factors. A model of the role of wind on the reflected sky radiance measured by an above-water sensor illustrates that, for clear-sky conditions and wind speeds greater than 5 m/s, determinations of water-leaving radiance at 490 nm are undercorrected by as much as 60%. A data merging procedure is presented to provide sky radiance correction parameters for above-water remote-sensing reflectance estimates. The merging results are consistent with statistical and model findings and highlight the importance of multiple field measurements in developing quality coastal oceanographic data sets for satellite ocean color algorithm development and validation.

Remote Sensing of Ocean Color in the Arctic: Algorithm Development and Comparative Validation. Chapter 9

NASA Technical Reports Server (NTRS)

Cota, Glenn F.

2001-01-01

The overall goal of this effort is to acquire a large bio-optical database, encompassing most environmental variability in the Arctic, to develop algorithms for phytoplankton biomass and production and other optically active constituents. A large suite of bio-optical and biogeochemical observations have been collected in a variety of high latitude ecosystems at different seasons. The Ocean Research Consortium of the Arctic (ORCA) is a collaborative effort between G.F. Cota of Old Dominion University (ODU), W.G. Harrison and T. Platt of the Bedford Institute of Oceanography (BIO), S. Sathyendranath of Dalhousie University and S. Saitoh of Hokkaido University. ORCA has now conducted 12 cruises and collected over 500 in-water optical profiles plus a variety of ancillary data. Observational suites typically include apparent optical properties (AOPs), inherent optical property (IOPs), and a variety of ancillary observations including sun photometry, biogeochemical profiles, and productivity measurements. All quality-assured data have been submitted to NASA's SeaWIFS Bio-Optical Archive and Storage System (SeaBASS) data archive. Our algorithm development efforts address most of the potential bio-optical data products for the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and GLI, and provides validation for a specific areas of concern, i.e., high latitudes and coastal waters.

Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Johnson, B.

1988-01-01

The Coastal Zone Color Scanner (CZCS) spacecraft ocean color instrument is capable of measuring and mapping global ocean surface chlorophyll concentration. It is a scanning radiometer with multiband capability. With new electronics and some mechanical, and optical re-work, it probably can be made flight worthy. Some additional components of a second flight model are also available. An engineering study and further tests are necessary to determine exactly what effort is required to properly prepare the instrument for spaceflight and the nature of interfaces to prospective spacecraft. The CZCS provides operational instrument capability for monitoring of ocean productivity and currents. It could be a simple, low cost alternative to developing new instruments for ocean color imaging. Researchers have determined that with global ocean color data they can: specify quantitatively the role of oceans in the global carbon cycle and other major biogeochemical cycles; determine the magnitude and variability of annual primary production by marine phytoplankton on a global scale; understand the fate of fluvial nutrients and their possible affect on carbon budgets; elucidate the coupling mechanism between upwelling and large scale patterns in ocean basins; answer questions concerning the large scale distribution and timing of spring blooms in the global ocean; acquire a better understanding of the processes associated with mixing along the edge of eddies, coastal currents, western boundary currents, etc., and acquire global data on marine optical properties.

Use of satellite ocean color observations to refine understanding of global geochemical cycles

NASA Technical Reports Server (NTRS)

Walsh, J. J.; Dieterle, D. A.

1985-01-01

In October 1978, the first satellite-borne color sensor, the Coastal Zone Color Scanner (CZCS), was launched aboard Nimbus-7 with four visible and two infrared bands, permitting a sensitivity about 60 times that of the Landsat-1 multispectral scanner. The CZCS radiance data can be utilized to estimate ocean chlorophyll concentrations by detecting shifts in sea color, particularly in oceanic waters. The obtained data can be used in studies regarding problems of overfishing, and, in addition, in investigations concerning the consequences of man's accelerated extraction of nitrogen from the atmosphere and addition of carbon to the atmosphere. The satellite data base is considered along with a simulation analysis, and ships providing ground-truth chlorophyll measurements in the ocean.

Achieving Global Ocean Color Climate Data Records

NASA Technical Reports Server (NTRS)

Franz, Bryan

2010-01-01

Ocean color, or the spectral distribution of visible light upwelling from beneath the ocean surface, carries information on the composition and concentration of biological constituents within the water column. The CZCS mission in 1978 demonstrated that quantitative ocean color measurements could be. made from spaceborne sensors, given sufficient corrections for atmospheric effects and a rigorous calibration and validation program. The launch of SeaWiFS in 1997 represents the beginning of NASA's ongoing efforts to develop a continuous ocean color data record with sufficient coverage and fidelity for global change research. Achievements in establishing and maintaining the consistency of the time-series through multiple missions and varying instrument designs will be highlighted in this talk, including measurements from NASA'S MODIS instruments currently flying on the Terra and Aqua platforms, as well as the MERIS sensor flown by ESA and the OCM-2 sensor recently launched by ISRO.

Corrections to the MODIS Aqua Calibration Derived From MODIS Aqua Ocean Color Products

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan Alden

2013-01-01

Ocean color products such as, e.g., chlorophyll-a concentration, can be derived from the top-of-atmosphere radiances measured by imaging sensors on earth-orbiting satellites. There are currently three National Aeronautics and Space Administration sensors in orbit capable of providing ocean color products. One of these sensors is the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, whose ocean color products are currently the most widely used of the three. A recent improvement to the MODIS calibration methodology has used land targets to improve the calibration accuracy. This study evaluates the new calibration methodology and describes further calibration improvements that are built upon the new methodology by including ocean measurements in the form of global temporally averaged water-leaving reflectance measurements. The calibration improvements presented here mainly modify the calibration at the scan edges, taking advantage of the good performance of the land target trending in the center of the scan.

NASA Satellite Monitoring of Water Clarity in Mobile Bay for Nutrient Criteria Development

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holekamp, Kara; Spiering, Bruce A.

2009-01-01

This project has demonstrated feasibility of deriving from MODIS daily measurements time series of water clarity parameters that provide coverage of a specific location or an area of interest for 30-50% of days. Time series derived for estuarine and coastal waters display much higher variability than time series of ecological parameters (such as vegetation indices) derived for land areas. (Temporal filtering often applied in terrestrial studies cannot be used effectively in ocean color processing). IOP-based algorithms for retrieval of diffuse light attenuation coefficient and TSS concentration perform well for the Mobile Bay environment: only a minor adjustment was needed in the TSS algorithm, despite generally recognized dependence of such algorithms on local conditions. The current IOP-based algorithm for retrieval of chlorophyll a concentration has not performed as well: a more reliable algorithm is needed that may be based on IOPs at additional wavelengths or on remote sensing reflectance from multiple spectral bands. CDOM algorithm also needs improvement to provide better separation between effects of gilvin (gelbstoff) and detritus. (Identification or development of such algorithm requires more data from in situ measurements of CDOM concentration in Gulf of Mexico coastal waters (ongoing collaboration with the EPA Gulf Ecology Division))

Variability in Ocean Color Associated with Phytoplankton and Terrigenous Matter: Time Series Measurements and Algorithm Development at the FRONT Site on the New England Continental Shelf. Chapter 12

NASA Technical Reports Server (NTRS)

Morrison, John R.; Sosik, Heidi M.

2003-01-01

Fronts in the coastal ocean describe areas of strong horizontal gradients in both physical and biological properties associated with tidal mixing and freshwater estuarine output (e.g. Simpson, 1981 and O Donnell, 1993). Related gradients in optically important constituents mean that fronts can be observed from space as changes in ocean color as well as sea surface temperature (e.g., Dupouy et al., 1986). This research program is designed to determine which processes and optically important constituents must be considered to explain ocean color variations associated with coastal fronts on the New England continental shelf, in particular the National Ocean Partnership Program (NOPP) Front Resolving Observational Network with Telemetry (FRONT) site. This site is located at the mouth of Long Island sound and was selected after the analysis of 12 years of AVHRR data showed the region to be an area of strong frontal activity (Ullman and Cornillon, 1999). FRONT consists of a network of modem nodes that link bottom mounted Acoustic Doppler Current Profilers (ADCPs) and profiling arrays. At the center of the network is the Autonomous Vertically Profiling Plankton Observatory (AVPPO) (Thwaites et al. 1998). The AVPPO consists of buoyant sampling vehicle and a trawl-resistant bottom-mounted enclosure, which holds a winch, the vehicle (when not sampling), batteries, and controller. Three sampling systems are present on the vehicle, a video plankton recorder, a CTD with accessory sensors, and a suite of bio-optical sensors including Satlantic OCI-200 and OCR-200 spectral radiometers and a WetLabs ac-9 dual path absorption and attenuation meter. At preprogrammed times the vehicle is released, floats to the surface, and is then winched back into the enclosure with power and data connection maintained through the winch cable. Communication to shore is possible through a bottom cable and nearby surface telemetry buoy, equipped with a mobile modem, giving the capability for near-real time data transmission and interactive sampling control.

Mechanical Properties of the Surface Material of Comet 67P/Churyumov-Gerasimenko Measured By the Casse Instrument Onboard the Philae Lander

NASA Astrophysics Data System (ADS)

Knapmeyer, M.; Fischer, H. H.; Seidensticker, K. J.; Arnold, W.; Faber, C.; Möhlmann, D.; Thiel, K.

2014-12-01

Satellite remote sensing of ocean color is a critical tool for assessing the productivity of marine ecosystems and monitoring changes resulting from climatic or environmental influences. Yet water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Traditional ocean color retrieval algorithms utilize a standard set of aerosol models and the assumption of negligible water-leaving radiance in the near-infrared. Modern improvements have been developed to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean, where ocean fertilization can impact biological productivity at the base of the marine food chain. Even so, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error. In the UV, the problem of UV-enhanced absorption and nonsphericity of certain aerosol types are amplified due to the increased Rayleigh and aerosol optical depth, especially at off-nadir view angles. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of the work to be described is the assessment of the effects of absorbing aerosol properties on water leaving radiance measurement uncertainty by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach described by Dubovik et al., 2006. A vector Markov Chain radiative transfer code including bio-optical models was used to evaluate TOA and water leaving radiances.

Assessment of capabilities of multiangle imaging photo-polarimetry for atmospheric correction in presence of absorbing aerosols

NASA Astrophysics Data System (ADS)

Kalashnikova, O. V.; Garay, M. J.; Xu, F.; Seidel, F. C.; Diner, D. J.

2015-12-01

Satellite remote sensing of ocean color is a critical tool for assessing the productivity of marine ecosystems and monitoring changes resulting from climatic or environmental influences. Yet water-leaving radiance comprises less than 10% of the signal measured from space, making correction for absorption and scattering by the intervening atmosphere imperative. Traditional ocean color retrieval algorithms utilize a standard set of aerosol models and the assumption of negligible water-leaving radiance in the near-infrared. Modern improvements have been developed to handle absorbing aerosols such as urban particulates in coastal areas and transported desert dust over the open ocean, where ocean fertilization can impact biological productivity at the base of the marine food chain. Even so, imperfect knowledge of the absorbing aerosol optical properties or their height distribution results in well-documented sources of error. In the UV, the problem of UV-enhanced absorption and nonsphericity of certain aerosol types are amplified due to the increased Rayleigh and aerosol optical depth, especially at off-nadir view angles. Multi-angle spectro-polarimetric measurements have been advocated as an additional tool to better understand and retrieve the aerosol properties needed for atmospheric correction for ocean color retrievals. The central concern of the work to be described is the assessment of the effects of absorbing aerosol properties on water leaving radiance measurement uncertainty by neglecting UV-enhanced absorption of carbonaceous particles and by not accounting for dust nonsphericity. In addition, we evaluate the polarimetric sensitivity of absorbing aerosol properties in light of measurement uncertainties achievable for the next generation of multi-angle polarimetric imaging instruments, and demonstrate advantages and disadvantages of wavelength selection in the UV/VNIR range. The phase matrices for the spherical smoke particles were calculated using a standard Mie code, while those for non-spherical dust particles were calculated using the numerical approach described by Dubovik et al., 2006. A vector Markov Chain radiative transfer code including bio-optical models was used to evaluate TOA and water leaving radiances.

Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations.

PubMed

Krasnopolsky, Vladimir; Nadiga, Sudhir; Mehra, Avichal; Bayler, Eric; Behringer, David

2016-01-01

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites and in situ physical observations. Satellite-derived "ocean color" (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA's operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed--signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN's generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series.

Microradiometers Reveal Ocean Health, Climate Change

NASA Technical Reports Server (NTRS)

2013-01-01

When NASA researcher Stanford Hooker is in the field, he pays close attention to color. For Hooker, being in the field means being at sea. On one such research trip to the frigid waters of the Arctic, with a Coast Guard icebreaker looming nearby and the snow-crusted ice shelf a few feet away, Hooker leaned over the edge of his small boat and lowered a tethered device into the bright turquoise water, a new product devised by a NASA partner and enabled by a promising technology for oceanographers and atmospheric scientists alike. Color is a function of light. Pure water is clear, but the variation in color observed during a visit to the beach or a flight along a coastline depends on the water s depth and the constituents in it, how far down the light penetrates and how it is absorbed and scattered by dissolved and suspended material. Hooker cares about ocean color because of what it can reveal about the health of the ocean, and in turn, the health of our planet. "The main thing we are interested in is the productivity of the water," Hooker says. The seawater contains phytoplankton, microscopic plants, which are the food base for the ocean s ecosystems. Changes in the water s properties, whether due to natural seasonal effects or human influence, can lead to problems for delicate ecosystems such as coral reefs. Ocean color can inform researchers about the quantities and distribution of phytoplankton and other materials, providing clues as to how the world ocean is changing. NASA s Coastal Zone Color Scanner, launched in 1978, was the first ocean color instrument flown on a spacecraft. Since then, the Agency s ocean color research capabilities have become increasingly sophisticated with the launch of the SeaWiFS instrument in 1997 and the twin MODIS instruments carried into orbit on NASA s Terra (1999) and Aqua (2002) satellites. The technology provides sweeping, global information on ocean color on a scale unattainable by any other means. One issue that arises from satellite observation, however, is that the instruments must be continuously calibrated over time to maintain the quality of the data they gather from orbit. To validate and calibrate the satellites, researchers must also gather data at sea level.

Rayleigh radiance computations for satellite remote sensing: accounting for the effect of sensor spectral response function.

PubMed

Wang, Menghua

2016-05-30

To understand and assess the effect of the sensor spectral response function (SRF) on the accuracy of the top of the atmosphere (TOA) Rayleigh-scattering radiance computation, new TOA Rayleigh radiance lookup tables (LUTs) over global oceans and inland waters have been generated. The new Rayleigh LUTs include spectral coverage of 335-2555 nm, all possible solar-sensor geometries, and surface wind speeds of 0-30 m/s. Using the new Rayleigh LUTs, the sensor SRF effect on the accuracy of the TOA Rayleigh radiance computation has been evaluated for spectral bands of the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (SNPP) satellite and the Joint Polar Satellite System (JPSS)-1, showing some important uncertainties for VIIRS-SNPP particularly for large solar- and/or sensor-zenith angles as well as for large Rayleigh optical thicknesses (i.e., short wavelengths) and bands with broad spectral bandwidths. To accurately account for the sensor SRF effect, a new correction algorithm has been developed for VIIRS spectral bands, which improves the TOA Rayleigh radiance accuracy to ~0.01% even for the large solar-zenith angles of 70°-80°, compared with the error of ~0.7% without applying the correction for the VIIRS-SNPP 410 nm band. The same methodology that accounts for the sensor SRF effect on the Rayleigh radiance computation can be used for other satellite sensors. In addition, with the new Rayleigh LUTs, the effect of surface atmospheric pressure variation on the TOA Rayleigh radiance computation can be calculated precisely, and no specific atmospheric pressure correction algorithm is needed. There are some other important applications and advantages to using the new Rayleigh LUTs for satellite remote sensing, including an efficient and accurate TOA Rayleigh radiance computation for hyperspectral satellite remote sensing, detector-based TOA Rayleigh radiance computation, Rayleigh radiance calculations for high altitude lakes, and the same Rayleigh LUTs are applicable for all satellite sensors over the global ocean and inland waters. The new Rayleigh LUTs have been implemented in the VIIRS-SNPP ocean color data processing for routine production of global ocean color and inland water products.

Onboard Science and Applications Algorithm for Hyperspectral Data Reduction

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Davies, Ashley G.; Silverman, Dorothy; Mandl, Daniel

2012-01-01

An onboard processing mission concept is under development for a possible Direct Broadcast capability for the HyspIRI mission, a Hyperspectral remote sensing mission under consideration for launch in the next decade. The concept would intelligently spectrally and spatially subsample the data as well as generate science products onboard to enable return of key rapid response science and applications information despite limited downlink bandwidth. This rapid data delivery concept focuses on wildfires and volcanoes as primary applications, but also has applications to vegetation, coastal flooding, dust, and snow/ice applications. Operationally, the HyspIRI team would define a set of spatial regions of interest where specific algorithms would be executed. For example, known coastal areas would have certain products or bands downlinked, ocean areas might have other bands downlinked, and during fire seasons other areas would be processed for active fire detections. Ground operations would automatically generate the mission plans specifying the highest priority tasks executable within onboard computation, setup, and data downlink constraints. The spectral bands of the TIR (thermal infrared) instrument can accurately detect the thermal signature of fires and send down alerts, as well as the thermal and VSWIR (visible to short-wave infrared) data corresponding to the active fires. Active volcanism also produces a distinctive thermal signature that can be detected onboard to enable spatial subsampling. Onboard algorithms and ground-based algorithms suitable for onboard deployment are mature. On HyspIRI, the algorithm would perform a table-driven temperature inversion from several spectral TIR bands, and then trigger downlink of the entire spectrum for each of the hot pixels identified. Ocean and coastal applications include sea surface temperature (using a small spectral subset of TIR data, but requiring considerable ancillary data), and ocean color applications to track biological activity such as harmful algal blooms. Measuring surface water extent to track flooding is another rapid response product leveraging VSWIR spectral information.

Detection of ocean color changes from high altitudes

NASA Technical Reports Server (NTRS)

Hovis, W. A.; Forman, M. L.; Blaine, L. R.

1973-01-01

The detection of ocean color changes, thought to be due to chlorophyll concentrations and gelbstoffe variations, is attempted from high altitude (11.3km) and low altitude (0.3km). The atmospheric back scattering is shown to reduce contrast, but not sufficiently to obscure color change detection at high altitudes.

Ocean Color Data at the Goddard Earth Sciences (GES) DAAC: CZCS, SeaWiFS, OCTS, MODIS-Terra, MODIS-Aqua

NASA Technical Reports Server (NTRS)

2002-01-01

The Goddard Earth Sciences Distributed Active Archive Center (DAAC) is the designated archive for all of the ocean color data produced by NASA satellite missions. The DAAC is a long-term, high volume, secure repository for many different kinds of environmental data. With respect to ocean color, the Goddard DAAC holds all the data obtained during the eight-year mission of the Coastal Zone Color Scanner (CZCS). The DAAC is currently receiving data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and the MODIS-Terra instrument. The DAAC recently received reformatted data from the Ocean Color and Temperature Scanner (OCTS) and will also archive MODIS-Aqua Ocean products. In addition to its archive and distribution services, the Goddard DAAC strives to improve data access, ease-of-use, and data applicability for a broad spectrum of customers. The DAAC's data support teams practice dual roles, both insuring the integrity of the DAAC data archive and serving the user community with answers to user inquiries, online and print documentation, and customized data services.

A preliminary assessment of the Nimbus-7 CZCS atmospheric correction algorithm in a horizontally inhomogeneous atmosphere. [Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Gordon, H. R.

1981-01-01

For an estimation of the concentration of phytoplankton pigments in the oceans on the basis of Nimbus-7 CZCS imagery, it is necessary to remove the effects of the intervening atmosphere from the satellite imagery. The principle effect of the atmosphere is a loss in contrast caused by the addition of a substantial amount of radiance (path radiance) to that scatttered out of the water. Gordon (1978) has developed a technique which shows considerable promise for removal of these atmospheric effects. Attention is given to the correction algorithm, and its application to CZCS imagery. An alternate method under study for affecting the atmospheric correction requires a knowledge of 'clear water' subsurface upwelled radiance as a function of solar angle and pigment concentration.

Late Summer Frazil Ice-Associated Algal Blooms around Antarctica

NASA Astrophysics Data System (ADS)

DeJong, Hans B.; Dunbar, Robert B.; Lyons, Evan A.

2018-01-01

Antarctic continental shelf waters are the most biologically productive in the Southern Ocean. Although satellite-derived algorithms report peak productivity during the austral spring/early summer, recent studies provide evidence for substantial late summer productivity that is associated with green colored frazil ice. Here we analyze daily Moderate Resolution Imaging Spectroradiometer satellite images for February and March from 2003 to 2017 to identify green colored frazil ice hot spots. Green frazil ice is concentrated in 11 of the 13 major sea ice production polynyas, with the greenest frazil ice in the Terra Nova Bay and Cape Darnley polynyas. While there is substantial interannual variability, green frazil ice is present over greater than 300,000 km2 during March. Late summer frazil ice-associated algal productivity may be a major phenomenon around Antarctica that is not considered in regional carbon and ecosystem models.

Eddies in the Southern Ocean

NASA Image and Video Library

2015-04-08

The cloud cover over the Southern Ocean occasionally parts as it did on January 1, 2015 just west of the Drake Passage where the VIIRS instrument on the Suomi NPP satellite glimpsed the above collection of ocean-color delineated eddies which have diameters ranging from a couple of kilometers to a couple of hundred kilometers. Recent studies indicate that eddy activity has been increasing in the Southern Ocean with possible implications for climate change. Credit: NASA's OceanColor/Suomi NPP/VIIRS

[Design and Implementation of Image Interpolation and Color Correction for Ultra-thin Electronic Endoscope on FPGA].

PubMed

Luo, Qiang; Yan, Zhuangzhi; Gu, Dongxing; Cao, Lei

This paper proposed an image interpolation algorithm based on bilinear interpolation and a color correction algorithm based on polynomial regression on FPGA, which focused on the limited number of imaging pixels and color distortion of the ultra-thin electronic endoscope. Simulation experiment results showed that the proposed algorithm realized the real-time display of 1280 x 720@60Hz HD video, and using the X-rite color checker as standard colors, the average color difference was reduced about 30% comparing with that before color correction.

Color constancy by characterization of illumination chromaticity

NASA Astrophysics Data System (ADS)

Nikkanen, Jarno T.

2011-05-01

Computational color constancy algorithms play a key role in achieving desired color reproduction in digital cameras. Failure to estimate illumination chromaticity correctly will result in invalid overall colour cast in the image that will be easily detected by human observers. A new algorithm is presented for computational color constancy. Low computational complexity and low memory requirement make the algorithm suitable for resource-limited camera devices, such as consumer digital cameras and camera phones. Operation of the algorithm relies on characterization of the range of possible illumination chromaticities in terms of camera sensor response. The fact that only illumination chromaticity is characterized instead of the full color gamut, for example, increases robustness against variations in sensor characteristics and against failure of diagonal model of illumination change. Multiple databases are used in order to demonstrate the good performance of the algorithm in comparison to the state-of-the-art color constancy algorithms.

Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

NASA Technical Reports Server (NTRS)

Hlaing, Soe; Gilerson, Alexander; Harmal, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

2012-01-01

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

Cross-media color reproduction using the frequency-based spatial gamut mapping algorithm based on human color vision

NASA Astrophysics Data System (ADS)

Wu, Guangyuan; Niu, Shijun; Li, Xiaozhou; Hu, Guichun

2018-04-01

Due to the increasing globalization of printing industry, remoting proofing will become the inevitable development trend. Cross-media color reproduction will occur in different color gamuts using remote proofing technologies, which usually leads to the problem of incompatible color gamut. In this paper, to achieve equivalent color reproduction between a monitor and a printer, a frequency-based spatial gamut mapping algorithm is proposed for decreasing the loss of visual color information. The design of algorithm is based on the contrast sensitivity functions (CSF), which exploited CSF spatial filter to preserve luminance of the high spatial frequencies and chrominance of the low frequencies. First we show a general framework for how to apply CSF spatial filter in retention of relevant visual information. Then we compare the proposed framework with HPMINDE, CUSP, Bala's algorithm. The psychophysical experimental results indicated the good performance of the proposed algorithm.

Enhancing moderate-resolution ocean color products over coastal/inland waters (Conference Presentation)

NASA Astrophysics Data System (ADS)

Pahlevan, Nima; Schott, John R.; Zibordi, Giuseppe

2016-10-01

With the successful launch of Landsat-8 in 2013 followed by a very recent launch of Sentinel-2A, we are entering a new area where frequent moderate resolution water quality products over coastal/inland waters will be available to scientists and operational agencies. Although designed for land observations, the Operational Land Imager (OLI) has proven to provide high-fidelity products in these aquatic systems where coarse-resolution ocean color imagers fail to provide valid observations. High-quality, multi-scale ocean color products can give insights into the biogeochemical/physical processes from the upstream in watersheds, into near-shore regions, and further out in ocean basins. In this research, we describe a robust cross-calibration approach, which facilitates seamless ocean color products at multi scales. The top-of-atmosphere (TOA) OLI imagery is cross-calibrated against near-simultaneous MODIS and VIIRS ocean color observations in high-latitude regions. This allows for not only examining the overall relative performance of OLI but also for characterizing non-uniformity (i.e., banding) across its swath. The uncertainty of this approach is, on average, found to be less than 0.5% in the blue channels. The adjustments made for OLI TOA reflectance products are then validated against in-situ measurements of remote sensing reflectance collected in research cruises or at the AERONET-OC.

Regional vicarious gain adjustment for coastal VIIRS products

NASA Astrophysics Data System (ADS)

Bowers, Jennifer; Arnone, Robert; Ladner, Sherwin; Fargion, Giulietta S.; Lawson, Adam; Martinolich, Paul; Vandermeulen, Ryan

2014-05-01

As part of the Joint Polar Satellite System (JPSS) Ocean Cal/Val Team, Naval Research Lab - Stennis Space Center (NRL-SSC) has been working to facilitate calibration and validation of the Visible Infrared Imaging Radiometer Suite (VIIRS) ocean color products. By relaxing the constraints of the NASA Ocean Biology Processing Group (OBPG) methodology for vicarious calibration of ocean color satellites and utilizing the Aerosol Robotic Network Ocean Color (AERONET-OC) system to provide in situ data, we investigated differences between remotely sensed water leaving radiance and the expected in situ response in coastal areas and compare the results to traditional Marine Optical Buoy (MOBY) calibration/validation activities. An evaluation of the Suomi National Polar-Orbiting Partnership (SNPP)-VIIRS ocean color products was performed in coastal waters using the time series data obtained from the Northern Gulf of Mexico AERONET-OC site, WaveCIS. The coastal site provides different water types with varying complexity of CDOM, sedimentary, and chlorophyll components. Time series data sets were used to develop a vicarious gain adjustment (VGA) at this site, which provides a regional top of the atmospheric (TOA) spectral offset to compare the standard MOBY spectral calibration gain in open ocean waters.

SeaWiFS technical report series. Volume 28: SeaWiFS algorithms, part 1

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor); Acker, James G. (Editor); Mcclain, Charles R.; Arrigo, Kevin; Esaias, Wayne E.; Darzi, Michael; Patt, Frederick S.; Evans, Robert H.; Brown, James W.

1995-01-01

This document provides five brief reports that address several algorithm investigations sponsored by the Calibration and Validation Team (CVT) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. This volume, therefore, has been designated as the first in a series of algorithm volumes. Chapter 1 describes the initial suite of masks, used to prevent further processing of contaminated radiometric data, and flags, which are employed to mark data whose quality (due to a variety of factors) may be suspect. In addition to providing the mask and flag algorithms, this chapter also describes the initial strategy for their implementation. Chapter 2 evaluates various strategies for the detection of clouds and ice in high latitude (polar and sub-polar regions) using Coastal Zone Color Scanner (CZCS) data. Chapter 3 presents an algorithm designed for detecting and masking coccolithosphore blooms in the open ocean. Chapter 4 outlines a proposed scheme for correcting the out-of-band response when SeaWiFS is in orbit. Chapter 5 gives a detailed description of the algorithm designed to apply sensor calibration data during the processing of level-1b data.

Uncertainties and applications of satellite-derived coastal water quality products

NASA Astrophysics Data System (ADS)

Zheng, Guangming; DiGiacomo, Paul M.

2017-12-01

Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely and make optical and environmental measurements in parallel, (ii) more efforts are devoted to identifying optical, ecological, and environmental forerunners of autochthonous water quality issues (e.g., onsite growth of pathogens), and, (iii) environmental processes associated with the source, transport, and transformation of allochthonous issues (e.g., transport of nutrients) are better understood. Accompanying these challenges, the need still exists to conduct fundamental research in satellite ocean color radiometry, including development of more robust atmospheric correction methods as well as inverse models for coastal regions where optical properties of both aerosols and hydrosols are complex.

CFA-aware features for steganalysis of color images

NASA Astrophysics Data System (ADS)

Goljan, Miroslav; Fridrich, Jessica

2015-03-01

Color interpolation is a form of upsampling, which introduces constraints on the relationship between neighboring pixels in a color image. These constraints can be utilized to substantially boost the accuracy of steganography detectors. In this paper, we introduce a rich model formed by 3D co-occurrences of color noise residuals split according to the structure of the Bayer color filter array to further improve detection. Some color interpolation algorithms, AHD and PPG, impose pixel constraints so tight that extremely accurate detection becomes possible with merely eight features eliminating the need for model richification. We carry out experiments on non-adaptive LSB matching and the content-adaptive algorithm WOW on five different color interpolation algorithms. In contrast to grayscale images, in color images that exhibit traces of color interpolation the security of WOW is significantly lower and, depending on the interpolation algorithm, may even be lower than non-adaptive LSB matching.

Color enhancement and image defogging in HSI based on Retinex model

NASA Astrophysics Data System (ADS)

Gao, Han; Wei, Ping; Ke, Jun

2015-08-01

Retinex is a luminance perceptual algorithm based on color consistency. It has a good performance in color enhancement. But in some cases, the traditional Retinex algorithms, both Single-Scale Retinex(SSR) and Multi-Scale Retinex(MSR) in RGB color space, do not work well and will cause color deviation. To solve this problem, we present improved SSR and MSR algorithms. Compared to other Retinex algorithms, we implement Retinex algorithms in HSI(Hue, Saturation, Intensity) color space, and use a parameter αto improve quality of the image. Moreover, the algorithms presented in this paper has a good performance in image defogging. Contrasted with traditional Retinex algorithms, we use intensity channel to obtain reflection information of an image. The intensity channel is processed using a Gaussian center-surround image filter to get light information, which should be removed from intensity channel. After that, we subtract the light information from intensity channel to obtain the reflection image, which only includes the attribute of the objects in image. Using the reflection image and a parameter α, which is an arbitrary scale factor set manually, we improve the intensity channel, and complete the color enhancement. Our experiments show that this approach works well compared with existing methods for color enhancement. Besides a better performance in color deviation problem and image defogging, a visible improvement in the image quality for human contrast perception is also observed.

Real Data and Rapid Results: Ocean Color Data Analysis with Giovanni (GES DISC Interactive Online Visualization and ANalysis Infrastructure)

NASA Technical Reports Server (NTRS)

Acker, J. G.; Leptoukh, G.; Kempler, S.; Gregg, W.; Berrick, S.; Zhu, T.; Liu, Z.; Rui, H.; Shen, S.

2004-01-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step addressing the challenge of using archived Earth Observing System (EOS) data for regional or global studies by developing an infrastructure with a World Wide Web interface which allows online, interactive, data analysis: the GES DISC Interactive Online Visualization and ANalysis Infrastructure, or "Giovanni." Giovanni provides a data analysis environment that is largely independent of underlying data file format. The Ocean Color Time-Series Project has created an initial implementation of Giovanni using monthly Standard Mapped Image (SMI) data products from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) mission. Giovanni users select geophysical parameters, and the geographical region and time period of interest. The system rapidly generates a graphical or ASCII numerical data output. Currently available output options are: Area plot (averaged or accumulated over any available data period for any rectangular area); Time plot (time series averaged over any rectangular area); Hovmeller plots (image view of any longitude-time and latitude-time cross sections); ASCII output for all plot types; and area plot animations. Future plans include correlation plots, output formats compatible with Geographical Information Systems (GIs), and higher temporal resolution data. The Ocean Color Time-Series Project will produce sensor-independent ocean color data beginning with the Coastal Zone Color Scanner (CZCS) mission and extending through SeaWiFS and Moderate Resolution Imaging Spectroradiometer (MODIS) data sets, and will enable incorporation of Visible/lnfrared Imaging Radiometer Suite (VIIRS) data, which will be added to Giovanni. The first phase of Giovanni will also include tutorials demonstrating the use of Giovanni and collaborative assistance in the development of research projects using the SeaWiFS and Ocean Color Time-Series Project data in the online Laboratory for Ocean Color Users (LOCUS). The synergy of Giovanni with high-quality ocean color data provides users with the ability to investigate a variety of important oceanic phenomena, such as coastal primary productivity related to pelagic fisheries, seasonal patterns and interannual variability, interdependence of atmospheric dust aerosols and harmful algal blooms, and the potential effects of climate change on oceanic productivity.

VIIRS Marine Isoprene Product and Initial Applications

NASA Astrophysics Data System (ADS)

Tong, D.; Wang, M.; Wang, B.; Pan, L.; Lee, P.; Goldberg, M.

2017-12-01

Isoprene is a reactive biogenic hydrocarbon that affects atmospheric chemistry, aerosol loading, and cloud formation. We have developed a marine isoprene emission algorithm based on ocean color data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). and global meteorology simulated by NOAA Global Forecasting System (GFS). This algorithm is implemented to generate a multi-year data record (2012-2015) of marine isoprene. The product was validated using historic ocean observations of marine isoprene, as well as in-situ data collected during two recent cruises (SPACES/OASIS in 2014 and ASTRA-OMZ in 2015). Result shows that the VIIRS product has captured the seasonal and spatial variability of global oceanic isoprene emission, which is controlled by a myriad of biological and environmental variables including chlorophyll-a concentration, phytoplankton functional types, seawater light attenuation rate, wind speed, and sea surface temperature. The VIIRS isoprene emission displays considerable seasonal and spatial variations, with peaks in spring over seawater abundant with nutrient inputs. Year to year variations are small, with the annual global emissions ranging from 0.20 to 0.25 Tg C/yr. This new dataset provides the first multi-year observations of global isoprene emissions that can be used to study a variety of environmental issues such as coastal air quality, global aerosol, and cloud formation. Some "early-adopter" applications of this product are briefly discussed.

Corrections to MODIS Terra Calibration and Polarization Trending Derived from Ocean Color Products

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Eplee, Robert E.; Franz, Bryan A.

2014-01-01

Remotely sensed ocean color products require highly accurate top-of-atmosphere (TOA) radiances, on the order of 0.5% or better. Due to incidents both prelaunch and on-orbit, meeting this requirement has been a consistent problem for the MODIS instrument on the Terra satellite, especially in the later part of the mission. The NASA Ocean Biology Processing Group (OBPG) has developed an approach to correct the TOA radiances of MODIS Terra using spatially and temporally averaged ocean color products from other ocean color sensors (such as the SeaWiFS instrument on Orbview-2 or the MODIS instrument on the Aqua satellite). The latest results suggest that for MODIS Terra, both linear polarization parameters of the Mueller matrix are temporally evolving. A change to the functional form of the scan angle dependence improved the quality of the derived coefficients. Additionally, this paper demonstrates that simultaneously retrieving polarization and gain parameters improves the gain retrieval (versus retrieving the gain parameter only).

Blind color isolation for color-channel-based fringe pattern profilometry using digital projection

NASA Astrophysics Data System (ADS)

Hu, Yingsong; Xi, Jiangtao; Chicharo, Joe; Yang, Zongkai

2007-08-01

We present an algorithm for estimating the color demixing matrix based on the color fringe patterns captured from the reference plane or the surface of the object. The advantage of this algorithm is that it is a blind approach to calculating the demixing matrix in the sense that no extra images are required for color calibration before performing profile measurement. Simulation and experimental results convince us that the proposed algorithm can significantly reduce the influence of the color cross talk and at the same time improve the measurement accuracy of the color-channel-based phase-shifting profilometry.

Separation of irradiance and reflectance from observed color images by logarithmical nonlinear diffusion process

NASA Astrophysics Data System (ADS)

Saito, Takahiro; Takahashi, Hiromi; Komatsu, Takashi

2006-02-01

The Retinex theory was first proposed by Land, and deals with separation of irradiance from reflectance in an observed image. The separation problem is an ill-posed problem. Land and others proposed various Retinex separation algorithms. Recently, Kimmel and others proposed a variational framework that unifies the previous Retinex algorithms such as the Poisson-equation-type Retinex algorithms developed by Horn and others, and presented a Retinex separation algorithm with the time-evolution of a linear diffusion process. However, the Kimmel's separation algorithm cannot achieve physically rational separation, if true irradiance varies among color channels. To cope with this problem, we introduce a nonlinear diffusion process into the time-evolution. Moreover, as to its extension to color images, we present two approaches to treat color channels: the independent approach to treat each color channel separately and the collective approach to treat all color channels collectively. The latter approach outperforms the former. Furthermore, we apply our separation algorithm to a high quality chroma key in which before combining a foreground frame and a background frame into an output image a color of each pixel in the foreground frame are spatially adaptively corrected through transformation of the separated irradiance. Experiments demonstrate superiority of our separation algorithm over the Kimmel's separation algorithm.

Surveillance of waste disposal activity at sea using satellite ocean color imagers: GOCI and MODIS

NASA Astrophysics Data System (ADS)

Hong, Gi Hoon; Yang, Dong Beom; Lee, Hyun-Mi; Yang, Sung Ryull; Chung, Hee Woon; Kim, Chang Joon; Kim, Young-Il; Chung, Chang Soo; Ahn, Yu-Hwan; Park, Young-Je; Moon, Jeong-Eon

2012-09-01

Korean Geostationary Ocean Color Imager (GOCI) and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua observations of the variation in ocean color at the sea surface were utilized to monitor the impact of nutrient-rich sewage sludge disposal in the oligotrophic area of the Yellow Sea. MODIS revealed that algal blooms persisted in the spring annually at the dump site in the Yellow Sea since year 2000 to the present. A number of implications of using products of the satellite ocean color imagers were exploited here based on the measurements in the Yellow Sea. GOCI observes almost every hour during the daylight period, every day since June 2011. Therefore, GOCI provides a powerful tool to monitor waste disposal at sea in real time. Tracking of disposal activity from a large tanker was possible hour by hour from the GOCI timeseries images compared to MODIS. Smaller changes in the color of the ocean surface can be easily observed, as GOCI resolves images at smaller scales in space and time in comparison to polar orbiting satellites, e.g., MODIS. GOCI may be widely used to monitor various marine activities in the sea, including waste disposal activity from ships.

SeaWiFS Technical Report Series. Volume 24: SeaWiFS Technical Report Series Cumulative Index, Volumes 1-23

NASA Technical Reports Server (NTRS)

Firestone, Elaine R. (Editor); Hooker, Stanford B. (Editor)

1995-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an eight-year mission. SeaWiFS is expected to be launched in 1995, on the SeaStar satellite, being built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC), has undertaken the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is in the form of NASA Technical Memorandum Number 104566. All reports published are volumes within the series. This particular volume serves as a reference, or guidebook, to the previous 23 volumes and consists of 6 sections including: an errata, an addendum (summaries of various SeaWiFS Working Group Bio-optical Algorithm and Protocols Subgroups Workshops, and other auxiliary information), an index to key words and phrases, a list of all references cited, and lists of acronyms and symbols used. It is the editors' intention to publish a cumulative index of this type after every five volumes in the series. Each index covers the topics published in all previous editions, that is, each new index will include all of the information contained in the preceding indices.

SeaWiFS technical report series. Volume 24: SeaWiFS technical report series cumulative index, volumes 1-23

NASA Technical Reports Server (NTRS)

Hooker, Stanford B. (Editor); Firestone, Elaine R. (Editor)

1995-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an eight-year mission. SeaWiFS is expected to be launched in 1995, on the SeaStar satellite, being built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC), has undertaken the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is the form of NASA Technical Memorandum Number 104566. All reports published are volumes within the series. This particular volume serves as a reference, or guidebook, to the previous 23 volumes and consists of 6 sections including: an errata, an addendum (summaries of various SeaWiFS Working Group Bio-optical Algorithm and Protocols Subgroups Workshops, and other auxiliary information), an index to key words and phrases, a list of all references cited, and lists of acronyms and symbols used. It is the editors' intention to publish a cumulative index of this type after every five volumes in the series. Each index covers the topics published in all previous editions, that is, each new index will include all of the information contained in the preceeding indices.

SeaWiFS technical report series. Volume 18: SeaWiFS technical report series cumulative index: Volumes 1-17

NASA Technical Reports Server (NTRS)

Firestone, Elaine R. (Editor); Hooker, Stanford B. (Editor)

1995-01-01

The Sea-viewing Wide field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS) which ceased operations in 1986 after an eight-year mission. SeaWiFS is expected to be launched in 1995 on the SeaStar satellite, being built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC), has undertaken the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is in the form of NASA Technical Memorandum Number 104566. All reports published are volumes within the series. This particular volume serves as a reference, or guidebook, to the previous 17 volumes and consists of 6 sections including: an errata, an addendum (summaries of various SeaWiFS Working Group Bio-optical Algorithm and Protocols Subgroups Workshops, and other auxiliary information), an index to key words and phrases, a list of all references cited, and lists of acronyms and symbols used. It is the editor's intention to publish a cumulative index of this type after every five volumes in the series. Each index covers the topics published in all previous editions, that is, each new index includes all of the information contained in the preceding indices.

SeaWiFS technical report series. Volume 12, SeaWiFS technical report series cumulative index: Volumes 1-11

NASA Technical Reports Server (NTRS)

Firestone, Elaine R. (Editor); Hooker, Stanford B. (Editor)

1993-01-01

The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) is the follow-on ocean color instrument to the Coastal Zone Color Scanner (CZCS), which ceased operations in 1986, after an 8-year mission. SeaWiFS is expected to be launched in 1994, on the SeaStar satellite, being built by Orbital Sciences Corporation (OSC). The SeaWiFS Project at the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has undertaken the responsibility of documenting all aspects of this mission, which is critical to the ocean color and marine science communities. This documentation, entitled the SeaWiFS Technical Report Series, is in the form of NASA Technical Memorandum Number 104566. All reports published are volumes within the series. This particular volume serves as a reference, or guidebook, to the previous 11 volumes and consists of 6 sections including: an errata, an addendum (a summary of the SeaWiFS Working Group Bio-optical Algorithm and Protocols Subgroups Workshops), an index to keywords and phrases, a list of all references cited, and lists of acronyms and symbols used. It is the editors' intention to publish a cumulative index of this type after every five volumes in the series. This will cover the topics published in all previous editions of the indices, that is, each new index will include all of the information contained in the preceding indices.

Remote sensing of ocean color and detection of chlorophyll content

NASA Technical Reports Server (NTRS)

Deschamps, P. Y.; Lecompte, P.; Viollier, M.

1977-01-01

The chlorophyll enrichment of the water in an equatorial upwelling was surveyed and described with the aid of a radiometer specially designed for the airborne measurement of ocean color. A relation is proposed between airborne measurement of difference of albedos at two wavelengths in the blue and green, and the concentration of chlorophyll in the ocean.

Then Why Do They Call Earth the Blue Planet?

NASA Technical Reports Server (NTRS)

2005-01-01

While the most common photographs of Earth taken from space show the planet covered in blue water, NASA has managed to produce detailed color images, using satellite imagery, that show the remarkable variation of colors that actually make up the oceanic surface. An ocean s color is determined by the interaction of surface waters with sunlight, and surface waters can contain any number of different particles and dissolved substances, which could then change the color. Then Why Do They Call Earth the Blue Planet? The particles are mostly phytoplankton, the microscopic, single-celled ocean plants that are the primary food source for much marine life. Remote detection of phytoplankton provides information about the uptake and cycling of carbon by the ocean through photosynthesis, as well as the overall health of the water. Inorganic particles and substances dissolved in the water also affect its color, particularly in coastal regions. Satellite images can be used to calculate the concentrations of these materials in surface waters, as well as the levels of biological activity. The satellites allow a global view that is not available from ship or shore. NASA s orbiting satellites offer a unique vantage point for studying the oceans. By resolving the biological, chemical, and physical conditions in surface waters, they have allowed the oceanographic community to make huge leaps in its understanding of oceanographic processes on regional and global fronts. The study of ocean color, in particular, has been integral in helping researchers understand the natural and human-induced changes in the global environment and establishing the role of the oceans in the biochemical cycles of elements that influence the climate and the distribution of life on Earth.

Coastal Zone Color Scanner (CZCS): Imagery of near-surface phytoplankton pigment concentrations from the first coastal ocean dynamics experiment (CODE-1), March - July 1981

NASA Technical Reports Server (NTRS)

Abbott, M. R.; Zion, P. M.

1984-01-01

As part of the first Coastal Ocean Dynamics Experiment, images of ocean color were collected from late March until late July, 1981, by the Coastal Zone Color Scanner aboard Nimbus-7. Images that had sufficient cloud-free area to be of interest were processed to yield near-surface phytoplankton pigment concentrations. These images were then remapped to a fixed equal-area grid. This report contains photographs of the digital images and a brief description of the processing methods.

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

NASA Astrophysics Data System (ADS)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

The dissolved yellow substance and the shades of blue in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Morel, A.; Gentili, B.

2009-11-01

When the nominal algorithms commonly in use in Space Agencies are applied to satellite Ocean Color data, the retrieved chlorophyll concentrations in the Mediterranean Sea are recurrently notable overestimates of the field values. Accordingly, several regionally tuned algorithms have been proposed in the past to correct for this deviation. Actually, the blueness of the Mediterranean waters is not as deep as expected from the actual (low) chlorophyll content, and the modified algorithms account for this peculiarity. Among the possible causes for such a deviation, an excessive amount of yellow substance (or of chromophoric dissolved organic matter, CDOM) has been frequently cited. This conjecture is presently tested, by using a new technique simply based on the simultaneous consideration of marine reflectance determined at four spectral bands, namely at 412, 443, 490, and 555 nm, available on the NASA-SeaWiFS sensor (Sea-viewing Wide Field-of-view Sensor). It results from this test that the concentration in yellow colored material (quantified as ay, the absorption coefficient of this material at 443 nm) is about twice that one observed in the nearby Atlantic Ocean at the same latitude. There is a strong seasonal signal, with maximal ay values in late fall and winter, an abrupt decrease beginning in spring, and then a flat minimum during the summer months, which plausibly results from the intense photo-bleaching process favored by the high level of sunshine in these areas. Systematically, the ay values, reproducible from year to year, are higher in the western basin compared with those in the eastern basin (by about 50%). The relative importance of the river discharges into this semi-enclosed sea, as well as the winter deep vertical mixing occurring in the northern parts of the basins may explain the high yellow substance background. The regionally tuned [Chl] algorithms, actually reflect the presence of an excess of CDOM with respect to its standard (Chl-related) values. When corrected for the presence of the actual CDOM content, the [Chl] values as derived via the nominal algorithms are restored to more realistic values, i.e., approximately divided by about two; the strong autumnal increase is smoothed whereas the spring bloom remains as an isolated feature.

False colors removal on the YCr-Cb color space

NASA Astrophysics Data System (ADS)

Tomaselli, Valeria; Guarnera, Mirko; Messina, Giuseppe

2009-01-01

Post-processing algorithms are usually placed in the pipeline of imaging devices to remove residual color artifacts introduced by the demosaicing step. Although demosaicing solutions aim to eliminate, limit or correct false colors and other impairments caused by a non ideal sampling, post-processing techniques are usually more powerful in achieving this purpose. This is mainly because the input of post-processing algorithms is a fully restored RGB color image. Moreover, post-processing can be applied more than once, in order to meet some quality criteria. In this paper we propose an effective technique for reducing the color artifacts generated by conventional color interpolation algorithms, in YCrCb color space. This solution efficiently removes false colors and can be executed while performing the edge emphasis process.

Atmospheric correction over case 2 waters with an iterative fitting algorithm: relative humidity effects.

PubMed

Land, P E; Haigh, J D

1997-12-20

In algorithms for the atmospheric correction of visible and near-IR satellite observations of the Earth's surface, it is generally assumed that the spectral variation of aerosol optical depth is characterized by an Angström power law or similar dependence. In an iterative fitting algorithm for atmospheric correction of ocean color imagery over case 2 waters, this assumption leads to an inability to retrieve the aerosol type and to the attribution to aerosol spectral variations of spectral effects actually caused by the water contents. An improvement to this algorithm is described in which the spectral variation of optical depth is calculated as a function of aerosol type and relative humidity, and an attempt is made to retrieve the relative humidity in addition to aerosol type. The aerosol is treated as a mixture of aerosol components (e.g., soot), rather than of aerosol types (e.g., urban). We demonstrate the improvement over the previous method by using simulated case 1 and case 2 sea-viewing wide field-of-view sensor data, although the retrieval of relative humidity was not successful.

Application of an optimization algorithm to satellite ocean color imagery: A case study in Southwest Florida coastal waters

NASA Astrophysics Data System (ADS)

Hu, Chuanmin; Lee, Zhongping; Muller-Karger, Frank E.; Carder, Kendall L.

2003-05-01

A spectra-matching optimization algorithm, designed for hyperspectral sensors, has been implemented to process SeaWiFS-derived multi-spectral water-leaving radiance data. The algorithm has been tested over Southwest Florida coastal waters. The total spectral absorption and backscattering coefficients can be well partitioned with the inversion algorithm, resulting in RMS errors generally less than 5% in the modeled spectra. For extremely turbid waters that come from either river runoff or sediment resuspension, the RMS error is in the range of 5-15%. The bio-optical parameters derived in this optically complex environment agree well with those obtained in situ. Further, the ability to separate backscattering (a proxy for turbidity) from the satellite signal makes it possible to trace water movement patterns, as indicated by the total absorption imagery. The derived patterns agree with those from concurrent surface drifters. For waters where CDOM overwhelmingly dominates the optical signal, however, the procedure tends to regard CDOM as the sole source of absorption, implying the need for better atmospheric correction and for adjustment of some model coefficients for this particular region.

An overview of mesoscales distribution of ocean color in the North Atlantic

NASA Technical Reports Server (NTRS)

Yentsch, C. S.

1989-01-01

The spatial changes in phytoplankton abundance is the result of regional differences in the amount of nutrient fluxed into the euphotic zone. The energy contributing to this flux is derived from ocean currents. A close coupling between physics and biology of the system accounts for mesoscale features associated with fluid dynamics being reflected by changes in ocean color.

Adaboost multi-view face detection based on YCgCr skin color model

NASA Astrophysics Data System (ADS)

Lan, Qi; Xu, Zhiyong

2016-09-01

Traditional Adaboost face detection algorithm uses Haar-like features training face classifiers, whose detection error rate is low in the face region. While under the complex background, the classifiers will make wrong detection easily to the background regions with the similar faces gray level distribution, which leads to the error detection rate of traditional Adaboost algorithm is high. As one of the most important features of a face, skin in YCgCr color space has good clustering. We can fast exclude the non-face areas through the skin color model. Therefore, combining with the advantages of the Adaboost algorithm and skin color detection algorithm, this paper proposes Adaboost face detection algorithm method that bases on YCgCr skin color model. Experiments show that, compared with traditional algorithm, the method we proposed has improved significantly in the detection accuracy and errors.

Color transfer algorithm in medical images

NASA Astrophysics Data System (ADS)

Wang, Weihong; Xu, Yangfa

2007-12-01

In digital virtual human project, image data acquires from the freezing slice of human body specimen. The color and brightness between a group of images of a certain organ could be quite different. The quality of these images could bring great difficulty in edge extraction, segmentation, as well as 3D reconstruction process. Thus it is necessary to unify the color of the images. The color transfer algorithm is a good algorithm to deal with this kind of problem. This paper introduces the principle of this algorithm and uses it in the medical image processing.

Daytime sea fog retrieval based on GOCI data: a case study over the Yellow Sea.

PubMed

Yuan, Yibo; Qiu, Zhongfeng; Sun, Deyong; Wang, Shengqiang; Yue, Xiaoyuan

2016-01-25

In this paper, a new daytime sea fog detection algorithm has been developed by using Geostationary Ocean Color Imager (GOCI) data. Based on spectral analysis, differences in spectral characteristics were found over different underlying surfaces, which include land, sea, middle/high level clouds, stratus clouds and sea fog. Statistical analysis showed that the Rrc (412 nm) (Rayleigh Corrected Reflectance) of sea fog pixels is approximately 0.1-0.6. Similarly, various band combinations could be used to separate different surfaces. Therefore, three indices (SLDI, MCDI and BSI) were set to discern land/sea, middle/high level clouds and fog/stratus clouds, respectively, from which it was generally easy to extract fog pixels. The remote sensing algorithm was verified using coastal sounding data, which demonstrated that the algorithm had the ability to detect sea fog. The algorithm was then used to monitor an 8-hour sea fog event and the results were consistent with observational data from buoys data deployed near the Sheyang coast (121°E, 34°N). The goal of this study was to establish a daytime sea fog detection algorithm based on GOCI data, which shows promise for detecting fog separately from stratus.

Estimators of primary production for interpretation of remotely sensed data on ocean color

NASA Technical Reports Server (NTRS)

Platt, Trevor; Sathyendranath, Shubha

1993-01-01

The theoretical basis is explained for some commonly used estimators of daily primary production in a vertically uniform water column. These models are recast into a canonical form, with dimensionless arguments, to facilitate comparison with each other and with an analytic solution. The limitations of each model are examined. The values of the photoadaptation parameter I(k) observed in the ocean are analyzed, and I(k) is used as a scale to normalize the surface irradiance. The range of this scaled irradiance is presented. An equation is given for estimation of I(k) from recent light history. It is shown how the models for water column production can be adapted for estimation of the production in finite layers. The distinctions between model formulation, model implementation and model evaluation are discussed. Recommendations are given on the choice of algorithm for computation of daily production according to the degree of approximation acceptable in the result.

Merging Ocean Color Data From Multiple Missions. Chapter 6

NASA Technical Reports Server (NTRS)

Gregg, Watson W.

2003-01-01

Oceanic phytoplankton may play an important role in the cycling of carbon on the Earth, through the uptake of carbon dioxide in the process of photosynthesis. Although they are ubiquitous in the global oceans, their abundances and dynamics are difficult to estimate, primarily due to the vast spatial extent of the oceans and the short time scales over which their abundances can change. Consequently, the effects of oceanic phytoplankton on biogeochemical cycling, climate change, and fisheries are not well known. In response to the potential importance of phytoplankton in the global carbon cycle and the lack of comprehensive data, NASA and the international community have established high priority satellite missions designed to acquire and produce high quality ocean color data (Table 6.1). Ten of the missions are routine global observational missions: the Ocean Color and Temperature Sensor (OCTS), the Polarization and Directionality of the Earth's Reflectances sensor (POLDER), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Moderate Resolution Imaging Spectrometer-AM (MODIS-AM), Medium Resolution Imaging Spectrometer (MERIS), Global Imager (GLI), MODIS-PM, Super-GLI (S-GLI), and the Visible/Infrared Imager and Radiometer Suite (VIIRS) on the NPOESS Preparatory Project (NPP) and the National Polar-orbiting Operational Environmental Satellite System (NPOESS). In addition, there are several other missions capable of providing ocean color data on smaller scales. Most of these missions contain the spectral band complement considered necessary to derive oceanic chlorophyll concentrations and other related parameters. Many contain additional bands that can provide important ancillary information about the optical and biological state of the oceans.

Remote Sensing of the Absorption Coefficients and Chlorophyll a Concentration in the U.S. Southern Middle Atlantic Bight from SeaWiFS and MODIS-Aqua

NASA Technical Reports Server (NTRS)

Pan, Xiaoju; Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.

2008-01-01

At present, satellite remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of satellite sensors in oceanic waters. In this study, field measurements collected on a series of cruises within U.S. southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of satellite ocean color products in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in satellite retrievals of absorption coefficients of phytoplankton (a(sub ph)), colored dissolved organic matter (CDOM) (a(sub g)), non-pigmented particles (a(sub d)), and non-pigmented particles plus CDOM (a(sub dg)), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing reflectance (R(sub rs)) ratios. The validation match-ups showed that the mean absolute percent differences (MAPD) were typically less than 35%, although higher errors were found for a(sub d) retrievals. Seasonal and spatial variability of satellite-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35-70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30-45% for phytoplankton and 0-20% for non-pigmented particles. The overestimation of [Chl_a] from the operational satellite algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment, but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.

Adjustments to the MODIS Terra Radiometric Calibration and Polarization Sensitivity in the 2010 Reprocessing

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The Moderate-Resolution Imaging Spectroradiometer (MODIS) on NASA s Earth Observing System (EOS) satellite Terra provides global coverage of top-of-atmosphere (TOA) radiances that have been successfully used for terrestrial and atmospheric research. The MODIS Terra ocean color products, however, have been compromised by an inadequate radiometric calibration at the short wavelengths. The Ocean Biology Processing Group (OBPG) at NASA has derived radiometric corrections using ocean color products from the SeaWiFS sensor as truth fields. In the R2010.0 reprocessing, these corrections have been applied to the whole mission life span of 10 years. This paper presents the corrections to the radiometric gains and to the instrument polarization sensitivity, demonstrates the improvement to the Terra ocean color products, and discusses issues that need further investigation. Although the global averages of MODIS Terra ocean color products are now in excellent agreement with those of SeaWiFS and MODIS Aqua, and image quality has been significantly improved, the large corrections applied to the radiometric calibration and polarization sensitivity require additional caution when using the data.

Joint retrieval of aerosol and water-leaving radiance from multispectral, multiangular and polarimetric measurements over ocean

NASA Astrophysics Data System (ADS)

Xu, Feng; Dubovik, Oleg; Zhai, Peng-Wang; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Litvinov, Pavel; Bovchaliuk, Andrii; Garay, Michael J.; van Harten, Gerard; Davis, Anthony B.

2016-07-01

An optimization approach has been developed for simultaneous retrieval of aerosol properties and normalized water-leaving radiance (nLw) from multispectral, multiangular, and polarimetric observations over ocean. The main features of the method are (1) use of a simplified bio-optical model to estimate nLw, followed by an empirical refinement within a specified range to improve its accuracy; (2) improved algorithm convergence and stability by applying constraints on the spatial smoothness of aerosol loading and Chlorophyll a (Chl a) concentration across neighboring image patches and spectral constraints on aerosol optical properties and nLw across relevant bands; and (3) enhanced Jacobian calculation by modeling and storing the radiative transfer (RT) in aerosol/Rayleigh mixed layer, pure Rayleigh-scattering layers, and ocean medium separately, then coupling them to calculate the field at the sensor. This approach avoids unnecessary and time-consuming recalculations of RT in unperturbed layers in Jacobian evaluations. The Markov chain method is used to model RT in the aerosol/Rayleigh mixed layer and the doubling method is used for the uniform layers of the atmosphere-ocean system. Our optimization approach has been tested using radiance and polarization measurements acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) over the AERONET USC_SeaPRISM ocean site (6 February 2013) and near the AERONET La Jolla site (14 January 2013), which, respectively, reported relatively high and low aerosol loadings. Validation of the results is achieved through comparisons to AERONET aerosol and ocean color products. For comparison, the USC_SeaPRISM retrieval is also performed by use of the Generalized Retrieval of Aerosol and Surface Properties algorithm (Dubovik et al., 2011). Uncertainties of aerosol and nLw retrievals due to random and systematic instrument errors are analyzed by truth-in/truth-out tests with three Chl a concentrations, five aerosol loadings, three different types of aerosols, and nine combinations of solar incidence and viewing geometries.

Applications of MODIS Fluorescence Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity in Coastal and Estuarine Waters

NASA Astrophysics Data System (ADS)

Fischer, A.; Ryan, J. P.; Moreno-Madriñán, M. J.

2012-12-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS), calibration updates, improved aerosol retrievals, and new aerosol models have led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean-color. This has opened the way for studying coastal ocean phenomena and processes at finer spatial scales. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and increases in local concentrations of phytoplankton, which could result in harmful algal blooms. In two case studies we present improved and validated MODIS coastal observations of fluorescence line height (FLH) to: (1) assess trends in water quality for Tampa Bay, Florida; and (2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California, as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and imagery from Tampa Bay, we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout this large, optically complex estuarine system. A systematic analysis of sampling sites throughout the bay illustrates that the correlations between FLH and in situ chlorophyll-a are influenced by water quality parameters of total nitrogen, total phosphorous, turbidity and biological oxygen demand. Sites that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and cyclonic bay-wide circulation transports these nutrients to a northern Bay bloom incubation region. Both of these case studies illustrate the utility of improved MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

Asian dust aerosol: Optical effect on satellite ocean color signal and a scheme of its correction

NASA Astrophysics Data System (ADS)

Fukushima, H.; Toratani, M.

1997-07-01

The paper first exhibits the influence of the Asian dust aerosol (KOSA) on a coastal zone color scanner (CZCS) image which records erroneously low or negative satellite-derived water-leaving radiance especially in a shorter wavelength region. This suggests the presence of spectrally dependent absorption which was disregarded in the past atmospheric correction algorithms. On the basis of the analysis of the scene, a semiempirical optical model of the Asian dust aerosol that relates aerosol single scattering albedo (ωA) to the spectral ratio of aerosol optical thickness between 550 nm and 670 nm is developed. Then, as a modification to a standard CZCS atmospheric correction algorithm (NASA standard algorithm), a scheme which estimates pixel-wise aerosol optical thickness, and in turn ωA, is proposed. The assumption of constant normalized water-leaving radiance at 550 nm is adopted together with a model of aerosol scattering phase function. The scheme is combined to the standard algorithm, performing atmospheric correction just the same as the standard version with a fixed Angstrom coefficient except in the case where the presence of Asian dust aerosol is detected by the lowered satellite-derived Angstrom exponent. Some of the model parameter values are determined so that the scheme does not produce any spatial discontinuity with the standard scheme. The algorithm was tested against the Japanese Asian dust CZCS scene with parameter values of the spectral dependency of ωA, first statistically determined and second optimized for selected pixels. Analysis suggests that the parameter values depend on the assumed Angstrom coefficient for standard algorithm, at the same time defining the spatial extent of the area to apply the Asian dust scheme. The algorithm was also tested for a Saharan dust scene, showing the relevance of the scheme but with different parameter setting. Finally, the algorithm was applied to a data set of 25 CZCS scenes to produce a monthly composite of pigment concentration for April 1981. Through these analyses, the modified algorithm is considered robust in the sense that it operates most compatibly with the standard algorithm yet performs adaptively in response to the magnitude of the dust effect.

Validation of ocean color sensors using a profiling hyperspectral radiometer

NASA Astrophysics Data System (ADS)

Ondrusek, M. E.; Stengel, E.; Rella, M. A.; Goode, W.; Ladner, S.; Feinholz, M.

2014-05-01

Validation measurements of satellite ocean color sensors require in situ measurements that are accurate, repeatable and traceable enough to distinguish variability between in situ measurements and variability in the signal being observed on orbit. The utility of using a Satlantic Profiler II equipped with HyperOCR radiometers (Hyperpro) for validating ocean color sensors is tested by assessing the stability of the calibration coefficients and by comparing Hyperpro in situ measurements to other instruments and between different Hyperpros in a variety of water types. Calibration and characterization of the NOAA Satlantic Hyperpro instrument is described and concurrent measurements of water-leaving radiances conducted during cruises are presented between this profiling instrument and other profiling, above-water and moored instruments. The moored optical instruments are the US operated Marine Optical BuoY (MOBY) and the French operated Boussole Buoy. In addition, Satlantic processing versions are described in terms of accuracy and consistency. A new multi-cast approach is compared to the most commonly used single cast method. Analysis comparisons are conducted in turbid and blue water conditions. Examples of validation matchups with VIIRS ocean color data are presented. With careful data collection and analysis, the Satlantic Hyperpro profiling radiometer has proven to be a reliable and consistent tool for satellite ocean color validation.

Visible and infrared imaging radiometers for ocean observations

NASA Technical Reports Server (NTRS)

Barnes, W. L.

1977-01-01

The current status of visible and infrared sensors designed for the remote monitoring of the oceans is reviewed. Emphasis is placed on multichannel scanning radiometers that are either operational or under development. Present design practices and parameter constraints are discussed. Airborne sensor systems examined include the ocean color scanner and the ocean temperature scanner. The costal zone color scanner and advanced very high resolution radiometer are reviewed with emphasis on design specifications. Recent technological advances and their impact on sensor design are examined.

Seahawk: An Advanced Cubesat Mission for Sustained Ocean Color Monitoring

NASA Technical Reports Server (NTRS)

Morrison, John M.; Jeffrey, Hazel; Gorter, Hessel; Anderson, Pamela; Clark, Craig; Holmes, Alan; Feldman, Gene C.; Pratt, Frederick S.

2016-01-01

Sustained ocean color monitoring is vital to understanding the marine ecosystem. It has been identified as an Essential Climate Variable (ECV) and is a vital parameter in understanding long-term climate change. Furthermore, observations can be beneficial in observing oil spills, harmful algal blooms and the health of fisheries. Space-based remote sensing, through MERIS, SeaWiFS and MODIS instruments, have provided a means of observing the vast area covered by the ocean which would otherwise be impossible using ships alone. However, the large pixel size makes measurements of lakes, rivers, estuaries and coastal zones difficult. Furthermore, retirement of a number of widely used and relied upon ocean observation instruments, particularly MERIS and SeaWiFS, leaves a significant gap in ocean color observation opportunities. This paper presents an overview of the SeaHawk mission, a collaborative effort between Clyde Space Ltd., the University of North Carolina Wilmington, Cloudland Instruments, and Goddard Spaceflight Center, funded by the Gordon and Betty Moore Foundation. The goal of the project is to enhance the ability to observe ocean color in high temporal and spatial resolution through use of a low-cost, next-generation ocean color sensor flown aboard a CubeSat. The final product will be 530 times smaller (0.0034 vs 1.81cu m) and 115 time less massive (3.4 vs 390.0 kg) but with a ground resolution 10 times better whilst maintaining a signal/noise ratio 50 that of SeaWiFs. This paper will describe the objectives of the mission, outline the payload specification and the spacecraft platform to support it.

Colors after the Storms

NASA Image and Video Library

2015-10-26

Damaging heavy rains fell on South Carolina in the southeastern United States at the beginning of October 2015. Much of that water had, by mid October, flowed into the Atlantic Ocean bringing with it heavy loads of sediment, nutrients, and dissolved organic material. The above VIIRS image shows the runoff as it interacts with ocean currents on October 15, 2015. Credit: NASA/Goddard/SuomiNPP/VIIRS via NASA's OceanColor

Characterizing bio-optical and ecological features of algal bloom waters for detection and tracking from space

NASA Astrophysics Data System (ADS)

Ahmed, S.; Amin, R.; Gladkova, I.; Gilerson, A.; Grossberg, M.; Hlaing, S.; Shariar, F.; Alabi, P.

2010-04-01

The detection and monitoring of harmful algal blooms using in-situ field measurements is both labor intensive and is practically limited on achievable temporal and spatial resolutions, since field measurements are typically carried out at a series of discrete points and at discrete times, with practical limitations on temporal continuity. The planning and preparation of remedial measures to reduce health risks, etc., requires detection approaches which can effectively cover larger areas with contiguous spatial resolutions, and at the same time offer a more comprehensive and contemporaneous snapshot of entire blooms as they occur. This is beyond capabilities of in-situ measurements and it is in this context that satellite Ocean Color sensors offer potential advantages for bloom detection and monitoring. In this paper we examine the applications and limitations of an approach we have recently developed for the detection of K. brevis blooms from satellite Ocean Color Sensors measurements, the Red Band Difference Technique, and compare it to other detection algorithm approaches, including a new statistical based approach also proposed here. To achieve more uniform standards of comparisons, the performance of different techniques for detection are applied to the same specific verified blooms occurring off the West Florida Shelf (WFS) that have been verified by in-situ measurements.

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

NASA Technical Reports Server (NTRS)

Palacios, Sherry L.; Schafer, Chris; Broughton, Jennifer; Guild, Liane S.; Kudela, Raphael M.

2013-01-01

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Color reproduction and processing algorithm based on real-time mapping for endoscopic images.

PubMed

Khan, Tareq H; Mohammed, Shahed K; Imtiaz, Mohammad S; Wahid, Khan A

2016-01-01

In this paper, we present a real-time preprocessing algorithm for image enhancement for endoscopic images. A novel dictionary based color mapping algorithm is used for reproducing the color information from a theme image. The theme image is selected from a nearby anatomical location. A database of color endoscopy image for different location is prepared for this purpose. The color map is dynamic as its contents change with the change of the theme image. This method is used on low contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. It can also be applied to enhance the tone of color images. The statistic visual representation and universal image quality measures show that the proposed method can highlight the mucosa structure compared to other methods. The color similarity has been verified using Delta E color difference, structure similarity index, mean structure similarity index and structure and hue similarity. The color enhancement was measured using color enhancement factor that shows considerable improvements. The proposed algorithm has low and linear time complexity, which results in higher execution speed than other related works.

Impulsive noise removal from color video with morphological filtering

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly

2017-09-01

This paper deals with impulse noise removal from color video. The proposed noise removal algorithm employs a switching filtering for denoising of color video; that is, detection of corrupted pixels by means of a novel morphological filtering followed by removal of the detected pixels on the base of estimation of uncorrupted pixels in the previous scenes. With the help of computer simulation we show that the proposed algorithm is able to well remove impulse noise in color video. The performance of the proposed algorithm is compared in terms of image restoration metrics with that of common successful algorithms.

BOUSSOLE: A Joint CNRS-INSU, ESA, CNES, and NASA Ocean Color Calibration and Validation Activity

NASA Technical Reports Server (NTRS)

Antoine, David; Chami, Malik; Claustre, Herve; d'Ortenzio, Fabrizio; Morel, Andre; Becu, Guislain; Gentili, Bernard; Louis, Francis; Ras, Josephine; Roussier, Emmanuel;

Ocean Optics Protocols for Satellite Ocean Color Sensor Validation. Revised

NASA Technical Reports Server (NTRS)

Fargion, Giulietta S.; Mueller, James L.

2000-01-01

The document stipulates protocols for measuring bio-optical and radiometric data for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project activities and algorithm development. This document supersedes the earlier version (Mueller and Austin 1995) published as Volume 25 in the SeaWiFS Technical Report Series. This document marks a significant departure from, and improvement on, theformat and content of Mueller and Austin (1995). The authorship of the protocols has been greatly broadened to include experts specializing in some key areas. New chapters have been added to provide detailed and comprehensive protocols for stability monitoring of radiometers using portable sources, abovewater measurements of remote-sensing reflectance, spectral absorption measurements for discrete water samples, HPLC pigment analysis and fluorometric pigment analysis. Protocols were included in Mueller and Austin (1995) for each of these areas, but the new treatment makes significant advances in each topic area. There are also new chapters prescribing protocols for calibration of sun photometers and sky radiance sensors, sun photometer and sky radiance measurements and analysis, and data archival. These topic areas were barely mentioned in Mueller and Austin (1995).

Automatically Generated Algorithms for the Vertex Coloring Problem

PubMed Central

Contreras Bolton, Carlos; Gatica, Gustavo; Parada, Víctor

2013-01-01

The vertex coloring problem is a classical problem in combinatorial optimization that consists of assigning a color to each vertex of a graph such that no adjacent vertices share the same color, minimizing the number of colors used. Despite the various practical applications that exist for this problem, its NP-hardness still represents a computational challenge. Some of the best computational results obtained for this problem are consequences of hybridizing the various known heuristics. Automatically revising the space constituted by combining these techniques to find the most adequate combination has received less attention. In this paper, we propose exploring the heuristics space for the vertex coloring problem using evolutionary algorithms. We automatically generate three new algorithms by combining elementary heuristics. To evaluate the new algorithms, a computational experiment was performed that allowed comparing them numerically with existing heuristics. The obtained algorithms present an average 29.97% relative error, while four other heuristics selected from the literature present a 59.73% error, considering 29 of the more difficult instances in the DIMACS benchmark. PMID:23516506

Model-based color halftoning using direct binary search.

PubMed

Agar, A Ufuk; Allebach, Jan P

2005-12-01

In this paper, we develop a model-based color halftoning method using the direct binary search (DBS) algorithm. Our method strives to minimize the perceived error between the continuous tone original color image and the color halftone image. We exploit the differences in how the human viewers respond to luminance and chrominance information and use the total squared error in a luminance/chrominance based space as our metric. Starting with an initial halftone, we minimize this error metric using the DBS algorithm. Our method also incorporates a measurement based color printer dot interaction model to prevent the artifacts due to dot overlap and to improve color texture quality. We calibrate our halftoning algorithm to ensure accurate colorant distributions in resulting halftones. We present the color halftones which demonstrate the efficacy of our method.

Quantum Color Image Encryption Algorithm Based on A Hyper-Chaotic System and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Tan, Ru-Chao; Lei, Tong; Zhao, Qing-Min; Gong, Li-Hua; Zhou, Zhi-Hong

2016-12-01

To improve the slow processing speed of the classical image encryption algorithms and enhance the security of the private color images, a new quantum color image encryption algorithm based on a hyper-chaotic system is proposed, in which the sequences generated by the Chen's hyper-chaotic system are scrambled and diffused with three components of the original color image. Sequentially, the quantum Fourier transform is exploited to fulfill the encryption. Numerical simulations show that the presented quantum color image encryption algorithm possesses large key space to resist illegal attacks, sensitive dependence on initial keys, uniform distribution of gray values for the encrypted image and weak correlation between two adjacent pixels in the cipher-image.

Inter-Sensor Comparison of Satellite Ocean Color Products from GOCI and MODIS

DTIC Science & Technology

2013-02-26

current map for this region. However the NOCOM modeled and GOCI measured data need to be validate using in-situ measurements. ...collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION...Ocean Model (NCOM). 15. SUBJECT TERMS satellite ocean color products, GOCI, MODIS, phytoplankton 16. SECURITY CLASSIFICATION OF: a. REPORT

The Hyperspectral Imager for the Coastal Ocean (HICO): Sensor and Data Processing Overview

DTIC Science & Technology

2010-01-20

backscattering coefficients, and others. Several of these software modules will be developed within the Automated Processing System (APS), a data... Automated Processing System (APS) NRL developed APS, which processes satellite data into ocean color data products. APS is a collection of methods...used for ocean color processing which provide the tools for the automated processing of satellite imagery [1]. These tools are in the process of

How the wet side of NOAA (NMFS and NOS) is using JPSS data

NASA Astrophysics Data System (ADS)

Wilson, C.

2016-12-01

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on the JPSS satellite, launched in 2011, is the most recent of a series of US ocean-color satellite measurements. With the launch of VIIRS we now have a nineteen-year continuous time-series of ocean-color measurements, starting with SeaWiFS (Sea-Viewing Wide Field-of-View Sensor), launched in 1997, and followed by MODIS (Moderate Resolution Imaging Spectroradiometer) on the Aqua satellite that was launched in 2002. What is significant about the VIIRS launch is that it represents a transition from ocean-color satellite data being generated from research missions launched by NASA to an operational data-stream that NOAA has responsibility for. In this presentation I will present a broad array of projects that will demonstrate how NOS (National Ocean Service) and NMFS (National Marine Fisheries Service) are using VIIRS data, both ocean-color and sea-surface temperature. Since fisheries and ecosystems studies typically require long time series, on the order of years to decades, the utility of the VIIRS data is that it has been intercalibrated with legacy data-streams to provide a climate data record. The majority of the projects highlighted were developed as part of the NOAA ocean satellite course that has been conducted annually since 2005.

Satellite Ocean Color Sensor Design Concepts and Performance Requirements

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Meister, Gerhard; Monosmith, Bryan

2014-01-01

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to 800 nanometers with three additional discrete near infrared (NIR) and shortwave infrared (SWIR) ocean aerosol correction bands. Also, to avoid drift in sensor sensitivity from being interpreted as environmental change, climate change research requires rigorous monitoring of sensor stability. For SeaWiFS, monthly lunar imaging accurately tracked stability at an accuracy of approximately 0.1% that allowed the data to be used for climate studies [2]. It is now acknowledged by the international community that future missions and sensor designs need to accommodate lunar calibrations. An overview of ocean color remote sensing and a review of the progress made in ocean color remote sensing and the variety of research applications derived from global satellite ocean color data are provided. The purpose of this chapter is to discuss the design options for ocean color satellite radiometers, performance and testing criteria, and sensor components (optics, detectors, electronics, etc.) that must be integrated into an instrument concept. These ultimately dictate the quality and quantity of data that can be delivered as a trade against mission cost. Historically, science and sensor technology have advanced in a "leap-frog" manner in that sensor design requirements for a mission are defined many years before a sensor is launched and by the end of the mission, perhaps 15-20 years later, science applications and requirements are well beyond the capabilities of the sensor. Section 3 provides a summary of historical mission science objectives and sensor requirements. This progression is expected to continue in the future as long as sensor costs can be constrained to affordable levels and still allow the incorporation of new technologies without incurring unacceptable risk to mission success. The IOCCG Report Number 13 discusses future ocean biology mission Level-1 requirements in depth.

Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations

PubMed Central

Nadiga, Sudhir; Mehra, Avichal; Bayler, Eric; Behringer, David

2016-01-01

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites and in situ physical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA's operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed—signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN's generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series. PMID:26819586

Parameterization of typhoon-induced ocean cooling using temperature equation and machine learning algorithms: an example of typhoon Soulik (2013)

NASA Astrophysics Data System (ADS)

Wei, Jun; Jiang, Guo-Qing; Liu, Xin

2017-09-01

This study proposed three algorithms that can potentially be used to provide sea surface temperature (SST) conditions for typhoon prediction models. Different from traditional data assimilation approaches, which provide prescribed initial/boundary conditions, our proposed algorithms aim to resolve a flow-dependent SST feedback between growing typhoons and oceans in the future time. Two of these algorithms are based on linear temperature equations (TE-based), and the other is based on an innovative technique involving machine learning (ML-based). The algorithms are then implemented into a Weather Research and Forecasting model for the simulation of typhoon to assess their effectiveness, and the results show significant improvement in simulated storm intensities by including ocean cooling feedback. The TE-based algorithm I considers wind-induced ocean vertical mixing and upwelling processes only, and thus obtained a synoptic and relatively smooth sea surface temperature cooling. The TE-based algorithm II incorporates not only typhoon winds but also ocean information, and thus resolves more cooling features. The ML-based algorithm is based on a neural network, consisting of multiple layers of input variables and neurons, and produces the best estimate of the cooling structure, in terms of its amplitude and position. Sensitivity analysis indicated that the typhoon-induced ocean cooling is a nonlinear process involving interactions of multiple atmospheric and oceanic variables. Therefore, with an appropriate selection of input variables and neuron sizes, the ML-based algorithm appears to be more efficient in prognosing the typhoon-induced ocean cooling and in predicting typhoon intensity than those algorithms based on linear regression methods.

Chlorophyll-a specific volume scattering function of phytoplankton.

PubMed

Tan, Hiroyuki; Oishi, Tomohiko; Tanaka, Akihiko; Doerffer, Roland; Tan, Yasuhiro

2017-06-12

Chlorophyll-a specific light volume scattering functions (VSFs) by cultured phytoplankton in visible spectrum range is presented. Chlorophyll-a specific VSFs were determined based on the linear least squares method using a measured VSFs with different chlorophyll-a concentrations. We found obvious variability of it in terms of spectral and angular shapes of VSF between cultures. It was also presented that chlorophyll-a specific scattering significantly affected on spectral variation of the remote sensing reflectance, depending on spectral shape of b. This result is useful for developing an advance algorithm of ocean color remote sensing and for deep understanding of light in the sea.

Marine optical characterizations

NASA Technical Reports Server (NTRS)

Clark, Dennis K.; Ge, Yuntao; Hovey, Phil; King, ED; Stengel, Eric; Yuen, Marilyn; Koval, Larisa

1995-01-01

During the past three months, the MOCE Team conducted two field experiments in Mill Creek,Chesapeake Bay, from July 24 to August 4, and at the MOBY operations site at Snug Harbor, Honolulu, Hawaii, from August 15-30, prepared two technical memoranda, and continued MOCE-2 and MOCE-3 data reduction. The primary purposes of the experiments were to test the SeaWiFS 'remote sensing reflectance' protocol, obtain turbid water data for ocean color satellite algorithm development, perform calibration for both Near Infrared (NIR) and Visible Rainbow Spectrometer system, continue assembling the operational Marine Optical Buoy, and to test the MOBY cellular phone communications link at the Lanai mooring site.

A deblocking algorithm based on color psychology for display quality enhancement

NASA Astrophysics Data System (ADS)

Yeh, Chia-Hung; Tseng, Wen-Yu; Huang, Kai-Lin

2012-12-01

This article proposes a post-processing deblocking filter to reduce blocking effects. The proposed algorithm detects blocking effects by fusing the results of Sobel edge detector and wavelet-based edge detector. The filtering stage provides four filter modes to eliminate blocking effects at different color regions according to human color vision and color psychology analysis. Experimental results show that the proposed algorithm has better subjective and objective qualities for H.264/AVC reconstructed videos when compared to several existing methods.

Performance metrics for the assessment of satellite data products: an ocean color case study

EPA Science Inventory

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coeffic...

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern

PubMed Central

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-01-01

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method. PMID:28657602

Colorization-Based RGB-White Color Interpolation using Color Filter Array with Randomly Sampled Pattern.

PubMed

Oh, Paul; Lee, Sukho; Kang, Moon Gi

2017-06-28

Recently, several RGB-White (RGBW) color filter arrays (CFAs) have been proposed, which have extra white (W) pixels in the filter array that are highly sensitive. Due to the high sensitivity, the W pixels have better SNR (Signal to Noise Ratio) characteristics than other color pixels in the filter array, especially, in low light conditions. However, most of the RGBW CFAs are designed so that the acquired RGBW pattern image can be converted into the conventional Bayer pattern image, which is then again converted into the final color image by using conventional demosaicing methods, i.e., color interpolation techniques. In this paper, we propose a new RGBW color filter array based on a totally different color interpolation technique, the colorization algorithm. The colorization algorithm was initially proposed for colorizing a gray image into a color image using a small number of color seeds. Here, we adopt this algorithm as a color interpolation technique, so that the RGBW color filter array can be designed with a very large number of W pixels to make the most of the highly sensitive characteristics of the W channel. The resulting RGBW color filter array has a pattern with a large proportion of W pixels, while the small-numbered RGB pixels are randomly distributed over the array. The colorization algorithm makes it possible to reconstruct the colors from such a small number of RGB values. Due to the large proportion of W pixels, the reconstructed color image has a high SNR value, especially higher than those of conventional CFAs in low light condition. Experimental results show that many important information which are not perceived in color images reconstructed with conventional CFAs are perceived in the images reconstructed with the proposed method.

Adaptive Wiener filter super-resolution of color filter array images.

PubMed

Karch, Barry K; Hardie, Russell C

2013-08-12

Digital color cameras using a single detector array with a Bayer color filter array (CFA) require interpolation or demosaicing to estimate missing color information and provide full-color images. However, demosaicing does not specifically address fundamental undersampling and aliasing inherent in typical camera designs. Fast non-uniform interpolation based super-resolution (SR) is an attractive approach to reduce or eliminate aliasing and its relatively low computational load is amenable to real-time applications. The adaptive Wiener filter (AWF) SR algorithm was initially developed for grayscale imaging and has not previously been applied to color SR demosaicing. Here, we develop a novel fast SR method for CFA cameras that is based on the AWF SR algorithm and uses global channel-to-channel statistical models. We apply this new method as a stand-alone algorithm and also as an initialization image for a variational SR algorithm. This paper presents the theoretical development of the color AWF SR approach and applies it in performance comparisons to other SR techniques for both simulated and real data.

NIMBUS-7 CZCS. Coastal Zone Color Scanner Imagery for Selected Coastal Regions. North America - Europe. South America - Africa - Antarctica. Level 2 Photographic Product

NASA Technical Reports Server (NTRS)

1984-01-01

The Nimbus-7 Coastal Zone Color Scanner (CZCS) is the first spacecraft instrument devoted to the measurement of ocean color. Although instruments on other satellites have sensed ocean color, their spectral bands, spatial resolution, and dynamic range were optimized for geographical or meteorological use. In the CZCS, every parameter is optimized for use over water to the exclusion of any other type of sensing. The signal-to-noise ratios in the spectral channels sensing reflected solar radiance are higher than those required in the past. These ratios need to be high because the ocean is such a poor reflecting surface that the majority of the signal seen by the reflected energy channels at spacecraft altitudes is backscattered solar radiation from the atmosphere rather than reflected solar energy from the ocean. The CZCS is a conventional multichannel scanning radiometer utilizing a rotating plane mirror at a 45 deg angle to the optic axis of a Cassegrain telescope. The mirror scans 360 deg; however, only 80 deg of data centered on the spacecraft nadir is collected for ocean color measurements. Spatial resolution at spacecraft nadir is 825x825 m with some degradation at the edges of the scan swath. The useful swath width from a spacecraft altitude of 955 km is 1600 km.

Seasonality and flux estimates of dissolved organic carbon in tidal wetlands and estuaries in the U.S. Mid- Atlantic Bight and Gulf of Mexico from ocean color

NASA Astrophysics Data System (ADS)

Cao, F.; Tzortziou, M.; Hu, C.; Najjar, R.

2016-02-01

Tidal wetlands and estuaries are dynamic features of coastal ocean and play critical roles in the global carbon cycle. Exchanges of dissolved organic carbon (DOC) between tidal wetlands and adjacent estuaries have important implications for carbon sequestration in tidal wetlands as well as biogeochemical cycling of wetlands derived material in the coastal zones. Recent studies demonstrated that the absorption coefficients of chromophoric dissolved organic matter at λ= 275 and 295 nm, which can be derived from satellite ocean color observations, can be used to accurately retrieve dissolved organic carbon (DOC) in some coastal waters. Based on a synthesis of existing field observations collected covering wide spatial and temporal variability in the Mid-Atlantic Bight and the Gulf of Mexico, here we developed and validated new empirical models to estimate coastal DOC from remotely sensed bio-optical properties of the surface water. We focused on the interfaces between tidal wetland-estuary and estuary-shelf water domains. The DOC algorithms were applied to SeaWiFs and MODIS observations to generate long-term climatological DOC distributions from 1998 to 2014. Empirical orthogonal function analysis revealed strong seasonality and spatial gradients in the satellite retrieved DOC in the tidal wetlands and estuaries. Combined with field observations and biogeochemical models, satellite retrievals can be used to scale up carbon fluxes from individual marshes and sub-estuaries to the whole estuarine system, and improve understanding of biogeochemical exchanges between terrestrial and aquatic ecosystems.

Petri nets SM-cover-based on heuristic coloring algorithm

NASA Astrophysics Data System (ADS)

Tkacz, Jacek; Doligalski, Michał

2015-09-01

In the paper, coloring heuristic algorithm of interpreted Petri nets is presented. Coloring is used to determine the State Machines (SM) subnets. The present algorithm reduces the Petri net in order to reduce the computational complexity and finds one of its possible State Machines cover. The proposed algorithm uses elements of interpretation of Petri nets. The obtained result may not be the best, but it is sufficient for use in rapid prototyping of logic controllers. Found SM-cover will be also used in the development of algorithms for decomposition, and modular synthesis and implementation of parallel logic controllers. Correctness developed heuristic algorithm was verified using Gentzen formal reasoning system.

Minimized-Laplacian residual interpolation for color image demosaicking

NASA Astrophysics Data System (ADS)

Kiku, Daisuke; Monno, Yusuke; Tanaka, Masayuki; Okutomi, Masatoshi

2014-03-01

A color difference interpolation technique is widely used for color image demosaicking. In this paper, we propose a minimized-laplacian residual interpolation (MLRI) as an alternative to the color difference interpolation, where the residuals are differences between observed and tentatively estimated pixel values. In the MLRI, we estimate the tentative pixel values by minimizing the Laplacian energies of the residuals. This residual image transfor- mation allows us to interpolate more easily than the standard color difference transformation. We incorporate the proposed MLRI into the gradient based threshold free (GBTF) algorithm, which is one of current state-of- the-art demosaicking algorithms. Experimental results demonstrate that our proposed demosaicking algorithm can outperform the state-of-the-art algorithms for the 30 images of the IMAX and the Kodak datasets.

Accounting for the water-leaving radiance in the simultaneous retrieval of atmosphere and ocean properties from collocated polarimeters and lidar measurements: results for the SABOR campaign

NASA Astrophysics Data System (ADS)

Chowdhary, J.; Brian, C.; Stamnes, S.; Hostetler, C. A.; Cetinic, I.; Slade, W. H.; Hu, Y.

2017-12-01

Ocean spectra typically contribute less than 10% to top-of-atmosphere (TOA) radiance observations in the visible (VIS). The remaining 90% of TOA radiance originates from scattering in the atmosphere which needs to be removed (i.e. corrected) but varies substantially with the aerosol present at the time of observation. The traditional approach for atmospheric correction (AC), used for ocean color sensors such as SeaWiFS, MODIS, and VIIRS, estimates aerosol scattering properties from TOA radiance observations in the near-infrared/short-wave infrared (NIR/SWIR) where the ocean becomes dark. The aerosol model is subsequently used to compute the atmospheric scattering contribution to the TOA radiance in the VIS. The final step is to subtract this computed scattering contribution from the real (i.e. observed) TOA radiance. As an alternative to the traditional approach for AC, we retrieve the atmosphere (i.e., aerosol) and ocean (i.e., color) properties simultaneously from measurements in the VIS. To separate the information content for the atmosphere and ocean, we use lidar measurements and multi-angle polarization measurements. Lidar and polarimeter measurements are powerful tools to enhance the ocean product retrievals from conventional ocean color sensors, and are under consideration to accompany future generation ocean color sensors. Here, we present results of simultaneous atmosphere-ocean retrievals using collocated airborne lidar and polarimeter data that were acquired during the Ship-Aircraft Bio-Optical Research (SABOR) campaign. We discuss 2 hydrosol models (which differ in number of free parameters) that were used for these inversions. We then compare our ocean retrievals with measurements obtained from the accompanying cruise ship. Finally, we touch upon a next generation of hydrosol models that accommodates the unique sensitivity of ocean lidar profiles to plankton morphology.

Volumetric display containing multiple two-dimensional color motion pictures

NASA Astrophysics Data System (ADS)

Hirayama, R.; Shiraki, A.; Nakayama, H.; Kakue, T.; Shimobaba, T.; Ito, T.

2014-06-01

We have developed an algorithm which can record multiple two-dimensional (2-D) gradated projection patterns in a single three-dimensional (3-D) object. Each recorded pattern has the individual projected direction and can only be seen from the direction. The proposed algorithm has two important features: the number of recorded patterns is theoretically infinite and no meaningful pattern can be seen outside of the projected directions. In this paper, we expanded the algorithm to record multiple 2-D projection patterns in color. There are two popular ways of color mixing: additive one and subtractive one. Additive color mixing used to mix light is based on RGB colors and subtractive color mixing used to mix inks is based on CMY colors. We made two coloring methods based on the additive mixing and subtractive mixing. We performed numerical simulations of the coloring methods, and confirmed their effectiveness. We also fabricated two types of volumetric display and applied the proposed algorithm to them. One is a cubic displays constructed by light-emitting diodes (LEDs) in 8×8×8 array. Lighting patterns of LEDs are controlled by a microcomputer board. The other one is made of 7×7 array of threads. Each thread is illuminated by a projector connected with PC. As a result of the implementation, we succeeded in recording multiple 2-D color motion pictures in the volumetric displays. Our algorithm can be applied to digital signage, media art and so forth.

A Practical Application of Ocean Color Methodology to an Undergraduate Curriculum

ERIC Educational Resources Information Center

Moisan, Tiffany A.; Swift, Robert N.; Campbell, Brian A.; Yungel, James K.; Linkswiler, Matthew A.; Nolan, Jessica

2008-01-01

Recently there have been newly launched ocean color satellites which target the coastlines at unprecedented scales. Science education curricula can benefit from the provision of small low-cost spectroradiometers and curriculum supplemental materials that can be incorporated in a "hands on" teaching approach to explain and demonstrate remote…

Ocean Color Measurements from Landsat-8 OLI using SeaDAS

NASA Technical Reports Server (NTRS)

Franz, Bryan Alden; Bailey, Sean W.; Kuring, Norman; Werdell, P. Jeremy

2014-01-01

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that carries information on the biogeochemical constituents of the upper ocean euphotic zone. To evaluate the potential of OLI to measure ocean color, processing support was implemented in SeaDAS, which is an open-source software package distributed by NASA for processing, analysis, and display of ocean remote sensing measurements from a variety of satellite-based multi-spectral radiometers. Here we describe the implementation of OLI processing capabilities within SeaDAS, including support for various methods of atmospheric correction to remove the effects of atmospheric scattering and absorption and retrieve the spectral remote-sensing reflectance (Rrs; sr exp 1). The quality of the retrieved Rrs imagery will be assessed, as will the derived water column constituents such as the concentration of the phytoplankton pigment chlorophyll a.

Viral Lysogeny as a Potential Mechanism for Termination of a Red Tide Event

NASA Astrophysics Data System (ADS)

Martinez, S. B.; Kudela, R. M.; Broughton, J.

2014-12-01

Red tides are high-biomass blooms in the coastal ocean typically caused by dinoflagellates. While some red tides are harmful (via toxin production, high biomass, and oxygen depletion during decay), they also provide an important source of energy and carbon for other trophic levels. Red tides are often ephemeral, so while it is easy to identify one, what causes these events to terminate can vary. It has been hypothesized that viral lysis and parasitic infection may be important vectors of termination for these blooms. This study sought to compare the decay of one such bloom in Monterey Bay, California to in situ and mesocosm studies where bloom termination was due to viral lysis. To achieve this goal we used MODIS ocean color Level 2 data with spatial resolution of 1km; we identified and averaged RRS from 9 pixels within the northern "red tide incubator" region of Monterey Bay where a dinoflagellate bloom was identified. We applied the quasi-analytical algorithm (QAA) to derive the backscatter coefficient (bbp(λ)), absorption due to chlorophyll (aChl), and the gelbstoff absorption coefficient (ag). Separate equations were used to find the volume scattering function (β(ψ,λ) where ψ =140°) and the particle size distribution hyperbolic slope (ξ). A MODIS satellite time series of five days (during an eight-day period) confirmed optical changes similar to documented shifts in laboratory-controlled experiments examining viral lysis. As predicted from previous results, the decrease in chlorophyll - essentially the deterioration of the algal bloom - resulted in the anticipated decrease in bbp(λ) and VSF values as well as an increase in ξ. aChl and ag were also compared to the Morel 2009 band algorithm for Colored Dissolved Organic Matter (CDOM) and the OC3 band algorithm for chlorophyll concentration. Results indicate that the QAA retrievals cannot be statistically distinguished (using a paired t-test) from the Morel and OC3 band algorithms. Analyzing more bloom events would refine this method's results and would provide the potential to determine how a bloom is terminated - e.g. by viral lysis, parasitic infection, or nutrient depletion. This could in turn lead to a better understanding of bloom termination generally, perhaps leading to improved mitigation efforts for red tides and harmful algal blooms.

Incidence of plastic debris in Sooty Tern nests: A preliminary study on Trindade Island, a remote area of Brazil.

PubMed

de Souza Petersen, Elisa; Krüger, Lucas; Dezevieski, Alexandre; Petry, MariaVirginia; Montone, Rosalinda Carmela

2016-04-15

Plastic is abundant in the oceans, reaching pelagic zones away from continents. Here we present the first recordings of plastic used as nest material in Sooty Tern nests, on a remote oceanic island. We describe our findings in terms of quantity, size and color of plastic debris. A total of 78 plastics were noted in 54 nests. Four color categories were found: Blue, White, Green and Red. Blue fragments were the most frequent color, present three times as much as white debris. This pattern was present despite blue fragments being smaller and lighter. The plastic debris of lowest frequency were the larger and heavier pieces (red). To our knowledge this is the first record of plastic in Sooty Tern nests. Trindade Island is on an oceanic zone expected to accumulate garbage due to the dynamic ocean currents. Such findings call for a closer inspection of pollution in the Atlantic Ocean. Copyright © 2016 Elsevier Ltd. All rights reserved.

A novel blinding digital watermark algorithm based on lab color space

NASA Astrophysics Data System (ADS)

Dong, Bing-feng; Qiu, Yun-jie; Lu, Hong-tao

2010-02-01

It is necessary for blinding digital image watermark algorithm to extract watermark information without any extra information except the watermarked image itself. But most of the current blinding watermark algorithms have the same disadvantage: besides the watermarked image, they also need the size and other information about the original image when extracting the watermark. This paper presents an innovative blinding color image watermark algorithm based on Lab color space, which does not have the disadvantages mentioned above. This algorithm first marks the watermark region size and position through embedding some regular blocks called anchor points in image spatial domain, and then embeds the watermark into the image. In doing so, the watermark information can be easily extracted after doing cropping and scale change to the image. Experimental results show that the algorithm is particularly robust against the color adjusting and geometry transformation. This algorithm has already been used in a copyright protecting project and works very well.

A design study for an advanced ocean color scanner system. [spaceborne equipment

NASA Technical Reports Server (NTRS)

Kim, H. H.; Fraser, R. S.; Thompson, L. L.; Bahethi, O.

1980-01-01

Along with a colorimetric data analysis scheme, the instrumental parameters which need to be optimized in future spaceborne ocean color scanner systems are outlined. With regard to assessing atmospheric effects from ocean colorimetry, attention is given to computing size parameters of the aerosols in the atmosphere, total optical depth measurement, and the aerosol optical thickness. It is suggested that sensors based on the use of linear array technology will meet hardware objectives.

The tongue of the ocean as a remote sensing ocean color calibration range

NASA Technical Reports Server (NTRS)

Strees, L. V.

1972-01-01

In general, terrestrial scenes remain stable in content from both temporal and spacial considerations. Ocean scenes, on the other hand, are constantly changing in content and position. The solar energy that enters the ocean waters undergoes a process of scattering and selective spectral absorption. Ocean scenes are thus characterized as low level radiance with the major portion of the energy in the blue region of the spectrum. Terrestrial scenes are typically of high level radiance with their spectral energies concentrated in the green-red regions of the visible spectrum. It appears that for the evaluation and calibration of ocean color remote sensing instrumentation, an ocean area whose optical ocean and atmospheric properties are known and remain seasonably stable over extended time periods is needed. The Tongue of the Ocean, a major submarine channel in the Bahama Banks, is one ocean are for which a large data base of oceanographic information and a limited amount of ocean optical data are available.

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

NASA Astrophysics Data System (ADS)

Wang, Yunhua; DeBrunner, Linda; DeBrunner, Victor; Zhou, Dayong

2008-12-01

Tsatsanis and Xu have applied the constrained minimum output variance (CMOV) principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE) equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

Response of ocean ecosystems to climate warming

NASA Astrophysics Data System (ADS)

Sarmiento, J. L.; Slater, R.; Barber, R.; Bopp, L.; Doney, S. C.; Hirst, A. C.; Kleypas, J.; Matear, R.; Mikolajewicz, U.; Monfray, P.; Soldatov, V.; Spall, S. A.; Stouffer, R.

2004-09-01

We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.

Signature extraction of ocean pollutants by eigenvector transformation of remote spectra

NASA Technical Reports Server (NTRS)

Grew, G. W.

1978-01-01

Spectral signatures of suspended matter in the ocean are being extracted through characteristic vector analysis of remote ocean color data collected with MOCS (Multichannel Ocean Color Sensor). Spectral signatures appear to be obtainable through analyses of 'linear' clusters that appear on scatter diagrams associated with eigenvectors. Signatures associated with acid waste, sewage sludge, oil, and algae are presented. The application of vector analysis to two acid waste dumps overflown two years apart is examined in some detail. The relationships between eigenvectors and spectral signatures for these examples are analyzed. These cases demonstrate the value of characteristic vector analysis in remotely identifying pollutants in the ocean and in determining the consistency of their spectral signatures.

Ocean Observation Instrument

NASA Technical Reports Server (NTRS)

1993-01-01

The Airborne Ocean Color Imager (AOCI) was developed by Daedalus Enterprises, Inc. for Ames Research Center under a Small Business Innovation Research (SBIR) contract as a simulator for an advanced oceanographic satellite instrument. The instrument measures water temperature and detects water color in nine wavelengths. Water color indicates chlorophyll content or phytoplankton. After EOCAP assistance and technical improvements, the AOCI was successfully commercialized by Daedalus Enterprises, Inc. One version provides commercial fishing fleets with information about fish locations, and the other is used for oceanographic research.

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

NASA Technical Reports Server (NTRS)

Li, Yonghong; Angal, Amit; Wu, Aisheng; Geng, Xu; Link, Daniel; Xiong, Xiaoxiong

2016-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Specificity of Atmosphere Correction of Satellite Ocean Color Data in Far-Eastern Region

NASA Astrophysics Data System (ADS)

Trusenkova, O.; Kachur, V.; Aleksanin, A. I.

2016-02-01

It was carried out an error analysis of satellite reflectance coefficients (Rrs) of MODIS/AQUA colour data for two atmospheric correction algorithms (NIR, MUMM) in the Far-Eastern region. Some sets of unique data of in situ and satellite measurements have been analysed. A set has some measurements with ASD spectroradiometer for each satellite pass. The measurement allocations were selected so the Chlorophyll-a concentration has high variability. Analysis of arbitrary set demonstrated that the main error component is systematic error, and it has simple relations on Rrs values. The reasons of such error behavior are considered. The most probable explanation of the large errors of oceanic color parameters in the Far-Eastern region is the ability of high concentrations of continental aerosol. A comparison of satellite and in situ measurements at AERONET stations of USA and South Korea regions has been made. It was shown that for NIR-correction of the atmosphere influence the error values in these two regions have differences up to 10 times for almost the same water turbidity and relatively good accuracy of computation of aerosol optical thickness. The study was supported by grant Russian Scientific Foundation No. 14-50-00034, by grant of Russian Foundation of Basic Research No.15-35-21032-mol-a-ved, and by Program of Basic Research "Far East" of Far Eastern Branch of Russian Academy of Sciences.

Illuminant color estimation based on pigmentation separation from human skin color

NASA Astrophysics Data System (ADS)

Tanaka, Satomi; Kakinuma, Akihiro; Kamijo, Naohiro; Takahashi, Hiroshi; Tsumura, Norimichi

2015-03-01

Human has the visual system called "color constancy" that maintains the perceptive colors of same object across various light sources. The effective method of color constancy algorithm was proposed to use the human facial color in a digital color image, however, this method has wrong estimation results by the difference of individual facial colors. In this paper, we present the novel color constancy algorithm based on skin color analysis. The skin color analysis is the method to separate the skin color into the components of melanin, hemoglobin and shading. We use the stationary property of Japanese facial color, and this property is calculated from the components of melanin and hemoglobin. As a result, we achieve to propose the method to use subject's facial color in image and not depend on the individual difference among Japanese facial color.

Demosaicking algorithm for the Kodak-RGBW color filter array

NASA Astrophysics Data System (ADS)

Rafinazari, M.; Dubois, E.

2015-01-01

Digital cameras capture images through different Color Filter Arrays and then reconstruct the full color image. Each CFA pixel only captures one primary color component; the other primary components will be estimated using information from neighboring pixels. During the demosaicking algorithm, the two unknown color components will be estimated at each pixel location. Most of the demosaicking algorithms use the RGB Bayer CFA pattern with Red, Green and Blue filters. The least-Squares Luma-Chroma demultiplexing method is a state of the art demosaicking method for the Bayer CFA. In this paper we develop a new demosaicking algorithm using the Kodak-RGBW CFA. This particular CFA reduces noise and improves the quality of the reconstructed images by adding white pixels. We have applied non-adaptive and adaptive demosaicking method using the Kodak-RGBW CFA on the standard Kodak image dataset and the results have been compared with previous work.

Pet fur color and texture classification

NASA Astrophysics Data System (ADS)

Yen, Jonathan; Mukherjee, Debarghar; Lim, SukHwan; Tretter, Daniel

2007-01-01

Object segmentation is important in image analysis for imaging tasks such as image rendering and image retrieval. Pet owners have been known to be quite vocal about how important it is to render their pets perfectly. We present here an algorithm for pet (mammal) fur color classification and an algorithm for pet (animal) fur texture classification. Per fur color classification can be applied as a necessary condition for identifying the regions in an image that may contain pets much like the skin tone classification for human flesh detection. As a result of the evolution, fur coloration of all mammals is caused by a natural organic pigment called Melanin and Melanin has only very limited color ranges. We have conducted a statistical analysis and concluded that mammal fur colors can be only in levels of gray or in two colors after the proper color quantization. This pet fur color classification algorithm has been applied for peteye detection. We also present here an algorithm for animal fur texture classification using the recently developed multi-resolution directional sub-band Contourlet transform. The experimental results are very promising as these transforms can identify regions of an image that may contain fur of mammals, scale of reptiles and feather of birds, etc. Combining the color and texture classification, one can have a set of strong classifiers for identifying possible animals in an image.

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

PubMed Central

2015-01-01

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377

SeaHawk: an advanced CubeSat mission for sustained ocean colour monitoring

NASA Astrophysics Data System (ADS)

Morrison, John M.; Jeffrey, Hazel; Gorter, Hessel; Anderson, Pamela; Clark, Craig; Holmes, Alan; Feldman, Gene C.; Patt, Frederick S.

2016-10-01

Sustained ocean color monitoring is vital to understanding the marine ecosystem. It has been identified as an Essential Climate Variable (ECV) and is a vital parameter in understanding long-term climate change. Furthermore, observations can be beneficial in observing oil spills, harmful algal blooms and the health of fisheries. Space-based remote sensing, through MERIS, SeaWiFS and MODIS instruments, have provided a means of observing the vast area covered by the ocean which would otherwise be impossible using ships alone. However, the large pixel size makes measurements of lakes, rivers, estuaries and coastal zones difficult. Furthermore, retirement of a number of widely used and relied upon ocean observation instruments, particularly MERIS and SeaWiFS, leaves a significant gap in ocean color observation opportunities This paper presents an overview of the SeaHawk mission, a collaborative effort between Clyde Space Ltd., the University of North Carolina Wilmington, Cloudland Instruments, and Goddard Spaceflight Center, funded by the Gordon and Betty Moore Foundation. The goal of the project is to enhance the ability to observe ocean color in high temporal and spatial resolution through use of a low-cost, next-generation ocean color sensor flown aboard a CubeSat. The final product will be 530 times smaller (0.0034 vs 1.81m3) and 115 time less massive (3.4 vs 390.0kg) but with a ground resolution 10 times better whilst maintaining a signal/noise ratio 50% that of SeaWiFs. This paper will describe the objectives of the mission, outline the payload specification and the spacecraft platform to support it.

Do Doppler color flow algorithms for mapping disturbed flow make sense?

PubMed

Gardin, J M; Lobodzinski, S M

1990-01-01

It has been suggested that a major advantage of Doppler color flow mapping is its ability to visualize areas of disturbed ("turbulent") flow, for example, in valvular stenosis or regurgitation and in shunts. To investigate how various color flow mapping instruments display disturbed flow information, color image processing was used to evaluate the most common velocity-variance color encoding algorithms of seven commercially available ultrasound machines. In six of seven machines, green was reportedly added by the variance display algorithms to map areas of disturbed flow. The amount of green intensity added to each pixel along the red and blue portions of the velocity reference color bar was calculated for each machine. In this study, velocities displayed on the reference color bar ranged from +/- 46 to +/- 64 cm/sec, depending on the Nyquist limit. Of note, changing the Nyquist limits depicted on the color reference bars did not change the distribution of the intensities of red, blue, or green within the contour of the reference map, but merely assigned different velocities to the pixels. Most color flow mapping algorithms in our study added increasing intensities of green to increasing positive (red) or negative (blue) velocities along their color reference bars. Most of these machines also added increasing green to red and blue color intensities horizontally across their reference bars as a marker of increased variance (spectral broadening). However, at any given velocity, marked variations were noted between different color flow mapping instruments in the amount of green added to their color velocity reference bars.(ABSTRACT TRUNCATED AT 250 WORDS)

Atmospheric correction of ocean color sensors: analysis of the effects of residual instrument polarization sensitivity.

PubMed

Gordon, H R; Du, T; Zhang, T

1997-09-20

We provide an analysis of the influence of instrument polarization sensitivity on the radiance measured by spaceborne ocean color sensors. Simulated examples demonstrate the influence of polarization sensitivity on the retrieval of the water-leaving reflectance rho(w). A simple method for partially correcting for polarization sensitivity--replacing the linear polarization properties of the top-of-atmosphere reflectance with those from a Rayleigh-scattering atmosphere--is provided and its efficacy is evaluated. It is shown that this scheme improves rho(w) retrievals as long as the polarization sensitivity of the instrument does not vary strongly from band to band. Of course, a complete polarization-sensitivity characterization of the ocean color sensor is required to implement the correction.

Polar research from satellites

NASA Technical Reports Server (NTRS)

Thomas, Robert H.

1991-01-01

In the polar regions and climate change section, the topics of ocean/atmosphere heat transfer, trace gases, surface albedo, and response to climate warming are discussed. The satellite instruments section is divided into three parts. Part one is about basic principles and covers, choice of frequencies, algorithms, orbits, and remote sensing techniques. Part two is about passive sensors and covers microwave radiometers, medium-resolution visible and infrared sensors, advanced very high resolution radiometers, optical line scanners, earth radiation budget experiment, coastal zone color scanner, high-resolution imagers, and atmospheric sounding. Part three is about active sensors and covers synthetic aperture radar, radar altimeters, scatterometers, and lidar. There is also a next decade section that is followed by a summary and recommendations section.

Ocean Opportunities. A Guide to What the Oceans Have to Offer.

ERIC Educational Resources Information Center

Burtis, William S.

High school students interested in ocean-related careers will find their imagination piqued by "Ocean Opportunities." As the ocean's resources are recognized more and more as extremely important economically, yet very fragile, study of those resources is burgeoning. This multi-color booklet describes the exciting opportunities which ocean research…

Radiometric Quality of the MODIS Bands at 667 and 678nm

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2010-01-01

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top- of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Radiometric Quality of the MODIS Bands at 667 and 678nm

NASA Technical Reports Server (NTRS)

Meister, Gerhard; Franz, Bryan A.

2011-01-01

The MODIS instruments on Terra and Aqua were designed to allow the measurement of chlorophyll fluorescence effects over ocean. The retrieval algorithm is based on the difference between the water-leaving radiances at 667nm and 678nm. The water-leaving radiances at these wavelengths are usually very low relative to the top-of-atmosphere radiances. The high radiometric accuracy needed to retrieve the small fluorescence signal lead to a dual gain design for the 667 and 678nm bands. This paper discusses the benefits obtained from this design choice and provides justification for the use of only one set of gains for global processing of ocean color products. Noise characteristics of the two bands and their related products are compared to other products of bands from 412nm to 2130nm. The impact of polarization on the two bands is discussed. In addition, the impact of stray light on the two bands is compared to other MODIS bands.

Apparent optical properties of the Canadian Beaufort Sea - Part 1: Observational overview and water column relationships

NASA Astrophysics Data System (ADS)

Antoine, D.; Hooker, S. B.; Bélanger, S.; Matsuoka, A.; Babin, M.

2013-07-01

A data set of radiometric measurements collected in the Beaufort Sea (Canadian Arctic) in August 2009 (Malina project) is analyzed in order to describe apparent optical properties (AOPs) in this sea, which has been subject to dramatic environmental changes for several decades. The two properties derived from the measurements are the spectral diffuse attenuation coefficient for downward irradiance, Kd, and the spectral remote sensing reflectance, Rrs. The former controls light propagation in the upper water column. The latter determines how light is backscattered out of the water and becomes eventually observable from a satellite ocean color sensor. The data set includes offshore clear waters of the Beaufort Basin as well as highly turbid waters of the Mackenzie River plumes. In the clear waters, we show Kd values that are much larger in the ultraviolet and blue parts of the spectrum than what could be anticipated considering the chlorophyll concentration. A larger contribution of absorption by colored dissolved organic matter (CDOM) is responsible for these high Kd values, as compared to other oligotrophic areas. In turbid waters, attenuation reaches extremely high values, driven by high loads of particulate materials and also by a large CDOM content. In these two extreme types of waters, current satellite chlorophyll algorithms fail. This questions the role of ocean color remote sensing in the Arctic when Rrs from only the blue and green bands are used. Therefore, other parts of the spectrum (e.g., the red) should be explored if one aims at quantifying interannual changes in chlorophyll in the Arctic from space. The very peculiar AOPs in the Beaufort Sea also advocate for developing specific light propagation models when attempting to predict light availability for photosynthesis at depth.

Hue-preserving and saturation-improved color histogram equalization algorithm.

PubMed

Song, Ki Sun; Kang, Hee; Kang, Moon Gi

2016-06-01

In this paper, an algorithm is proposed to improve contrast and saturation without color degradation. The local histogram equalization (HE) method offers better performance than the global HE method, whereas the local HE method sometimes produces undesirable results due to the block-based processing. The proposed contrast-enhancement (CE) algorithm reflects the characteristics of the global HE method in the local HE method to avoid the artifacts, while global and local contrasts are enhanced. There are two ways to apply the proposed CE algorithm to color images. One is luminance processing methods, and the other one is each channel processing methods. However, these ways incur excessive or reduced saturation and color degradation problems. The proposed algorithm solves these problems by using channel adaptive equalization and similarity of ratios between the channels. Experimental results show that the proposed algorithm enhances contrast and saturation while preserving the hue and producing better performance than existing methods in terms of objective evaluation metrics.

Application synergies between the NASA Pre- Aerosol Cloud and ocean Ecosystem (PACE) and Hyperspectral Infrared Imager (HyspIRI) missions

NASA Astrophysics Data System (ADS)

Lee, C. M.; Omar, A. H.; Hook, S. J.; Tzortziou, M.; Luvall, J. C.; Turner, W. W.

2016-02-01

Observations from the Pre-Aerosol Cloud and ocean Ecosystem (PACE) and Hyperspectral InfraRed Imager (HyspIRI) satellite missions are highly complementary and have the potential to significantly advance understanding of various science and applications challenges in the ocean sciences and water quality communities. Scheduled for launch in the 2022 timeframe, PACE is designed to make climate-quality global measurements essential for understanding ocean biology, biogeochemistry and ecology, and determining the role of the ocean in global biogeochemical cycling and ocean ecology, and how it affects and is affected by climate change. PACE will provide high signal-to-noise, hyperspectral observations over an extended spectral range (UV to SWIR) and will have global coverage every 1-2 days, at approximately 1 km spatial resolution; furthermore, PACE is currently designed to include a polarimeter, which will vastly improve atmospheric correction algorithms over water bodies. The PACE mission will enable advances in applications across a range of areas, including oceans, climate, water resources, ecological forecasting, disasters, human health and air quality. HyspIRI, with contiguous measurements in VSWIR, and multispectral measurements in TIR, will be able to provide detailed spectral observations and higher spatial resolution (30 to 60-m) over aquatic systems, but at a temporal resolution that is approximately 5-16 days. HyspIRI would enable improved, detailed studies of aquatic ecosystems, including benthic communities, algal blooms, coral reefs, and wetland species distribution as well as studies of water quality indicators or pollutants such as oil spills, suspended sediment, and colored dissolved organic matter. Together, PACE and HyspIRI will be able to address numerous applications and science priorities, including improving and extending climate data records, and studies of inland, coastal and ocean environments.

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

NASA Technical Reports Server (NTRS)

Mannino, A.; Hooker, S. B.; Hyde, K.; Novak, M. G.; Pan, X.; Friedrichs, M.; Cahill, B.; Wilkin, J.

2011-01-01

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Instrumentation for optical ocean remote sensing

NASA Technical Reports Server (NTRS)

Esaias, W. E.

1991-01-01

Instruments used in ocean color remote sensing algorithm development, validation, and data acquisition which have the potential for further commercial development and marketing are discussed. The Ocean Data Acquisition System (ODAS) is an aircraft-borne radiometer system suitable for light aircraft, which has applications for rapid measurement of chlorophyll pigment concentrations along the flight line. The instrument package includes a three channel radiometer system for upwelling radiance, an infrared temperature sensor, a three-channel downwelling irradiance sensor, and Loran-C navigation. Data are stored on a PC and processed to transects or interpolated 'images' on the ground. The instrument has been in operational use for two and one half years. The accuracy of pigment concentrations from the instrument is quite good, even in complex Chesapeake Bay waters. To help meet the requirement for validation of future satellite missions, a prototype air-deployable drifting buoy for measurement of near-surface upwelled radiance in multiple channnels is undergoing test deployment. The optical drifter burst samples radiance, stores and processes the data, and uses the Argos system as a data link. Studies are underway to explore the limits to useful lifetime with respect to power and fouling.

Towards PACE Atmospheric Correction, Aerosol and Cloud Products: Making Use of Expanded Spectral, Angular and Polarimetric Information.

NASA Astrophysics Data System (ADS)

Remer, L. A.; Boss, E.; Ahmad, Z.; Cairns, B.; Chowdhary, J.; Coddington, O.; Davis, A. B.; Dierssen, H. M.; Diner, D. J.; Franz, B. A.; Frouin, R.; Gao, B. C.; Garay, M. J.; Heidinger, A.; Ibrahim, A.; Kalashnikova, O. V.; Knobelspiesse, K. D.; Levy, R. C.; Omar, A. H.; Meyer, K.; Platnick, S. E.; Seidel, F. C.; van Diedenhoven, B.; Werdell, J.; Xu, F.; Zhai, P.; Zhang, Z.

2017-12-01

NASA's Science Team for the Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission is concluding three years of study exploring the science potential of expanded spectral, angular and polarization capability for space-based retrievals of water leaving radiance, aerosols and clouds. The work anticipates future development of retrievals to be applied to the PACE Ocean Color Instrument (OCI) and/or possibly a PACE Multi-Angle Polarimeter (MAP). In this presentation we will report on the Science Team's accomplishments associated with the atmosphere (significant efforts are also directed by the ST towards the ocean). Included in the presentation will be sensitivity studies that explore new OCI capabilities for aerosol and cloud layer height, aerosol absorption characterization, cloud property retrievals, and how we intend to move from heritage atmospheric correction algorithms to make use of and adjust to OCI's hyperspectral and UV wavelengths. We will then address how capabilities will improve with the PACE MAP, how these capabilities from both OCI and MAP correspond to specific societal benefits from the PACE mission, and what is still needed to close the gaps in our understanding before the PACE mission can realize its full potential.

Bringing the Coastal Zone into Finer Focus

NASA Astrophysics Data System (ADS)

Guild, L. S.; Hooker, S. B.; Kudela, R. M.; Morrow, J. H.; Torres-Perez, J. L.; Palacios, S. L.; Negrey, K.; Dungan, J. L.

2015-12-01

Measurements over extents from submeter to 10s of meters are critical science requirements for the design and integration of remote sensing instruments for coastal zone research. Various coastal ocean phenomena operate at different scales (e.g. meters to kilometers). For example, river plumes and algal blooms have typical extents of 10s of meters and therefore can be resolved with satellite data, however, shallow benthic ecosystem (e.g., coral, seagrass, and kelp) biodiversity and change are best studied at resolutions of submeter to meter, below the pixel size of typical satellite products. The delineation of natural phenomena do not fit nicely into gridded pixels and the coastal zone is complicated by mixed pixels at the land-sea interface with a range of bio-optical signals from terrestrial and water components. In many standard satellite products, these coastal mixed pixels are masked out because they confound algorithms for the ocean color parameter suite. In order to obtain data at the land/sea interface, finer spatial resolution satellite data can be achieved yet spectral resolution is sacrificed. This remote sensing resolution challenge thwarts the advancement of research in the coastal zone. Further, remote sensing of benthic ecosystems and shallow sub-surface phenomena are challenged by the requirements to sense through the sea surface and through a water column with varying light conditions from the open ocean to the water's edge. For coastal waters, >80% of the remote sensing signal is scattered/absorbed due to the atmospheric constituents, sun glint from the sea surface, and water column components. In addition to in-water measurements from various platforms (e.g., ship, glider, mooring, and divers), low altitude aircraft outfitted with high quality bio-optical radiometer sensors and targeted channels matched with in-water sensors and higher altitude platform sensors for ocean color products, bridge the sea-truth measurements to the pixels acquired from satellite and high altitude platforms. We highlight a novel NASA airborne calibration, validation, and research capability for addressing the coastal remote sensing resolution challenge.

Surface currents in the Bohai Sea derived from the Korean Geostationary Ocean Color Imager (GOCI)

NASA Astrophysics Data System (ADS)

Jiang, L.; Wang, M.

2016-02-01

The first geostationary ocean color satellite sensor, the Geostationary Ocean Color Imager (GOCI) onboard the Korean Communication, Ocean, and Meteorological Satellite can monitor and measure ocean phenomena over an area of 2500 × 2500 km2 around the western Pacific region centered at 36°N and 130°E. Hourly measurements during the day around 9:00 to 16:00 local time are a unique capability of GOCI to monitor ocean features of higher temporal variability. In this presentation, we show some recent results of GOCI-derived ocean surface currents in the Bohai Sea using the Maximum Cross-Correlation (MCC) feature tracking method and compare the results with altimetry-inversed tidal current observations produced from Oregon State University (OSU) Tidal Inversion Software (OTIS). The performance of the GOCI-based MCC method is assessed and the discrepancies between the GOCI- and OTIS-derived currents are evaluated. A series of sensitivity studies are conducted with images from various satellite products and of various time differences, MCC adjustable parameters, and influence from other forcings such as wind, to find the best setups for optimal MCC performance. Our results demonstrate that GOCI can effectively provide real-time monitoring of not only water optical, biological, and biogeochemical variability, but also the physical dynamics in the region.

VIIRS Product Evaluation at the Ocean PEATE

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Feldman, Gene C.

2010-01-01

The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) mission will support the continuation of climate records generated from NASA missions. The NASA Science Data Segment (SDS) relies upon discipline-specific centers of expertise to evaluate the NPP data products for suitability as climate data records, The Ocean Product Evaluation and Analysis Tool Element (PEATE) will build upon Well established NASA capabilities within the Ocean Color program in order to evaluate the NPP Visible and Infrared Imager/Radiometer Suite (VIIRS) Ocean Color and Chlorophyll data products. The specific evaluation methods will support not only the evaluation of product quality but also the sources of differences with existing data records.

Remote sensing of atmospheric aerosol and ocean color for the COMS/GOCI

NASA Astrophysics Data System (ADS)

Lee, Kwon-Ho; Kim, Young J.; Kim, Gwan C.; Wong, Man S.; Ahn, Yu H.

2010-10-01

The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS) requires accurate atmospheric correction for the purpose of qualified ocean remote sensing. Since its eight bands are affected by atmospheric constituents such as gases, molecules and atmospheric aerosols, understanding of aerosolradiation interactions is needed. Aerosol optical properties based on sun-photometer measurements are used to analysis aerosol optical thickness (AOT) under various aerosol type and loadings. It is found that the choice of aerosol type makes little different in AOT retrieval for AOT<0.2. These results will be useful for aerosol retrieval of COMS/GOCI data processing.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

NASA Oceanic Processes Program, fiscal year 1983

NASA Technical Reports Server (NTRS)

Nelson, R. M. (Editor); Pieri, D. C. (Editor)

1984-01-01

Accomplishments, activities, and plans are highlighted for studies of ocean circulation, air sea interaction, ocean productivity, and sea ice. Flight projects discussed include TOPEX, the ocean color imager, the advanced RF tracking system, the NASA scatterometer, and the pilot ocean data system. Over 200 papers generated by the program are listed.

Local and regional scale exchanges of dissolved organic carbon (DOC) between tidal wetlands and their adjacent coastal waters

NASA Astrophysics Data System (ADS)

Osburn, C. L.; Joshi, I.; Lebrasse, M. C.; Oviedo-Vargas, D.; Bianchi, T. S.; Bohnenstiehl, D. R.; D'Sa, E. J.; He, R.; Ko, D.; Arellano, A.; Ward, N. D.

2017-12-01

The contribution of blue carbon from tidal wetlands to the coastal ocean in the form of dissolved organic carbon (DOC) represents a terrestrial-aquatic linkage of increasing importance. DOC flux results will be presented from local (tidal creek) and regional (bays) scale studies in which various combinations of field observations, ocean-color satellite observations, and the outputs of high-resolution hydrodynamic models were used to estimate DOC export. The first project was located in Bald Head Creek, a tributary to the Cape Fear River estuary in eastern North Carolina (NC). DOC fluxes were computed using a bathymetric data collected via unmanned surface vehicle (USV) and a numerical hydrodynamic model (SCHISM) based on the relationships between colored dissolved organic matter (CDOM) absorption, DOC concentration, and salinity taken from field observations. Model predictions estimated an annual net export of DOC at 54 g C m-2 yr-1 from the tidal creek to the adjacent estuary. Carbon stable isotope (δ13C) values were used to estimate the contribution of wetland carbon to this export. In the second project, DOC fluxes from the Apalachicola Bay, FL, Barataria Bay, LA, were based on the development of algorithms between DOC and CDOM absorption derived from the VIIRS ocean color sensor. The Navy Coastal Ocean Model (NCOM) was used to compute salt flux estimates from each bay to the Louisiana-Texas shelf. The relationship between salinity and CDOM was used to estimate net annual DOC exports of 8.35 x 106 g C m-2 y-1 (Apalachicola Bay) and 7.14 x 106 g C m-2 yr-1 (Barataria Bay). These values approximate 13% and 9% of the annual loads of DOC from the Mississippi River to the Gulf of Mexico, respectively. CDOM and lignin were used in a mixing model to estimate wetland-derived DOC were 2% for Apalachicola Bay and 13% for Barataria Bay, the latter having one of the highest rates of relative sea level rise in North America. Results from our project demonstrated the utility of CDOM, amenable to high resolution observations from multiple platforms, as a basis for constraining the heterogeneity of DOC exports from tidal wetlands to estuaries and coastal waters using numerical models at local and regional scales.

Characterization of Particle Backscattering of Global Highly Turbid Waters From VIIRS Ocean Color Observations

NASA Astrophysics Data System (ADS)

Shi, Wei; Wang, Menghua

2017-11-01

Normalized water-leaving radiance spectra nLw(λ) at the near-infrared (NIR) from five years of observations (2012-2016) with the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) are used to derive the particle backscattering coefficients bbp(λ) for global highly turbid coastal and inland waters. Based on the fact that the absorption coefficient of sea water aw(λ) is generally much larger than those of the other constituents aiop(λ) at the NIR wavelengths in coastal and inland waters, an NIR-based bbp(λ) algorithm for turbid coastal and inland waters has been developed and used in this study. This algorithm can be safely used for highly turbid waters with nLw(745) and nLw(862) < ˜6 and ˜4 mW cm-2 μm-1 sr-1, respectively. Seasonal and interannual variations of bbp(λ) in China's east coastal region, the Amazon River Estuary, the La Plata River Estuary, the Meghna River Estuary, the Atchafalaya River Estuary, and Lake Taihu are characterized and quantified. The coefficient bbp(λ) can reach over ˜3-4 m-1 in the Amazon River Estuary and China's east coastal region. The Amazon River Estuary is identified as the most turbid region in the global ocean in terms of bbp(λ) magnitude. bbp(λ) spectra in these five highly turbid regions are also seasonal-dependent and regional-dependent. In the highly turbid waters of China's east coastal region and the Amazon River Estuary, bbp(λ) generally increases in wavelength from 410 to 862 nm, while it decreases in the La Plata River Estuary and Atchafalaya River Estuary. This is attributed to the different particle size distributions in these waters. The geophysical implication of the bbp(λ) spectral curvatures for different waters is discussed. To improve global bbp(λ) for both open oceans and coastal turbid waters, a new combined NIR-based and Quasi-Analytical Algorithm (QAA)-based bbp(λ) algorithm is proposed and demonstrated.

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Holben, Brent; Eck, Thomas F.; Li, Zhengqiang; Song, Chul H.

2018-01-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG - τA) is within -0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

A system to measure the data quality of spectral remote-sensing reflectance of aquatic environments

NASA Astrophysics Data System (ADS)

Wei, Jianwei; Lee, Zhongping; Shang, Shaoling

2016-11-01

Spectral remote-sensing reflectance (Rrs, sr-1) is the key for ocean color retrieval of water bio-optical properties. Since Rrs from in situ and satellite systems are subject to errors or artifacts, assessment of the quality of Rrs data is critical. From a large collection of high quality in situ hyperspectral Rrs data sets, we developed a novel quality assurance (QA) system that can be used to objectively evaluate the quality of an individual Rrs spectrum. This QA scheme consists of a unique Rrs spectral reference and a score metric. The reference system includes Rrs spectra of 23 optical water types ranging from purple blue to yellow waters, with an upper and a lower bound defined for each water type. The scoring system is to compare any target Rrs spectrum with the reference and a score between 0 and 1 will be assigned to the target spectrum, with 1 for perfect Rrs spectrum and 0 for unusable Rrs spectrum. The effectiveness of this QA system is evaluated with both synthetic and in situ Rrs spectra and it is found to be robust. Further testing is performed with the NOMAD data set as well as with satellite Rrs over coastal and oceanic waters, where questionable or likely erroneous Rrs spectra are shown to be well identifiable with this QA system. Our results suggest that applications of this QA system to in situ data sets can improve the development and validation of bio-optical algorithms and its application to ocean color satellite data can improve the short-term and long-term products by objectively excluding questionable Rrs data.

Error decomposition and estimation of inherent optical properties.

PubMed

Salama, Mhd Suhyb; Stein, Alfred

2009-09-10

We describe a methodology to quantify and separate the errors of inherent optical properties (IOPs) derived from ocean-color model inversion. Their total error is decomposed into three different sources, namely, model approximations and inversion, sensor noise, and atmospheric correction. Prior information on plausible ranges of observation, sensor noise, and inversion goodness-of-fit are employed to derive the posterior probability distribution of the IOPs. The relative contribution of each error component to the total error budget of the IOPs, all being of stochastic nature, is then quantified. The method is validated with the International Ocean Colour Coordinating Group (IOCCG) data set and the NASA bio-Optical Marine Algorithm Data set (NOMAD). The derived errors are close to the known values with correlation coefficients of 60-90% and 67-90% for IOCCG and NOMAD data sets, respectively. Model-induced errors inherent to the derived IOPs are between 10% and 57% of the total error, whereas atmospheric-induced errors are in general above 43% and up to 90% for both data sets. The proposed method is applied to synthesized and in situ measured populations of IOPs. The mean relative errors of the derived values are between 2% and 20%. A specific error table to the Medium Resolution Imaging Spectrometer (MERIS) sensor is constructed. It serves as a benchmark to evaluate the performance of the atmospheric correction method and to compute atmospheric-induced errors. Our method has a better performance and is more appropriate to estimate actual errors of ocean-color derived products than the previously suggested methods. Moreover, it is generic and can be applied to quantify the error of any derived biogeophysical parameter regardless of the used derivation.

Genetic algorithm for investigating flight MH370 in Indian Ocean using remotely sensed data

NASA Astrophysics Data System (ADS)

Marghany, Maged; Mansor, Shattri; Shariff, Abdul Rashid Bin Mohamed

2016-06-01

This study utilized Genetic algorithm (GA) for automatic detection and simulation trajectory movements of flight MH370 debris. In doing so, the Ocean Surface Topography Mission(OSTM) on the Jason- 2 satellite have been used within 1 and half year covers data to simulate the pattern of Flight MH370 debris movements across the southern Indian Ocean. Further, multi-objectives evolutionary algorithm also used to discriminate uncertainty of flight MH370 imagined and detection. The study shows that the ocean surface current speed is 0.5 m/s. This current patterns have developed a large anticlockwise gyre over a water depth of 8,000 m. The multi-objectives evolutionary algorithm suggested that objects are existed on satellite data are not flight MH370 debris. In addition, multiobjectives evolutionary algorithm suggested that the difficulties to acquire the exact location of flight MH370 due to complicated hydrodynamic movements across the southern Indian Ocean.

Description of algorithms for processing Coastal Zone Color Scanner (CZCS) data

NASA Technical Reports Server (NTRS)

Zion, P. M.

1983-01-01

The algorithms for processing coastal zone color scanner (CZCS) data to geophysical units (pigment concentration) are described. Current public domain information for processing these data is summarized. Calibration, atmospheric correction, and bio-optical algorithms are presented. Three CZCS data processing implementations are compared.

Estimation of saturated pixel values in digital color imaging

PubMed Central

Zhang, Xuemei; Brainard, David H.

2007-01-01

Pixel saturation, where the incident light at a pixel causes one of the color channels of the camera sensor to respond at its maximum value, can produce undesirable artifacts in digital color images. We present a Bayesian algorithm that estimates what the saturated channel's value would have been in the absence of saturation. The algorithm uses the non-saturated responses from the other color channels, together with a multivariate Normal prior that captures the correlation in response across color channels. The appropriate parameters for the prior may be estimated directly from the image data, since most image pixels are not saturated. Given the prior, the responses of the non-saturated channels, and the fact that the true response of the saturated channel is known to be greater than the saturation level, the algorithm returns the optimal expected mean square estimate for the true response. Extensions of the algorithm to the case where more than one channel is saturated are also discussed. Both simulations and examples with real images are presented to show that the algorithm is effective. PMID:15603065

MOBY, A Radiometric Buoy for Performance Monitoring and Vicarious Calibration of Satellite Ocean Color Sensors: Measurement and Data Analysis Protocols. Chapter 2

NASA Technical Reports Server (NTRS)

Clark, Dennis K.; Yarbrough, Mark A.; Feinholz, Mike; Flora, Stephanie; Broenkow, William; Kim, Yong Sung; Johnson, B. Carol; Brown, Steven W.; Yuen, Marilyn; Mueller, James L.

2003-01-01

The Marine Optical Buoy (MOBY) is the centerpiece of the primary ocean measurement site for calibration of satellite ocean color sensors based on independent in situ measurements. Since late 1996, the time series of normalized water-leaving radiances L(sub WN)(lambda) determined from the array of radiometric sensors attached to MOBY are the primary basis for the on-orbit calibrations of the USA Sea-viewing Wide Field-of-view Sensor (SeaWiFS), the Japanese Ocean Color and Temperature Sensor (OCTS), the French Polarization Detection Environmental Radiometer (POLDER), the German Modular Optoelectronic Scanner on the Indian Research Satellite (IRS1-MOS), and the USA Moderate Resolution Imaging Spectrometer (MODIS). The MOBY vicarious calibration L(sub WN)(lambda) reference is an essential element in the international effort to develop a global, multi-year time series of consistently calibrated ocean color products using data from a wide variety of independent satellite sensors. A longstanding goal of the SeaWiFS and MODIS (Ocean) Science Teams is to determine satellite-derived L(sub WN)(labda) with a relative combined standard uncertainty of 5 %. Other satellite ocean color projects and the Sensor Intercomparison for Marine Biology and Interdisciplinary Oceanic Studies (SIMBIOS) project have also adopted this goal, at least implicitly. Because water-leaving radiance contributes at most 10 % of the total radiance measured by a satellite sensor above the atmosphere, a 5 % uncertainty in L(sub WN)(lambda) implies a 0.5 % uncertainty in the above-atmosphere radiance measurements. This level of uncertainty can only be approached using vicarious-calibration approaches as described below. In practice, this means that the satellite radiance responsivity is adjusted to achieve the best agreement, in a least-squares sense, for the L(sub WN)(lambda) results determined using the satellite and the independent optical sensors (e.g. MOBY). The end result of this approach is to implicitly absorb unquantified, but systematic, errors in the atmospheric correction, incident solar flux, and satellite sensor calibration into a single correction factor to produce consistency with the in situ data.

Spectral Variability of Airborne Ocean Color Data Linked to Variations in Lidar Backscattering Profiles

DTIC Science & Technology

2009-01-01

1008.3 r <•-• ADOR/Director NCST E. R. Franchi , 7000 Public Affairs (Unclassified/ Unlimited Only), Code 703Q 4 ’𔃻 iJL:,. iUn’i i’-"Vt... global ocean color sensors (e.g., MODIS). Also, this resolution roughly matches the swath of MicroSAS radiometric measurements in the visible range

Improvements and Extensions for Joint Polar Satellite System Algorithms

NASA Astrophysics Data System (ADS)

Grant, K. D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather satellite system: the Joint Polar Satellite System (JPSS). JPSS replaced the afternoon orbit component and ground processing of the old POES system managed by NOAA. JPSS satellites carry sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is the Common Ground System (CGS), and provides command, control, and communications (C3), data processing and product delivery. CGS's data processing capability provides environmental data products (Sensor Data Records (SDRs) and Environmental Data Records (EDRs)) to the NOAA Satellite Operations Facility. The first satellite in the JPSS constellation, S-NPP, was launched in October 2011. The second satellite, JPSS-1, is scheduled for launch in January 2017. During a satellite's calibration and validation (Cal/Val) campaign, numerous algorithm updates occur. Changes identified during Cal/Val become available for implementation into the operational system for both S-NPP and JPSS-1. In addition, new capabilities, such as higher spectral and spatial resolution, will be exercised on JPSS-1. This paper will describe changes to current algorithms and products as a result of S-NPP Cal/Val and related initiatives for improved capabilities. Improvements include Cross Track Infrared Sounder high spectral processing, extended spectral and spatial ranges for Ozone Mapping and Profiler Suite ozone Total Column and Nadir Profiles, and updates to Vegetation Index, Snow Cover, Active Fires, Suspended Matter, and Ocean Color. Updates will include Sea Surface Temperature, Cloud Mask, Cloud Properties, and other improvements.

Characteristic vector analysis of inflection ratio spectra: New technique for analysis of ocean color data

NASA Technical Reports Server (NTRS)

Grew, G. W.

1985-01-01

Characteristic vector analysis applied to inflection ratio spectra is a new approach to analyzing spectral data. The technique applied to remote data collected with the multichannel ocean color sensor (MOCS), a passive sensor, simultaneously maps the distribution of two different phytopigments, chlorophyll alpha and phycoerythrin, the ocean. The data set presented is from a series of warm core ring missions conducted during 1982. The data compare favorably with a theoretical model and with data collected on the same mission by an active sensor, the airborne oceanographic lidar (AOL).

Retinex at 50: color theory and spatial algorithms, a review

NASA Astrophysics Data System (ADS)

McCann, John J.

2017-05-01

Retinex Imaging shares two distinct elements: first, a model of human color vision; second, a spatial-imaging algorithm for making better reproductions. Edwin Land's 1964 Retinex Color Theory began as a model of human color vision of real complex scenes. He designed many experiments, such as Color Mondrians, to understand why retinal cone quanta catch fails to predict color constancy. Land's Retinex model used three spatial channels (L, M, S) that calculated three independent sets of monochromatic lightnesses. Land and McCann's lightness model used spatial comparisons followed by spatial integration across the scene. The parameters of their model were derived from extensive observer data. This work was the beginning of the second Retinex element, namely, using models of spatial vision to guide image reproduction algorithms. Today, there are many different Retinex algorithms. This special section, "Retinex at 50," describes a wide variety of them, along with their different goals, and ground truths used to measure their success. This paper reviews (and provides links to) the original Retinex experiments and image-processing implementations. Observer matches (measuring appearances) have extended our understanding of how human spatial vision works. This paper describes a collection very challenging datasets, accumulated by Land and McCann, for testing algorithms that predict appearance.

Probabilistic fusion of stereo with color and contrast for bilayer segmentation.

PubMed

Kolmogorov, Vladimir; Criminisi, Antonio; Blake, Andrew; Cross, Geoffrey; Rother, Carsten

2006-09-01

This paper describes models and algorithms for the real-time segmentation of foreground from background layers in stereo video sequences. Automatic separation of layers from color/contrast or from stereo alone is known to be error-prone. Here, color, contrast, and stereo matching information are fused to infer layers accurately and efficiently. The first algorithm, Layered Dynamic Programming (LDP), solves stereo in an extended six-state space that represents both foreground/background layers and occluded regions. The stereo-match likelihood is then fused with a contrast-sensitive color model that is learned on-the-fly and stereo disparities are obtained by dynamic programming. The second algorithm, Layered Graph Cut (LGC), does not directly solve stereo. Instead, the stereo match likelihood is marginalized over disparities to evaluate foreground and background hypotheses and then fused with a contrast-sensitive color model like the one used in LDP. Segmentation is solved efficiently by ternary graph cut. Both algorithms are evaluated with respect to ground truth data and found to have similar performance, substantially better than either stereo or color/ contrast alone. However, their characteristics with respect to computational efficiency are rather different. The algorithms are demonstrated in the application of background substitution and shown to give good quality composite video output.

Effect of Mineral Dust on Ocean Color Retrievals From Space: A Radiative Transfer Simulation Study

NASA Astrophysics Data System (ADS)

Ahmad, Z.; Franz, B. A.

2016-02-01

In this paper we examine the effect of mineral aerosols (dust) on the retrieval of ocean colors from space. Mineral aerosols are one of the major components of all aerosols found in the earth's atmosphere. These are mainly soil particles that originate from arid and semiarid regions of the world and are blown away by winds thousands of kilometers away from their source regions. The radii of these aerosols are between 0.1 and 1.0 μm and their resident time in the atmosphere is about 21 days. The primary focus of this paper is to estimate the remote sensing reflectance (Rrs) errors in the presence of absorbing aerosols over ocean. The present study is based on radiative transfer (RT) simulations, and it is particularly relevant to ocean color retrievals from sensors like MODIS, MERIS, VIIRS, and the future PACE/OCI. In the simulations, we have used mineralogy to determine the spectral dependence of aerosol refractive index, and modeled the aerosols to represent dust over Cape Verde (Sal Island). As a part of this study, we will present the results for retrieved aerosol optical thickness (τ), Angstrom exponent (α), and remote sensing reflectance (Rrs) and compare them with similar results for non-absorbing aerosols. In addition, we will show how aerosol layer height affects the ocean color retrievals.

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

NASA Astrophysics Data System (ADS)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

Encoding color information for visual tracking: Algorithms and benchmark.

PubMed

Liang, Pengpeng; Blasch, Erik; Ling, Haibin

2015-12-01

While color information is known to provide rich discriminative clues for visual inference, most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to integrate color in tracking, there is a lack of comprehensive understanding of the role color information can play. In this paper, we attack this problem by conducting a systematic study from both the algorithm and benchmark perspectives. On the algorithm side, we comprehensively encode 10 chromatic models into 16 carefully selected state-of-the-art visual trackers. On the benchmark side, we compile a large set of 128 color sequences with ground truth and challenge factor annotations (e.g., occlusion). A thorough evaluation is conducted by running all the color-encoded trackers, together with two recently proposed color trackers. A further validation is conducted on an RGBD tracking benchmark. The results clearly show the benefit of encoding color information for tracking. We also perform detailed analysis on several issues, including the behavior of various combinations between color model and visual tracker, the degree of difficulty of each sequence for tracking, and how different challenge factors affect the tracking performance. We expect the study to provide the guidance, motivation, and benchmark for future work on encoding color in visual tracking.

BIO ARGO floats: tools for operational monitoring of the Black Sea

NASA Astrophysics Data System (ADS)

Palazov, Atanas; Slabakova, Violeta; Peneva, Elisaveta; Stanev, Emil

2014-05-01

The assessment of ecological status in the context of the Water Framework Directive (WFD) and Marine Strategy Framework Directive (MSFD) requires comprehensive knowledge and understanding of the physical and biogeochemical processes that determine the functioning of marine ecosystems. One of the main challenges however is the need of data with frequency relevant to the spatial and temporal scales of the ecological processes. The majority of in situ observations that are commonly used for ecological monitoring of the Black Sea are generally based on near-shore monitoring programs or irregular oceanographic cruises that provide either non-synoptic, coarse resolution realizations of large scale processes or detailed, but time and site specific snapshots of local features. These gaps can be filled by two independent sources: satellite observation and profiling floats. In fact satellite ocean color sensors allows for determination at synoptic scale of water quality parameters through its absorption properties. However the satellite ocean color methods have a number of limitations such as: measurements can only be made during daylight hours; require cloud-free conditions and are sensitive to atmospheric aerosols; provide information only for the upper layer of the ocean (approximately the depth of 10% incident light); algorithms developed for global applications are a source of large uncertainties in the marginal seas and costal areas. These constrains of the optical remote sensing observations can be avoided by using miniature biogeochemical sensors and autonomous platforms that offer remarkable perspectives for observing the "biological" ocean, notably at critical spatiotemporal scales which have been out of reach until recently (Claustre et al., 2010). In the frame of "E-AIMS: Euro-Argo Improvements for the GMES marine Service" 7 EC FP project two Bio Argo floats were deployed in the Black Sea. Beside the traditionally CTD the floats were equipped with biogeochemical sensors (oxygen, irradiance, chl-a and backscattering). The selection of the deployment locations was limited only to the Bulgarian Black Sea waters, so that the optimal deployment strategy that has been chosen was the floats to be deployed in the maximum distant positions from each other along the Black Sea geostrophic current at depth ~ 1800 m. Coincident biogeochemical and in-water radiometric measurements were collected at the time of each float deployment to ensure intercalibration of the instruments mounted on the floats and as well as to find empirical relationship between optical data and biogeochemical variables. The data obtained form Bio floats will be used to: investigate the seasonal evolution of oxygen in the upper layers, including the subsurface oxygen maximum; study the seasonal and inter annual dynamics of phytoplankton blooms in the deeper Black Sea; cross validation of satellite derived Chl-a and backscattering. References: Claustre et al. (2010). Bio-optical profiling floats as new observational tools for biogeochemical and ecosystem studies: potential synergies with ocean color remote sensing. Proceedings of the "OceanObs'09: Sustained Ocean Observations and Information for Society" Conference, Venice/Italy.

A Decade of Satellite Ocean Color Observations

NASA Technical Reports Server (NTRS)

McClain, Charles R.

2009-01-01

After the successful Coastal Zone Color Scanner (CZCS, 1978-1986), demonstration that quantitative estimations of geophysical variables such as chlorophyll a and diffuse attenuation coefficient could be derived from top of the atmosphere radiances, a number of international missions with ocean color capabilities were launched beginning in the late 1990s. Most notable were those with global data acquisition capabilities, i.e., the Ocean Color and Temperature Sensor (OCTS 1996-1997), the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, United States, 1997-present), two Moderate Resolution Imaging Spectroradiometers, (MODIS, United States, Terra/2000-present and Aqua/2002-present), the Global Imager (GLI, Japan, 2002-2003), and the Medium Resolution Imaging Spectrometer (MERIS, European Space Agency, 2002-present). These missions have provided data of exceptional quality and continuity, allowing for scientific inquiries into a wide variety of marine research topics not possible with the CZCS. This review focuses on the scientific advances made over the past decade using these data sets.

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

NASA Astrophysics Data System (ADS)

Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang

2017-07-01

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

Analyses of multi-color plant-growth light sources in achieving maximum photosynthesis efficiencies with enhanced color qualities.

PubMed

Wu, Tingzhu; Lin, Yue; Zheng, Lili; Guo, Ziquan; Xu, Jianxing; Liang, Shijie; Liu, Zhuguagn; Lu, Yijun; Shih, Tien-Mo; Chen, Zhong

2018-02-19

An optimal design of light-emitting diode (LED) lighting that benefits both the photosynthesis performance for plants and the visional health for human eyes has drawn considerable attention. In the present study, we have developed a multi-color driving algorithm that serves as a liaison between desired spectral power distributions and pulse-width-modulation duty cycles. With the aid of this algorithm, our multi-color plant-growth light sources can optimize correlated-color temperature (CCT) and color rendering index (CRI) such that photosynthetic luminous efficacy of radiation (PLER) is maximized regardless of the number of LEDs and the type of photosynthetic action spectrum (PAS). In order to illustrate the accuracies of the proposed algorithm and the practicalities of our plant-growth light sources, we choose six color LEDs and German PAS for experiments. Finally, our study can help provide a useful guide to improve light qualities in plant factories, in which long-term co-inhabitance of plants and human beings is required.

Towards representation of a perceptual color manifold using associative memory for color constancy.

PubMed

Seow, Ming-Jung; Asari, Vijayan K

2009-01-01

In this paper, we propose the concept of a manifold of color perception through empirical observation that the center-surround properties of images in a perceptually similar environment define a manifold in the high dimensional space. Such a manifold representation can be learned using a novel recurrent neural network based learning algorithm. Unlike the conventional recurrent neural network model in which the memory is stored in an attractive fixed point at discrete locations in the state space, the dynamics of the proposed learning algorithm represent memory as a nonlinear line of attraction. The region of convergence around the nonlinear line is defined by the statistical characteristics of the training data. This learned manifold can then be used as a basis for color correction of the images having different color perception to the learned color perception. Experimental results show that the proposed recurrent neural network learning algorithm is capable of color balance the lighting variations in images captured in different environments successfully.

Agricultural produce grading and sorting system using color CCD and new color identification algorithm

NASA Astrophysics Data System (ADS)

Wang, Dongsheng; Zou, Jizuo; Yang, Yunping; Dong, Jianhua; Zhang, Yuanxiang

1996-10-01

A high-speed automatic agricultural produce grading and sorting system using color CCD and new color identification algorithm has been developed. In a typical application, the system can sort almonds into tow output grades according to their color. Almonds ar rich in 18 kinds of amino acids and 13 kinds of micro minerals and vitamins and can be made into almond drink. In order to ensure the drink quality, almonds must be sorted carefully before being made into a drink. Using this system, almonds can be sorted into two grades: up to grade and below grade almonds or foreign materials. A color CCD inspects the almonds passing on a conveyor of rotating rollers, a color identification algorithm grades almonds and distinguishes foreign materials from almonds. Employing an elaborately designed mechanism, the below grade almonds and foreign materials can be removed effectively from the raw almonds. This system can be easily adapted for inspecting and sorting other kinds of agricultural produce such as peanuts, beans tomatoes and so on.

Dehazed Image Quality Assessment by Haze-Line Theory

NASA Astrophysics Data System (ADS)

Song, Yingchao; Luo, Haibo; Lu, Rongrong; Ma, Junkai

2017-06-01

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. However, there is a lack of evaluation metrics to assess the performance of these algorithms or rate them. In this paper, an indicator of contrast enhancement is proposed basing on the newly proposed haze-line theory. The theory assumes that colors of a haze-free image are well approximated by a few hundred distinct colors, which form tight clusters in RGB space. The presence of haze makes each color cluster forms a line, which is named haze-line. By using these haze-lines, we assess performance of dehazing algorithms designed to enhance the contrast by measuring the inter-cluster deviations between different colors of dehazed image. Experimental results demonstrated that the proposed Color Contrast (CC) index correlates well with human judgments of image contrast taken in a subjective test on various scene of dehazed images and performs better than state-of-the-art metrics.

An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image.

PubMed

Cui, Xinchun; Niu, Yuying; Zheng, Xiangwei; Han, Yingshuai

2018-01-01

In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing. Our new algorithm uses differential evolution algorithm with adaptive optimization to choose the right scaling factors. Experimental results show that the proposed algorithm has a better performance in terms of invisibility and robustness.

Eddies in the Southern Ocean

NASA Image and Video Library

2015-04-08

The cloud cover over the Southern Ocean occasionally parts as it did on January 1, 2015 just west of the Drake Passage where the VIIRS instrument on the Suomi NPP satellite glimpsed the above collection of ocean-color delineated eddies which have diameters ranging from a couple of kilometers to a couple of hundred kilometers. Recent studies indicate that eddy activity has been increasing in the Southern Ocean with possible implications for climate change. Credit: NASA's OceanColor/Suomi NPP/VIIRS NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Oceanic Lithosphere Magnetization: Marine Magnetic Investigations of Crustal Accretion and Tectonic Processes in Mid-Ocean Ridge Environments

DTIC Science & Technology

2007-09-01

vs TiO2 ...................... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238 A2.4 Discussion...types can not be formed by metamorphic processes. Diabase samples have a green color that is characteristic of chlorite, a low temperature greenschist...grain boundaries of altered olivine and plagioclase (Fig. 3-14c and 13d). Zoning is observed within the oxides indicating alteration; light colored oxides

Adaptive intercolor error prediction coder for lossless color (rgb) picutre compression

NASA Astrophysics Data System (ADS)

Mann, Y.; Peretz, Y.; Mitchell, Harvey B.

2001-09-01

Most of the current lossless compression algorithms, including the new international baseline JPEG-LS algorithm, do not exploit the interspectral correlations that exist between the color planes in an input color picture. To improve the compression performance (i.e., lower the bit rate) it is necessary to exploit these correlations. A major concern is to find efficient methods for exploiting the correlations that, at the same time, are compatible with and can be incorporated into the JPEG-LS algorithm. One such algorithm is the method of intercolor error prediction (IEP), which when used with the JPEG-LS algorithm, results on average in a reduction of 8% in the overall bit rate. We show how the IEP algorithm can be simply modified and that it nearly doubles the size of the reduction in bit rate to 15%.

Traffic sign recognition by color segmentation and neural network

NASA Astrophysics Data System (ADS)

Surinwarangkoon, Thongchai; Nitsuwat, Supot; Moore, Elvin J.

2011-12-01

An algorithm is proposed for traffic sign detection and identification based on color filtering, color segmentation and neural networks. Traffic signs in Thailand are classified by color into four types: namely, prohibitory signs (red or blue), general warning signs (yellow) and construction area warning signs (amber). A color filtering method is first used to detect traffic signs and classify them by type. Then color segmentation methods adapted for each color type are used to extract inner features, e.g., arrows, bars etc. Finally, neural networks trained to recognize signs in each color type are used to identify any given traffic sign. Experiments show that the algorithm can improve the accuracy of traffic sign detection and recognition for the traffic signs used in Thailand.

Optical Sensors for Planetary Radiant Energy (OSPREy): Calibration and Validation of Current and Next-Generation NASA Missions

NASA Technical Reports Server (NTRS)

Hooker, Stanford B.; Bernhard, Germar; Morrow, John H.; Booth, Charles R.; Comer, Thomas; Lind, Randall N.; Quang, Vi

2012-01-01

A principal objective of the Optical Sensors for Planetary Radiance Energy (OSPREy) activity is to establish an above-water radiometer system as a lower-cost alternative to existing in-water systems for the collection of ground-truth observations. The goal is to be able to make high-quality measurements satisfying the accuracy requirements for the vicarious calibration and algorithm validation of next-generation satellites that make ocean color and atmospheric measurements. This means the measurements will have a documented uncertainty satisfying the established performance metrics for producing climate-quality data records. The OSPREy approach is based on enhancing commercial-off-the-shelf fixed-wavelength and hyperspectral sensors to create hybridspectral instruments with an improved accuracy and spectral resolution, as well as a dynamic range permitting sea, Sun, sky, and Moon observations. Greater spectral diversity in the ultraviolet (UV) will be exploited to separate the living and nonliving components of marine ecosystems; UV bands will also be used to flag and improve atmospheric correction algorithms in the presence of absorbing aerosols. The short-wave infrared (SWIR) is expected to improve atmospheric correction, because the ocean is radiometrically blacker at these wavelengths. This report describes the development of the sensors, including unique capabilities like three-axis polarimetry; the documented uncertainty will be presented in a subsequent report.

Remote sensing tools to study ocean biogeochemistry: state of the art

NASA Technical Reports Server (NTRS)

Carr, M. E.

2001-01-01

Remote sensing of the world ocean presently provides measurements of sea-surface temperature, sea surface height, wind speed and direction, and ocean color, from which chlorophyll concentration and aerosol optical thickness are obtained.

Spaceborne Lidar in the Study of Marine Systems.

PubMed

Hostetler, Chris A; Behrenfeld, Michael J; Hu, Yongxiang; Hair, Johnathan W; Schulien, Jennifer A

2018-01-03

Satellite passive ocean color instruments have provided an unbroken ∼20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

Spaceborne Lidar in the Study of Marine Systems

NASA Astrophysics Data System (ADS)

Hostetler, Chris A.; Behrenfeld, Michael J.; Hu, Yongxiang; Hair, Johnathan W.; Schulien, Jennifer A.

2018-01-01

Satellite passive ocean color instruments have provided an unbroken ˜20-year record of global ocean plankton properties, but this measurement approach has inherent limitations in terms of spatial-temporal sampling and ability to resolve vertical structure within the water column. These limitations can be addressed by coupling ocean color data with measurements from a spaceborne lidar. Airborne lidars have been used for decades to study ocean subsurface properties, but recent breakthroughs have now demonstrated that plankton properties can be measured with a satellite lidar. The satellite lidar era in oceanography has arrived. Here, we present a review of the lidar technique, its applications in marine systems, a perspective on what can be accomplished in the near future with an ocean- and atmosphere-optimized satellite lidar, and a vision for a multiplatform virtual constellation of observational assets that would enable a three-dimensional reconstruction of global ocean ecosystems.

A semianalytical MERIS green-red band algorithm for identifying phytoplankton bloom types in the East China Sea

NASA Astrophysics Data System (ADS)

Tao, Bangyi; Mao, Zhihua; Lei, Hui; Pan, Delu; Bai, Yan; Zhu, Qiankun; Zhang, Zhenglong

2017-03-01

A new bio-optical algorithm based on the green and red bands of the Medium Resolution Imaging Spectrometer (MERIS) is developed to differentiate the harmful algal blooms of Prorocentrum donghaiense Lu (P. donghaiense) from diatom blooms in the East China Sea (ECS). Specifically, a novel green-red index (GRI), actually an indicator for a(510) of bloom waters, is retrieved from a semianalytical bio-optical model based on the green and red bands of phytoplankton-absorption and backscattering spectra. In addition, a MERIS-based diatom index (DIMERIS) is derived by adjusting a Moderate Resolution Imaging Spectroradiometer (MODIS) diatom index algorithm to the MERIS bands. Finally, bloom types are effectively differentiated in the feature spaces of the green-red index and DIMERIS. Compared with three previous MERIS-based quasi-analytical algorithm (QAA) algorithms and three existing classification methods, the proposed GRI and classification method have the best discrimination performance when using the MERIS data. Further validations of the algorithm by using several MERIS image series and near-concurrent in situ observations indicate that our algorithm yields the best classification accuracy and thus can be used to reliably detect and classify P. donghaiense and diatom blooms in the ECS. This is the first time that the MERIS data have been used to identify bloom types in the ECS. Our algorithm can also be used for the successor of the MERIS, the Ocean and Land Color Instrument, which will aid the long-term observation of species succession in the ECS.

Statistical simplex approach to primary and secondary color correction in thick lens assemblies

NASA Astrophysics Data System (ADS)

Ament, Shelby D. V.; Pfisterer, Richard

2017-11-01

A glass selection optimization algorithm is developed for primary and secondary color correction in thick lens systems. The approach is based on the downhill simplex method, and requires manipulation of the surface color equations to obtain a single glass-dependent parameter for each lens element. Linear correlation is used to relate this parameter to all other glass-dependent variables. The algorithm provides a statistical distribution of Abbe numbers for each element in the system. Examples of several lenses, from 2-element to 6-element systems, are performed to verify this approach. The optimization algorithm proposed is capable of finding glass solutions with high color correction without requiring an exhaustive search of the glass catalog.

Contourlet domain multiband deblurring based on color correlation for fluid lens cameras.

PubMed

Tzeng, Jack; Liu, Chun-Chen; Nguyen, Truong Q

2010-10-01

Due to the novel fluid optics, unique image processing challenges are presented by the fluidic lens camera system. Developed for surgical applications, unique properties, such as no moving parts while zooming and better miniaturization than traditional glass optics, are advantages of the fluid lens. Despite these abilities, sharp color planes and blurred color planes are created by the nonuniform reaction of the liquid lens to different color wavelengths. Severe axial color aberrations are caused by this reaction. In order to deblur color images without estimating a point spread function, a contourlet filter bank system is proposed. Information from sharp color planes is used by this multiband deblurring method to improve blurred color planes. Compared to traditional Lucy-Richardson and Wiener deconvolution algorithms, significantly improved sharpness and reduced ghosting artifacts are produced by a previous wavelet-based method. Directional filtering is used by the proposed contourlet-based system to adjust to the contours of the image. An image is produced by the proposed method which has a similar level of sharpness to the previous wavelet-based method and has fewer ghosting artifacts. Conditions for when this algorithm will reduce the mean squared error are analyzed. While improving the blue color plane by using information from the green color plane is the primary focus of this paper, these methods could be adjusted to improve the red color plane. Many multiband systems such as global mapping, infrared imaging, and computer assisted surgery are natural extensions of this work. This information sharing algorithm is beneficial to any image set with high edge correlation. Improved results in the areas of deblurring, noise reduction, and resolution enhancement can be produced by the proposed algorithm.

Remote sensing of ocean currents

NASA Technical Reports Server (NTRS)

Maul, G. A. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Monthly field experiments in support of the NOAA investigation of ocean color boundary determination using ERTS-1 data have been conducted since June 1972. The boundary between coastal waters and the Loop Current has been detected by ERTS-1 as a result of sea state changes as well as color differences. Ocean information is contained in all 24 channels of the Bendix MSS flown on the C-130 in June 1972; this includes UV, visible, reflected IR, and emitted IR. Computer enhancement of MSS data is revealing many features not shown in the NDPF product.

Seasonal and nonseasonal variability of satellite-derived chlorophyll and colored dissolved organic matter concentration in the California Current

NASA Astrophysics Data System (ADS)

Kahru, Mati; Mitchell, B. Greg

2001-02-01

Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.

Application of a Topological Metric for Assessing Numerical Ocean Models with Satellite Observations

NASA Astrophysics Data System (ADS)

Morey, S. L.; Dukhovskoy, D. S.; Hiester, H. R.; Garcia-Pineda, O. G.; MacDonald, I. R.

2015-12-01

Satellite-based sensors provide a vast amount of observational data over the world ocean. Active microwave radars measure changes in sea surface height and backscattering from surface waves. Data from passive radiometers sensing emissions in multiple spectral bands can directly measure surface temperature, be combined with other data sources to estimate salinity, or processed to derive estimates of optically significant quantities, such as concentrations of biochemical properties. Estimates of the hydrographic variables can be readily used for assimilation or assessment of hydrodynamic ocean models. Optical data, however, have been underutilized in ocean circulation modeling. Qualitative assessments of oceanic fronts and other features commonly associated with changes in optically significant quantities are often made through visual comparison. This project applies a topological approach, borrowed from the field of computer image recognition, to quantitatively evaluate ocean model simulations of features that are related to quantities inferred from satellite imagery. The Modified Hausdorff Distance (MHD) provides a measure of the similarity of two shapes. Examples of applications of the MHD to assess ocean circulation models are presented. The first application assesses several models' representation of the freshwater plume structure from the Mississippi River, which is associated with a significant expression of color, using a satellite-derived ocean color index. Even though the variables being compared (salinity and ocean color index) differ, the MHD allows contours of the fields to be compared topologically. The second application assesses simulations of surface oil transport driven by winds and ocean model currents using surface oil maps derived from synthetic aperture radar backscatter data. In this case, maps of time composited oil coverage are compared between the simulations and satellite observations.

Applications of MODIS Fluorescent Line Height Measurements to Monitor Water Quality Trends and Algal Bloom Activity

NASA Technical Reports Server (NTRS)

Fischer, Andrew; Moreno-Mardinan, Max; Ryan, John P.

2012-01-01

Recent advances in satellite and airborne remote sensing, such as improvements in sensor and algorithm calibrations, processing techniques and atmospheric correction procedures have provided for increased coverage of remote-sensing, ocean-color products for coastal regions. In particular, for the Moderate Resolution Imaging Spectrometer (MODIS) sensor calibration updates, improved aerosol retrievals and new aerosol models has led to improved atmospheric correction algorithms for turbid waters and have improved the retrieval of ocean color in coastal waters. This has opened the way for studying ocean phenomena and processes at finer spatial scales, such as the interactions at the land-sea interface, trends in coastal water quality and algal blooms. Human population growth and changes in coastal management practices have brought about significant changes in the concentrations of organic and inorganic, particulate and dissolved substances entering the coastal ocean. There is increasing concern that these inputs have led to declines in water quality and have increase local concentrations of phytoplankton, which cause harmful algal blooms. In two case studies we present MODIS observations of fluorescence line height (FLH) to 1) assess trends in water quality for Tampa Bay, Florida and 2) illustrate seasonal and annual variability of algal bloom activity in Monterey Bay, California as well as document estuarine/riverine plume induced red tide events. In a comprehensive analysis of long term (2003-2011) in situ monitoring data and satellite imagery from Tampa Bay we assess the validity of the MODIS FLH product against chlorophyll-a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions and to develop a near decadal trend in water quality changes. In situ monitoring locations that correlated well with satellite imagery were in depths greater than seven meters and were located over five kilometers from shore. Water quality parameter of total nitrogen, phosphorous, turbidity and biological oxygen demand had high correlations with these sites, as well. Satellite FLH estimates show improving water quality from 2003-2007 with a slight decline up through 2011. Dinoflagellate blooms in Monterey Bay, California (USA) have recently increased in frequency and intensity. Nine years of MODIS FLH observations are used to describe the annual and seasonal variability of bloom activity within the Bay. Three classes of MODIS algorithms were correlated against in situ chlorophyll measurements. The FLH algorithm provided the most robust estimate of bloom activity. Elevated concentrations of phytoplankton were evident during the months of August-November, a period during which increased occurrences of dinoflagellate blooms have been observed in situ. Seasonal patterns of FLH show the on- and offshore movement of areas of high phytoplankton biomass between oceanographic seasons. Higher concentrations of phytoplankton are also evident in the vicinity of the land-based nutrient sources and outflows, and the cyclonic bay-wide circulation can transport these nutrients to the northern Bay bloom incubation region. Both of these case studies illustrate the utility MODIS FLH observations in supporting management decisions in coastal and estuarine waters.

Skin subspace color modeling for daytime and nighttime group activity recognition in confined operational spaces

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Poshtyar, Azin; Chan, Alex; Hu, Shuowen

2016-05-01

In many military and homeland security persistent surveillance applications, accurate detection of different skin colors in varying observability and illumination conditions is a valuable capability for video analytics. One of those applications is In-Vehicle Group Activity (IVGA) recognition, in which significant changes in observability and illumination may occur during the course of a specific human group activity of interest. Most of the existing skin color detection algorithms, however, are unable to perform satisfactorily in confined operational spaces with partial observability and occultation, as well as under diverse and changing levels of illumination intensity, reflection, and diffraction. In this paper, we investigate the salient features of ten popular color spaces for skin subspace color modeling. More specifically, we examine the advantages and disadvantages of each of these color spaces, as well as the stability and suitability of their features in differentiating skin colors under various illumination conditions. The salient features of different color subspaces are methodically discussed and graphically presented. Furthermore, we present robust and adaptive algorithms for skin color detection based on this analysis. Through examples, we demonstrate the efficiency and effectiveness of these new color skin detection algorithms and discuss their applicability for skin detection in IVGA recognition applications.

High temporal resolution aerosol retrieval using Geostationary Ocean Color Imager: application and initial validation

NASA Astrophysics Data System (ADS)

Zhang, Yuhuan; Li, Zhengqiang; Zhang, Ying; Hou, Weizhen; Xu, Hua; Chen, Cheng; Ma, Yan

2014-01-01

The Geostationary Ocean Color Imager (GOCI) provides multispectral imagery of the East Asia region hourly from 9:00 to 16:00 local time (GMT+9) and collects multispectral imagery at eight spectral channels (412, 443, 490, 555, 660, 680, 745, and 865 nm) with a spatial resolution of 500 m. Thus, this technology brings significant advantages to high temporal resolution environmental monitoring. We present the retrieval of aerosol optical depth (AOD) in northern China based on GOCI data. Cross-calibration was performed against Moderate Resolution Imaging Spectrometer (MODIS) data in order to correct the land calibration bias of the GOCI sensor. AOD retrievals were then accomplished using a look-up table (LUT) strategy with assumptions of a quickly varying aerosol and a slowly varying surface with time. The AOD retrieval algorithm calculates AOD by minimizing the surface reflectance variations of a series of observations in a short period of time, such as several days. The monitoring of hourly AOD variations was implemented, and the retrieved AOD agreed well with AErosol RObotic NETwork (AERONET) ground-based measurements with a good R2 of approximately 0.74 at validation sites at the cities of Beijing and Xianghe, although intercept bias may be high in specific cases. The comparisons with MODIS products also show a good agreement in AOD spatial distribution. This work suggests that GOCI imagery can provide high temporal resolution monitoring of atmospheric aerosols over land, which is of great interest in climate change studies and environmental monitoring.

Mapping CDOM Concentration in Waters Influenced by the Mississippi River Plume

NASA Technical Reports Server (NTRS)

Miller, Richard L.; DelCastillo, Carlos E.; Powell, Rodney T.; DSa, Eurico; Spiering, Bruce

2002-01-01

Colored dissolved organic matter (CDOM) is often an important component of the organic carbon pool in river-dominated coastal margins. CDOM directly influences remote sensing applications through its strong absorption in the UV and blue regions of the spectrum. This effect can complicate the use of chlorophyll a retrieval algorithms and phytoplankton production models that are based on remotely sensed ocean color. As freshwater input is the principle source of CDOM in coastal margins, CDOM distribution can often be described by conservative mixing with open ocean waters and may serve as an optical tracer of riverine water. Hence, there is considerable interest in the ability to accurately measure and map CDOM concentrations as well as understand the processes that govern the optical properties and distribution of CDOM in coastal environments. We are examining CDOM dynamics in the waters influenced by the Mississippi River plume. Our program incorporates discrete samples, flow-through measurements, and remote sensing. CDOM absorption spectra of discrete samples are measured at sea using a portable, multiple pathlength waveguide system. A SAFire multi-spectral fluorescence meter provides spectral characterization of CDOM (fluorescence and absorption) using a ship flow-through system for continuous surface mapping. In situ reflectance spectra are obtained by a hand held spectroradiometer. Remotely sensed images are obtained from the SeaWiFS and CRIS (Coastal Research Imaging Spectrometer) instruments. We describe here the instruments used, sampling protocols employed, and the relationships derived between in situ measurements and remotely sensed data for this optically complex environment.

Accurately Measuring the Color of the Ocean on Earth and from Space: Uncertainties Revisited and A Report from the Community-Led Spectral Absorption Workshop to Update and Revise the NASA Inherent Optical Properties Protocol

NASA Technical Reports Server (NTRS)

Neeley, Aimee Renee

2014-01-01

The color of the ocean (apparent optical properties or AOPs) is determined by the spectral scattering and absorption of light by its dissolved and particulate constituents.The absorption and scattering properties of the water column are the so-called inherent optical properties.

A combination chaotic system and application in color image encryption

NASA Astrophysics Data System (ADS)

Parvaz, R.; Zarebnia, M.

2018-05-01

In this paper, by using Logistic, Sine and Tent systems we define a combination chaotic system. Some properties of the chaotic system are studied by using figures and numerical results. A color image encryption algorithm is introduced based on new chaotic system. Also this encryption algorithm can be used for gray scale or binary images. The experimental results of the encryption algorithm show that the encryption algorithm is secure and practical.

LIDAR and acoustics applications to ocean productivity

NASA Technical Reports Server (NTRS)

Collins, D. J.

1982-01-01

The requirements for the submersible, the instrumentation necessary to perform these measurements, and the optical and acoustical technology required to develop the ocean color scanner instrumentation are described. The development of a second generation ocean color scanner produced the need for coincident in situ scientific measurements which examine the primary productivity of the upper ocean on time and space scales which are large compared to the environmental scales. The vertical and horizontal variability of the biota, including the relationship between chlorophyll and primary productivity, the productivity of zooplankton, and the dynamic interaction between phytoplankton and zooplankton, and between these populations and the physical environment are investigated. A towed submersible will be constructed which accommodates both an underwater LIDAR instrument and a multifrequency sonar.

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Diurnal variability in carbon and nitrogen pools within Chesapeake Bay and northern Gulf of Mexico: implications for future ocean color satellite sensors

NASA Astrophysics Data System (ADS)

Mannino, A.; Novak, M. G.; Tzortziou, M.; Salisbury, J.

2016-02-01

Relative to their areal extent, estuaries and coastal ocean ecosystems contribute disproportionately more to global biogeochemical cycling of carbon, nitrogen and other elements compared to the open ocean. Applying ocean color satellite data to study biological and biogeochemical processes within coastal ecosystems is challenging due to the complex mixtures of aquatic constituents derived from terrestrial, anthropogenic, and marine sources, human-impacted atmospheric properties, presence of clouds during satellite overpass, fine-scale spatial gradients, and time-varying processes on diurnal scales that cannot be resolved with current sensors. On diurnal scales, biological, photochemical, and biogeochemical processes are regulated by the variation in solar radiation. Other physical factors, such as tides, river discharge, estuarine and coastal ocean circulation, wind-driven mixing, etc., impart further variability on biological and biogeochemical processes on diurnal to multi-day time scales. Efforts to determine the temporal frequency required from a NASA GEO-CAPE ocean color satellite sensor to discern diurnal variability C and N stocks, fluxes and productivity culminated in field campaigns in the Chesapeake Bay and northern Gulf of Mexico. Near-surface drogues were released and tracked in quasi-lagrangian space to monitor hourly changes in community production, C and N stocks, and optical properties. While only small diurnal changes were observed in dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) absorption in Chesapeake Bay, substantial variation in particulate organic carbon (POC) and nitrogen (PN), chlorophyll-a, and inorganic nitrogen (DIN) were measured. Similar or greater diurnal changes in POC, PN, chlorophyll-a and DIN were found in Gulf of Mexico nearshore and offshore sites. These results suggest that satellite observations at hourly frequency are desirable to capture diurnal variability in carbon and nitrogen stocks, fluxes and productivity within coastal ecosystems.

An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters.

PubMed

Moore, Timothy S; Dowell, Mark D; Bradt, Shane; Verdu, Antonio Ruiz

2014-03-05

Bio-optical models are based on relationships between the spectral remote sensing reflectance and optical properties of in-water constituents. The wavelength range where this information can be exploited changes depending on the water characteristics. In low chlorophyll- a waters, the blue/green region of the spectrum is more sensitive to changes in chlorophyll- a concentration, whereas the red/NIR region becomes more important in turbid and/or eutrophic waters. In this work we present an approach to manage the shift from blue/green ratios to red/NIR-based chlorophyll- a algorithms for optically complex waters. Based on a combined in situ data set of coastal and inland waters, measures of overall algorithm uncertainty were roughly equal for two chlorophyll- a algorithms-the standard NASA OC4 algorithm based on blue/green bands and a MERIS 3-band algorithm based on red/NIR bands-with RMS error of 0.416 and 0.437 for each in log chlorophyll- a units, respectively. However, it is clear that each algorithm performs better at different chlorophyll- a ranges. When a blending approach is used based on an optical water type classification, the overall RMS error was reduced to 0.320. Bias and relative error were also reduced when evaluating the blended chlorophyll- a product compared to either of the single algorithm products. As a demonstration for ocean color applications, the algorithm blending approach was applied to MERIS imagery over Lake Erie. We also examined the use of this approach in several coastal marine environments, and examined the long-term frequency of the OWTs to MODIS-Aqua imagery over Lake Erie.

Regression analysis for LED color detection of visual-MIMO system

NASA Astrophysics Data System (ADS)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

The global distribution and dynamics of chromophoric dissolved organic matter.

PubMed

Nelson, Norman B; Siegel, David A

2013-01-01

Chromophoric dissolved organic matter (CDOM) is a ubiquitous component of the open ocean dissolved matter pool, and is important owing to its influence on the optical properties of the water column, its role in photochemistry and photobiology, and its utility as a tracer of deep ocean biogeochemical processes and circulation. In this review, we discuss the global distribution and dynamics of CDOM in the ocean, concentrating on developments in the past 10 years and restricting our discussion to open ocean and deep ocean (below the main thermocline) environments. CDOM has been demonstrated to exert primary control on ocean color by its absorption of light energy, which matches or exceeds that of phytoplankton pigments in most cases. This has important implications for assessing the ocean biosphere via ocean color-based remote sensing and the evaluation of ocean photochemical and photobiological processes. The general distribution of CDOM in the global ocean is controlled by a balance between production (primarily microbial remineralization of organic matter) and photolysis, with vertical ventilation circulation playing an important role in transporting CDOM to and from intermediate water masses. Significant decadal-scale fluctuations in the abundance of global surface ocean CDOM have been observed using remote sensing, indicating a potentially important role for CDOM in ocean-climate connections through its impact on photochemistry and photobiology.

The Living Ocean.

ERIC Educational Resources Information Center

National Aeronautics and Space Administration, Washington, DC.

This teaching guide contains information, activities, and discussion questions and answers about oceans for grades nine and ten. The information section covers the following topics: studying global ocean color from space, what can be seen from space, phytoplankton, carbon dioxide, and the greenhouse effect of the earth. (MKR)

Fusion of visible and near-infrared images based on luminance estimation by weighted luminance algorithm

NASA Astrophysics Data System (ADS)

Wang, Zhun; Cheng, Feiyan; Shi, Junsheng; Huang, Xiaoqiao

2018-01-01

In a low-light scene, capturing color images needs to be at a high-gain setting or a long-exposure setting to avoid a visible flash. However, such these setting will lead to color images with serious noise or motion blur. Several methods have been proposed to improve a noise-color image through an invisible near infrared flash image. A novel method is that the luminance component and the chroma component of the improved color image are estimated from different image sources [1]. The luminance component is estimated mainly from the NIR image via a spectral estimation, and the chroma component is estimated from the noise-color image by denoising. However, it is challenging to estimate the luminance component. This novel method to estimate the luminance component needs to generate the learning data pairs, and the processes and algorithm are complex. It is difficult to achieve practical application. In order to reduce the complexity of the luminance estimation, an improved luminance estimation algorithm is presented in this paper, which is to weight the NIR image and the denoised-color image and the weighted coefficients are based on the mean value and standard deviation of both images. Experimental results show that the same fusion effect at aspect of color fidelity and texture quality is achieved, compared the proposed method with the novel method, however, the algorithm is more simple and practical.

Bio-Optical and Geochemical Properties of the South Atlantic Subtropical Gyre

NASA Technical Reports Server (NTRS)

Signorini, S. R.; Hooker, Stanford B.; McClain, Charles R.

2003-01-01

An investigation of the bio-optical properties of the South Atlantic subtropical gyre (SASG) was conducted using data primarily from the UK Atlantic Meridional Transect (AMT) program and SeaWiFS. The AMT cruises extend from the UK to the Falklands Islands (sailing on the RRS James Clark Ross) with the purpose of improving our knowledge of surface layer hydrography, biogeochemical processes, ecosystem dynamics and food webs across basin scales in the Atlantic Ocean. Two objectives of the AMT program relevant to this study are the characterization of biogeochemical provinces and the analysis of optical and pigment parameters in connection with remote sensing ocean color data. The primary focus of this NASA Technical Memorandum is on the variability of the vertical distribution of phytoplankton pigments and associated absorption properties across the SASG, and their relevance to remote sensing algorithms. Therefore, a subset of the AMT data within the SASG from all available cruises was used in the analyses. One of the challenges addressed here is the determination of the SASG geographic boundaries. One of the major problems is to reconcile the properties of biogeochemical provinces. We use water mass analysis, dynamics of ocean currents, and meridional gradients of bio-optical properties, to identify the SASG boundaries.

Assessment of Satellite Radiometry in the Visible Domain

NASA Technical Reports Server (NTRS)

Melin, Frederick; Franz, Bryan A.

2014-01-01

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

Image Reconstruction for Hybrid True-Color Micro-CT

PubMed Central

Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

2013-01-01

X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid “true-color” micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose. PMID:22481806

The application analysis of the multi-angle polarization technique for ocean color remote sensing

NASA Astrophysics Data System (ADS)

Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Keli

2017-02-01

The multi-angle polarization technique, which uses the intensity of polarized radiation as the observed quantity, is a new remote sensing means for earth observation. With this method, not only can the multi-angle light intensity data be provided, but also the multi-angle information of polarized radiation can be obtained. So, the technique may solve the problems, those could not be solved with the traditional remote sensing methods. Nowadays, the multi-angle polarization technique has become one of the hot topics in the field of the international quantitative research on remote sensing. In this paper, we firstly introduce the principles of the multi-angle polarization technique, then the situations of basic research and engineering applications are particularly summarized and analysed in 1) the peeled-off method of sun glitter based on polarization, 2) the ocean color remote sensing based on polarization, 3) oil spill detection using polarization technique, 4) the ocean aerosol monitoring based on polarization. Finally, based on the previous work, we briefly present the problems and prospects of the multi-angle polarization technique used in China's ocean color remote sensing.

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

NASA Astrophysics Data System (ADS)

Shi, Chong; Nakajima, Teruyuki

2018-03-01

Retrieval of aerosol optical properties and water-leaving radiance over ocean is challenging since the latter mostly accounts for ˜ 10 % of the satellite-observed signal and can be easily influenced by the atmospheric scattering. Such an effort would be more difficult 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 multispectral satellite 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, an optimal estimation method is adopted to retrieve AOT and nLw iteratively. The algorithm is validated using Aerosol Robotic Network - Ocean Color (AERONET-OC) products selected from eight OC sites distributed over different waters, consisting of observations that covered glint and non-glint conditions from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. Results show a good consistency between retrieved and in situ measurements at each site. It is demonstrated that more accurate AOTs are determined based on the simultaneous retrieval method, particularly in shorter wavelengths and sunglint conditions, where the averaged percentage difference (APD) of retrieved AOT is generally reduced by approximate 10 % in visible bands compared with those derived from the standard atmospheric correction (AC) scheme, since 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, atmospheric overcorrection can be avoided in order to have a significant improvement of the inversion of nLw at 412 nm. Furthermore, generally better estimates of band ratios of nLw(443) / nLw(554) and nLw(488) / nLw(554) are obtained using the simultaneous retrieval approach with lower root mean square errors and relative differences than those derived from the standard AC approach in comparison to the AERONET-OC products, as well as the APD values of retrieved Chl which decreased 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 the oceanic bio-optical module of the current model.

A Novel BA Complex Network Model on Color Template Matching

PubMed Central

Han, Risheng; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching. PMID:25243235

A novel BA complex network model on color template matching.

PubMed

Han, Risheng; Shen, Shigen; Yue, Guangxue; Ding, Hui

2014-01-01

A novel BA complex network model of color space is proposed based on two fundamental rules of BA scale-free network model: growth and preferential attachment. The scale-free characteristic of color space is discovered by analyzing evolving process of template's color distribution. And then the template's BA complex network model can be used to select important color pixels which have much larger effects than other color pixels in matching process. The proposed BA complex network model of color space can be easily integrated into many traditional template matching algorithms, such as SSD based matching and SAD based matching. Experiments show the performance of color template matching results can be improved based on the proposed algorithm. To the best of our knowledge, this is the first study about how to model the color space of images using a proper complex network model and apply the complex network model to template matching.

Citrus fruit recognition using color image analysis

NASA Astrophysics Data System (ADS)

Xu, Huirong; Ying, Yibin

2004-10-01

An algorithm for the automatic recognition of citrus fruit on the tree was developed. Citrus fruits have different color with leaves and branches portions. Fifty-three color images with natural citrus-grove scenes were digitized and analyzed for red, green, and blue (RGB) color content. The color characteristics of target surfaces (fruits, leaves, or branches) were extracted using the range of interest (ROI) tool. Several types of contrast color indices were designed and tested. In this study, the fruit image was enhanced using the (R-B) contrast color index because results show that the fruit have the highest color difference among the objects in the image. A dynamic threshold function was derived from this color model and used to distinguish citrus fruit from background. The results show that the algorithm worked well under frontlighting or backlighting condition. However, there are misclassifications when the fruit or the background is under a brighter sunlight.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOEpatents

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

Halftoning and Image Processing Algorithms

DTIC Science & Technology

1999-02-01

screening techniques with the quality advantages of error diffusion in the half toning of color maps, and on color image enhancement for halftone ...image quality. Our goals in this research were to advance the understanding in image science for our new halftone algorithm and to contribute to...image retrieval and noise theory for such imagery. In the field of color halftone printing, research was conducted on deriving a theoretical model of our

Improving color characteristics of LCD

NASA Astrophysics Data System (ADS)

Feng, Xiao-fan; Daly, Scott J.

2005-01-01

The drive for larger size, higher spatial resolution, and wider aperture LCD has shown to increase the electrical crosstalk between electrodes in the driver circuit. This crosstalk leads to additivity errors in color LCD. In this paper, the crosstalk effect was analyzed with micrographs captured from an imaging colorimeter. The experimental result reveals the subpixel nature of color crosstalk. A spatial-based subpixel crosstalk correction algorithm was developed to improve the color performance of LCD. Compared to a 3D lookup table approach, the new algorithm is easier to implement and more accurate in performance.

A novel weighted-direction color interpolation

NASA Astrophysics Data System (ADS)

Tao, Jin-you; Yang, Jianfeng; Xue, Bin; Liang, Xiaofen; Qi, Yong-hong; Wang, Feng

2013-08-01

A digital camera capture images by covering the sensor surface with a color filter array (CFA), only get a color sample at pixel location. Demosaicking is a process by estimating the missing color components of each pixel to get a full resolution image. In this paper, a new algorithm based on edge adaptive and different weighting factors is proposed. Our method can effectively suppress undesirable artifacts. Experimental results based on Kodak images show that the proposed algorithm obtain higher quality images compared to other methods in numerical and visual aspects.

Wavelet Analysis of SAR Images for Coastal Monitoring

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Wu, Sunny Y.; Tseng, William Y.; Pichel, William G.

1998-01-01

The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

Algorithms for Coastal-Zone Color-Scanner Data

NASA Technical Reports Server (NTRS)

1986-01-01

Software for Nimbus-7 Coastal-Zone Color-Scanner (CZCS) derived products consists of set of scientific algorithms for extracting information from CZCS-gathered data. Software uses CZCS-generated Calibrated RadianceTemperature (CRT) tape as input and outputs computer-compatible tape and film product.

How Two Sides of the Atlantic Contributed to Understanding of the Global Oceans: Charles Yentsch and Andre Morel

NASA Technical Reports Server (NTRS)

Acker, James G.

2013-01-01

In a few short days in September of this year, the ocean color/ocean optics community lost two of the founding members of its Hall of FameCharles Yentsch and Andre Morel. Yentsch passed away at the age of 85 on September 19, and Morel passed away on September 23 at the age of 79. It might sound clich to say that someone was instrumental to the advance of science in a particular field, but in the case of Yentsch and Morel and ocean color instrumentation, such an assessment would likely be accurate. Each mans career complimented that of the other Yentsch was one of the first to make measurements of the light field of the ocean from altitude and to advocate an instrument in space that could observe the spectrum of ocean radiance Morels theoretical underpinnings established a firm foundation for the measurements such an instrument could make, allowing their successful interpretation.

Variability of the reflectance coefficient of skylight from the ocean surface and its implications to ocean color.

PubMed

Gilerson, Alexander; Carrizo, Carlos; Foster, Robert; Harmel, Tristan

2018-04-16

The value and spectral dependence of the reflectance coefficient (ρ) of skylight from wind-roughened ocean surfaces is critical for determining accurate water leaving radiance and remote sensing reflectances from shipborne, AERONET-Ocean Color and satellite observations. Using a vector radiative transfer code, spectra of the reflectance coefficient and corresponding radiances near the ocean surface and at the top of the atmosphere (TOA) are simulated for a broad range of parameters including flat and windy ocean surfaces with wind speeds up to 15 m/s, aerosol optical thicknesses of 0-1 at 440nm, wavelengths of 400-900 nm, and variable Sun and viewing zenith angles. Results revealed a profound impact of the aerosol load and type on the spectral values of ρ. Such impacts, not included yet in standard processing, may produce significant inaccuracies in the reflectance spectra retrieved from above-water radiometry and satellite observations. Implications for satellite cal/val activities as well as potential changes in measurement and data processing schemes are discussed.

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Improved algorithms for estimating Total Alkalinity in Northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Devkota, M.; Dash, P.

2017-12-01

Ocean Acidification (OA) is one of the serious challenges that have significant impacts on ocean. About 25% of anthropologically generated CO2 is absorbed by the oceans which decreases average ocean pH. This change has critical impacts on marine species, ocean ecology, and associated economics. 35 years of observation concluded that the rate of alteration in OA parameters varies geographically with higher variations in the northern Gulf of Mexico (N-GoM). Several studies have suggested that the Mississippi River affects the carbon dynamics of the N-GoM coastal ecosystem significantly. Total Alkalinity (TA) algorithms developed for major ocean basins produce inaccurate estimations in this region. Hence, a local algorithm to estimate TA is the need for this region, which would incorporate the local effects of oceanographic processes and complex spatial influences. In situ data collected in N-GoM region during the GOMECC-I and II cruises, and GISR Cruises (G-1, 3, 5) from 2007 to 2013 were assimilated and used to calculate the efficiency of the existing TA algorithm that uses Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) as explanatory variables. To improve this algorithm, firstly, statistical analyses were performed to improve the coefficients and the functional form of this algorithm. Then, chlorophyll a (Chl-a) was included as an additional explanatory variable in the multiple linear regression approach in addition to SST and SSS. Based on the average concentration of Chl-a for last 15 years, the N-GoM was divided into two regions, and two separate algorithms were developed for each region. Finally, to address spatial non-stationarity, a Geographically Weighted Regression (GWR) algorithm was developed. The existing TA algorithm resulted considerable algorithm bias with a larger bias in the coastal waters. Chl-a as an additional explanatory variable reduced the bias in the residuals and improved the algorithm efficiency. Chl-a worked as a proxy for addressing the organic pump's pronounced effects in the coastal waters. The GWR algorithm provided a raster surface of the coefficients with even more reliable algorithms to estimate TA with least error. The GWR algorithm addressed the spatial non-stationarity of OA in N-GoM, which apparently was not addressed in the previously developed algorithms.

Development of a regional ocean color algorithm using field- and satellite-derived datasets: Long Bay, South Carolina

NASA Astrophysics Data System (ADS)

Ryan, Kimberly Susan

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide numerous ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. However, bio and geo-optical models are required that relate the remotely sensed spectral data with color producing agents (CPAs) that define the water quality. These CPAs include chlorophyll-a, suspended sediments, and colored-dissolved organic matter. Developing these models may be challenging for coastal environments such as Long Bay, South Carolina, due to the presence of multiple optically interfering CPAs. In this work, a regionally tiered ocean color model was developed using band ratio techniques to specifically predict the variability of chlorophyll-a concentrations in the turbid Long Bay waters. This model produced higher accuracy results (r-squared = 0.62; RMSE = 0.87 micrograms per liter) compared to the existing models, which gave a highest r-squared value of 0.58 and RMSE = 0.99 micrograms per liter. To further enhance the retrievals of chlorophyll-a in these optically complex waters, a novel multivariate-based approach was developed using current generation hyperspectral data. This approach uses a partial least-squares regression model to identify wavelengths that are more sensitive to chlorophyll-a relative to other associated CPAs. This model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 micrograms per liter. This approach capitalizes on the spectral advantage gained from hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. Moreover, remote sensing applications such as this can be used as a tool for coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

Minimizing systematic errors from atmospheric multiple scattering and satellite viewing geometry in coastal zone color scanner level IIA imagery

NASA Technical Reports Server (NTRS)

Martin, D. L.; Perry, M. J.

1994-01-01

Water-leaving radiances and phytoplankton pigment concentrations are calculated from coastal zone color scanner (CZCS) radiance measurements by removing atmospheric Rayleigh and aerosol radiances from the total radiance signal measured at the satellite. The single greatest source of error in CZCS atmospheric correction algorithms in the assumption that these Rayleigh and aerosol radiances are separable. Multiple-scattering interactions between Rayleigh and aerosol components cause systematic errors in calculated aerosol radiances, and the magnitude of these errors is dependent on aerosol type and optical depth and on satellite viewing geometry. A technique was developed which extends the results of previous radiative transfer modeling by Gordon and Castano to predict the magnitude of these systematic errors for simulated CZCS orbital passes in which the ocean is viewed through a modeled, physically realistic atmosphere. The simulated image mathematically duplicates the exact satellite, Sun, and pixel locations of an actual CZCS image. Errors in the aerosol radiance at 443 nm are calculated for a range of aerosol optical depths. When pixels in the simulated image exceed an error threshhold, the corresponding pixels in the actual CZCS image are flagged and excluded from further analysis or from use in image compositing or compilation of pigment concentration databases. Studies based on time series analyses or compositing of CZCS imagery which do not address Rayleigh-aerosol multiple scattering should be interpreted cautiously, since the fundamental assumption used in their atmospheric correction algorithm is flawed.

Vicarious calibration of the Geostationary Ocean Color Imager.

PubMed

Ahn, Jae-Hyun; Park, Young-Je; Kim, Wonkook; Lee, Boram; Oh, Im Sang

2015-09-07

Measurements of ocean color from Geostationary Ocean Color Imager (GOCI) with a moderate spatial resolution and a high temporal frequency demonstrate high value for a number of oceanographic applications. This study aims to propose and evaluate the calibration of GOCI as needed to achieve the level of radiometric accuracy desired for ocean color studies. Previous studies reported that the GOCI retrievals of normalized water-leaving radiances (nLw) are biased high for all visible bands due to the lack of vicarious calibration. The vicarious calibration approach described here relies on the assumed constant aerosol characteristics over the open-ocean sites to accurately estimate atmospheric radiances for the two near-infrared (NIR) bands. The vicarious calibration of visible bands is performed using in situ nLw measurements and the satellite-estimated atmospheric radiance using two NIR bands over the case-1 waters. Prior to this analysis, the in situ nLw spectra in the NIR are corrected by the spectrum optimization technique based on the NIR similarity spectrum assumption. The vicarious calibration gain factors derived for all GOCI bands (except 865nm) significantly improve agreement in retrieved remote-sensing reflectance (Rrs) relative to in situ measurements. These gain factors are independent of angular geometry and possible temporal variability. To further increase the confidence in the calibration gain factors, a large data set from shipboard measurements and AERONET-OC is used in the validation process. It is shown that the absolute percentage difference of the atmospheric correction results from the vicariously calibrated GOCI system is reduced by ~6.8%.

Web-based visualization of gridded dataset usings OceanBrowser

NASA Astrophysics Data System (ADS)

Barth, Alexander; Watelet, Sylvain; Troupin, Charles; Beckers, Jean-Marie

2015-04-01

OceanBrowser is a web-based visualization tool for gridded oceanographic data sets. Those data sets are typically four-dimensional (longitude, latitude, depth and time). OceanBrowser allows one to visualize horizontal sections at a given depth and time to examine the horizontal distribution of a given variable. It also offers the possibility to display the results on an arbitrary vertical section. To study the evolution of the variable in time, the horizontal and vertical sections can also be animated. Vertical section can be generated by using a fixed distance from coast or fixed ocean depth. The user can customize the plot by changing the color-map, the range of the color-bar, the type of the plot (linearly interpolated color, simple contours, filled contours) and download the current view as a simple image or as Keyhole Markup Language (KML) file for visualization in applications such as Google Earth. The data products can also be accessed as NetCDF files and through OPeNDAP. Third-party layers from a web map service can also be integrated. OceanBrowser is used in the frame of the SeaDataNet project (http://gher-diva.phys.ulg.ac.be/web-vis/) and EMODNET Chemistry (http://oceanbrowser.net/emodnet/) to distribute gridded data sets interpolated from in situ observation using DIVA (Data-Interpolating Variational Analysis).

An optical water type framework for selecting and blending retrievals from bio-optical algorithms in lakes and coastal waters

PubMed Central

Moore, Timothy S.; Dowell, Mark D.; Bradt, Shane; Verdu, Antonio Ruiz

2014-01-01

Bio-optical models are based on relationships between the spectral remote sensing reflectance and optical properties of in-water constituents. The wavelength range where this information can be exploited changes depending on the water characteristics. In low chlorophyll-a waters, the blue/green region of the spectrum is more sensitive to changes in chlorophyll-a concentration, whereas the red/NIR region becomes more important in turbid and/or eutrophic waters. In this work we present an approach to manage the shift from blue/green ratios to red/NIR-based chlorophyll-a algorithms for optically complex waters. Based on a combined in situ data set of coastal and inland waters, measures of overall algorithm uncertainty were roughly equal for two chlorophyll-a algorithms—the standard NASA OC4 algorithm based on blue/green bands and a MERIS 3-band algorithm based on red/NIR bands—with RMS error of 0.416 and 0.437 for each in log chlorophyll-a units, respectively. However, it is clear that each algorithm performs better at different chlorophyll-a ranges. When a blending approach is used based on an optical water type classification, the overall RMS error was reduced to 0.320. Bias and relative error were also reduced when evaluating the blended chlorophyll-a product compared to either of the single algorithm products. As a demonstration for ocean color applications, the algorithm blending approach was applied to MERIS imagery over Lake Erie. We also examined the use of this approach in several coastal marine environments, and examined the long-term frequency of the OWTs to MODIS-Aqua imagery over Lake Erie. PMID:24839311

SST algorithm based on radiative transfer model

NASA Astrophysics Data System (ADS)

Mat Jafri, Mohd Z.; Abdullah, Khiruddin; Bahari, Alui

2001-03-01

An algorithm for measuring sea surface temperature (SST) without recourse to the in-situ data for calibration has been proposed. The algorithm which is based on the recorded infrared signal by the satellite sensor is composed of three terms, namely, the surface emission, the up-welling radiance emitted by the atmosphere, and the down-welling atmospheric radiance reflected at the sea surface. This algorithm requires the transmittance values of thermal bands. The angular dependence of the transmittance function was modeled using the MODTRAN code. Radiosonde data were used with the MODTRAN code. The expression of transmittance as a function of zenith view angle was obtained for each channel through regression of the MODTRAN output. The Ocean Color Temperature Scanner (OCTS) data from the Advanced Earth Observation Satellite (ADEOS) were used in this study. The study area covers the seas of the North West of Peninsular Malaysia region. The in-situ data (ship collected SST values) were used for verification of the results. Cloud contaminated pixels were masked out using the standard procedures which have been applied to the Advanced Very High Resolution Radiometer (AVHRR) data. The cloud free pixels at the in-situ sites were extracted for analysis. The OCTS data were then substituted in the proposed algorithm. The appropriate transmittance value for each channel was then assigned in the calculation. Assessment for the accuracy was made by observing the correlation and the rms deviations between the computed and the ship collected values. The results were also compared with the results from OCTS multi- channel sea surface temperature algorithm. The comparison produced high correlation values. The performance of this algorithm is comparable with the established OCTS algorithm. The effect of emissivity on the retrieved SST values was also investigated. SST map was generated and contoured manually.

Evaluation of the VIIRS Ocean Color Monitoring Performance in Coastal Regions

DTIC Science & Technology

2013-09-17

collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1...part of the VIIRS sensor calibration and validation efforts, our group has been continuously monitoring the validity of the VIlRS’s OC and atmospheric...the necessity for monitoring and assessing the validity and consistency of VIIRS’ ocean color pioducts. especially for coaslal waters. 15. SUBJECT

A Novel Color Image Encryption Algorithm Based on Quantum Chaos Sequence

NASA Astrophysics Data System (ADS)

Liu, Hui; Jin, Cong

2017-03-01

In this paper, a novel algorithm of image encryption based on quantum chaotic is proposed. The keystreams are generated by the two-dimensional logistic map as initial conditions and parameters. And then general Arnold scrambling algorithm with keys is exploited to permute the pixels of color components. In diffusion process, a novel encryption algorithm, folding algorithm, is proposed to modify the value of diffused pixels. In order to get the high randomness and complexity, the two-dimensional logistic map and quantum chaotic map are coupled with nearest-neighboring coupled-map lattices. Theoretical analyses and computer simulations confirm that the proposed algorithm has high level of security.

Joint demosaicking and zooming using moderate spectral correlation and consistent edge map

NASA Astrophysics Data System (ADS)

Zhou, Dengwen; Dong, Weiming; Chen, Wengang

2014-07-01

The recently published joint demosaicking and zooming algorithms for single-sensor digital cameras all overfit the popular Kodak test images, which have been found to have higher spectral correlation than typical color images. Their performance perhaps significantly degrades on other datasets, such as the McMaster test images, which have weak spectral correlation. A new joint demosaicking and zooming algorithm is proposed for the Bayer color filter array (CFA) pattern, in which the edge direction information (edge map) extracted from the raw CFA data is consistently used in demosaicking and zooming. It also moderately utilizes the spectral correlation between color planes. The experimental results confirm that the proposed algorithm produces an excellent performance on both the Kodak and McMaster datasets in terms of both subjective and objective measures. Our algorithm also has high computational efficiency. It provides a better tradeoff among adaptability, performance, and computational cost compared to the existing algorithms.

On the use of Schwarz-Christoffel conformal mappings to the grid generation for global ocean models

NASA Astrophysics Data System (ADS)

Xu, S.; Wang, B.; Liu, J.

2015-02-01

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present.

Utilizing typical color appearance models to represent perceptual brightness and colorfulness for digital images

NASA Astrophysics Data System (ADS)

Gong, Rui; Wang, Qing; Shao, Xiaopeng; Zhou, Conghao

2016-12-01

This study aims to expand the applications of color appearance models to representing the perceptual attributes for digital images, which supplies more accurate methods for predicting image brightness and image colorfulness. Two typical models, i.e., the CIELAB model and the CIECAM02, were involved in developing algorithms to predict brightness and colorfulness for various images, in which three methods were designed to handle pixels of different color contents. Moreover, massive visual data were collected from psychophysical experiments on two mobile displays under three lighting conditions to analyze the characteristics of visual perception on these two attributes and to test the prediction accuracy of each algorithm. Afterward, detailed analyses revealed that image brightness and image colorfulness were predicted well by calculating the CIECAM02 parameters of lightness and chroma; thus, the suitable methods for dealing with different color pixels were determined for image brightness and image colorfulness, respectively. This study supplies an example of enlarging color appearance models to describe image perception.

Single Channel Quantum Color Image Encryption Algorithm Based on HSI Model and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Gong, Li-Hua; He, Xiang-Tao; Tan, Ru-Chao; Zhou, Zhi-Hong

2018-01-01

In order to obtain high-quality color images, it is important to keep the hue component unchanged while emphasize the intensity or saturation component. As a public color model, Hue-Saturation Intensity (HSI) model is commonly used in image processing. A new single channel quantum color image encryption algorithm based on HSI model and quantum Fourier transform (QFT) is investigated, where the color components of the original color image are converted to HSI and the logistic map is employed to diffuse the relationship of pixels in color components. Subsequently, quantum Fourier transform is exploited to fulfill the encryption. The cipher-text is a combination of a gray image and a phase matrix. Simulations and theoretical analyses demonstrate that the proposed single channel quantum color image encryption scheme based on the HSI model and quantum Fourier transform is secure and effective.

The VIIRS Ocean Data Simulator Enhancements and Results

NASA Technical Reports Server (NTRS)

Robinson, Wayne D.; Patt, Fredrick S.; Franz, Bryan A.; Turpie, Kevin R.; McClain, Charles R.

2011-01-01

The VIIRS Ocean Science Team (VOST) has been developing an Ocean Data Simulator to create realistic VIIRS SDR datasets based on MODIS water-leaving radiances. The simulator is helping to assess instrument performance and scientific processing algorithms. Several changes were made in the last two years to complete the simulator and broaden its usefulness. The simulator is now fully functional and includes all sensor characteristics measured during prelaunch testing, including electronic and optical crosstalk influences, polarization sensitivity, and relative spectral response. Also included is the simulation of cloud and land radiances to make more realistic data sets and to understand their important influence on nearby ocean color data. The atmospheric tables used in the processing, including aerosol and Rayleigh reflectance coefficients, have been modeled using VIIRS relative spectral responses. The capabilities of the simulator were expanded to work in an unaggregated sample mode and to produce scans with additional samples beyond the standard scan. These features improve the capability to realistically add artifacts which act upon individual instrument samples prior to aggregation and which may originate from beyond the actual scan boundaries. The simulator was expanded to simulate all 16 M-bands and the EDR processing was improved to use these bands to make an SST product. The simulator is being used to generate global VIIRS data from and in parallel with the MODIS Aqua data stream. Studies have been conducted using the simulator to investigate the impact of instrument artifacts. This paper discusses the simulator improvements and results from the artifact impact studies.

The VIIRS ocean data simulator enhancements and results

NASA Astrophysics Data System (ADS)

Robinson, Wayne D.; Patt, Frederick S.; Franz, Bryan A.; Turpie, Kevin R.; McClain, Charles R.

2011-10-01

The VIIRS Ocean Science Team (VOST) has been developing an Ocean Data Simulator to create realistic VIIRS SDR datasets based on MODIS water-leaving radiances. The simulator is helping to assess instrument performance and scientific processing algorithms. Several changes were made in the last two years to complete the simulator and broaden its usefulness. The simulator is now fully functional and includes all sensor characteristics measured during prelaunch testing, including electronic and optical crosstalk influences, polarization sensitivity, and relative spectral response. Also included is the simulation of cloud and land radiances to make more realistic data sets and to understand their important influence on nearby ocean color data. The atmospheric tables used in the processing, including aerosol and Rayleigh reflectance coefficients, have been modeled using VIIRS relative spectral responses. The capabilities of the simulator were expanded to work in an unaggregated sample mode and to produce scans with additional samples beyond the standard scan. These features improve the capability to realistically add artifacts which act upon individual instrument samples prior to aggregation and which may originate from beyond the actual scan boundaries. The simulator was expanded to simulate all 16 M-bands and the EDR processing was improved to use these bands to make an SST product. The simulator is being used to generate global VIIRS data from and in parallel with the MODIS Aqua data stream. Studies have been conducted using the simulator to investigate the impact of instrument artifacts. This paper discusses the simulator improvements and results from the artifact impact studies.

A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon-Ocean Feedback in Typhoon Forecast Models

NASA Astrophysics Data System (ADS)

Jiang, Guo-Qing; Xu, Jing; Wei, Jun

2018-04-01

Two algorithms based on machine learning neural networks are proposed—the shallow learning (S-L) and deep learning (D-L) algorithms—that can potentially be used in atmosphere-only typhoon forecast models to provide flow-dependent typhoon-induced sea surface temperature cooling (SSTC) for improving typhoon predictions. The major challenge of existing SSTC algorithms in forecast models is how to accurately predict SSTC induced by an upcoming typhoon, which requires information not only from historical data but more importantly also from the target typhoon itself. The S-L algorithm composes of a single layer of neurons with mixed atmospheric and oceanic factors. Such a structure is found to be unable to represent correctly the physical typhoon-ocean interaction. It tends to produce an unstable SSTC distribution, for which any perturbations may lead to changes in both SSTC pattern and strength. The D-L algorithm extends the neural network to a 4 × 5 neuron matrix with atmospheric and oceanic factors being separated in different layers of neurons, so that the machine learning can determine the roles of atmospheric and oceanic factors in shaping the SSTC. Therefore, it produces a stable crescent-shaped SSTC distribution, with its large-scale pattern determined mainly by atmospheric factors (e.g., winds) and small-scale features by oceanic factors (e.g., eddies). Sensitivity experiments reveal that the D-L algorithms improve maximum wind intensity errors by 60-70% for four case study simulations, compared to their atmosphere-only model runs.

Estimating the beam attenuation coefficient in coastal waters from AVHRR imagery

NASA Astrophysics Data System (ADS)

Gould, Richard W.; Arnone, Robert A.

1997-09-01

This paper presents an algorithm to estimate particle beam attenuation at 660 nm ( cp660) in coastal areas using the red and near-infrared channels of the NOAA AVHRR satellite sensor. In situ reflectance spectra and cp660 measurements were collected at 23 stations in Case I and II waters during an April 1993 cruise in the northern Gulf of Mexico. The reflectance spectra were weighted by the spectral response of the AVHRR sensor and integrated over the channel 1 waveband to estimate the atmospherically corrected signal recorded by the satellite. An empirical relationship between integrated reflectance and cp660 values was derived with a linear correlation coefficient of 0.88. Because the AVHRR sensor requires a strong channel 1 signal, the algorithm is applicable in highly turbid areas ( cp660 > 1.5 m -1) where scattering from suspended sediment strongly controls the shape and magnitude of the red (550-650 nm) reflectance spectrum. The algorithm was tested on a data set collected 2 years later in different coastal waters in the northern Gulf of Mexico and satellite estimates of cp660 averaged within 37% of measured values. Application of the algorithm provides daily images of nearshore regions at 1 km resolution for evaluating processes affecting ocean color distribution patterns (tides, winds, currents, river discharge). Further validation and refinement of the algorithm are in progress to permit quantitative application in other coastal areas. Published by Elsevier Science Ltd

Color segmentation in the HSI color space using the K-means algorithm

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.

OSCAT Eyes Hurricane Sandy

NASA Image and Video Library

2012-10-30

This image shows ocean surface winds for Hurricane Sandy observed by the OSCAT radar scatterometer on the Indian Space Research Organization ISRO OceanSat-2 satellite. Colors indicate wind speed and arrows indicate direction.

Performance of the JPEG Estimated Spectrum Adaptive Postfilter (JPEG-ESAP) for Low Bit Rates

NASA Technical Reports Server (NTRS)

Linares, Irving (Inventor)

2016-01-01

Frequency-based, pixel-adaptive filtering using the JPEG-ESAP algorithm for low bit rate JPEG formatted color images may allow for more compressed images while maintaining equivalent quality at a smaller file size or bitrate. For RGB, an image is decomposed into three color bands--red, green, and blue. The JPEG-ESAP algorithm is then applied to each band (e.g., once for red, once for green, and once for blue) and the output of each application of the algorithm is rebuilt as a single color image. The ESAP algorithm may be repeatedly applied to MPEG-2 video frames to reduce their bit rate by a factor of 2 or 3, while maintaining equivalent video quality, both perceptually, and objectively, as recorded in the computed PSNR values.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using amore » combinatorial algorithm.« less

Enriching text with images and colored light

NASA Astrophysics Data System (ADS)

Sekulovski, Dragan; Geleijnse, Gijs; Kater, Bram; Korst, Jan; Pauws, Steffen; Clout, Ramon

2008-01-01

We present an unsupervised method to enrich textual applications with relevant images and colors. The images are collected by querying large image repositories and subsequently the colors are computed using image processing. A prototype system based on this method is presented where the method is applied to song lyrics. In combination with a lyrics synchronization algorithm the system produces a rich multimedia experience. In order to identify terms within the text that may be associated with images and colors, we select noun phrases using a part of speech tagger. Large image repositories are queried with these terms. Per term representative colors are extracted using the collected images. Hereto, we either use a histogram-based or a mean shift-based algorithm. The representative color extraction uses the non-uniform distribution of the colors found in the large repositories. The images that are ranked best by the search engine are displayed on a screen, while the extracted representative colors are rendered on controllable lighting devices in the living room. We evaluate our method by comparing the computed colors to standard color representations of a set of English color terms. A second evaluation focuses on the distance in color between a queried term in English and its translation in a foreign language. Based on results from three sets of terms, a measure of suitability of a term for color extraction based on KL Divergence is proposed. Finally, we compare the performance of the algorithm using either the automatically indexed repository of Google Images and the manually annotated Flickr.com. Based on the results of these experiments, we conclude that using the presented method we can compute the relevant color for a term using a large image repository and image processing.

Clustering of color map pixels: an interactive approach

NASA Astrophysics Data System (ADS)

Moon, Yiu Sang; Luk, Franklin T.; Yuen, K. N.; Yeung, Hoi Wo

2003-12-01

The demand for digital maps continues to arise as mobile electronic devices become more popular nowadays. Instead of creating the entire map from void, we may convert a scanned paper map into a digital one. Color clustering is the very first step of the conversion process. Currently, most of the existing clustering algorithms are fully automatic. They are fast and efficient but may not work well in map conversion because of the numerous ambiguous issues associated with printed maps. Here we introduce two interactive approaches for color clustering on the map: color clustering with pre-calculated index colors (PCIC) and color clustering with pre-calculated color ranges (PCCR). We also introduce a memory model that could enhance and integrate different image processing techniques for fine-tuning the clustering results. Problems and examples of the algorithms are discussed in the paper.

Evaluation of Ocean Color Scanner (OCS) photographic and digital data: Santa Barbara Channel test site, 29 October 1975 overflight

NASA Technical Reports Server (NTRS)

Kraus, S. P.; Estes, J. E.; Kronenberg, M. R.; Hajic, E. J.

1977-01-01

A summary of Ocean Color Scanner data was examined to evaluate detection and discrimination capabilities of the system for marine resources, oil pollution and man-made sea surface targets of opportunity in the Santa Barbara Channel. Assessment of the utility of OCS for the determination of sediment transport patterns along the coastal zone was a secondary goal. Data products provided 1975 overflight were in digital and analog formats. In evaluating the OCS data, automated and manual procedures were employed. A total of four channels of data in digital format were analyzed, as well as three channels of color combined imagery, and four channels of black and white imagery. In addition, 1:120,000 scale color infrared imagery acquired simultaneously with the OCS data were provided for comparative analysis purposes.

A robust embedded vision system feasible white balance algorithm

NASA Astrophysics Data System (ADS)

Wang, Yuan; Yu, Feihong

2018-01-01

White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.

Effects of Raman scattering on the water-leaving radiance

NASA Technical Reports Server (NTRS)

Waters, Kirk J.

1995-01-01

The contribution of Raman scattering to the water-leaving radiance is examined using Monte Carlo simulations. Exit angle information is retained, allowing a comparison of different satellite viewing directions. Chlorophyll values of 0.0, 0.01, 0.1, and 1.0 mg Chl/cu m are simulated. Little directional variability is found, with the exception of the direct solar backscatter direction. The wavelength variability is greatest for low chlorophyll concentrations and is negligible for 1.0 mg Chl/cu m. At 550 nm the Raman contribution ranges from approximately 18% of the total water-leaving radiance for pure water to 3% for 1.0 mg Chl/cu m. At 440 nm the range is from 6% to 2%, indicating that Raman scattering will impact radiance ratios for ocean color satellite algorithms.

Analysis of high altitude remotely sensed data collected in the Nantucket Shoals experiment 4-15 May, 1981

NASA Technical Reports Server (NTRS)

Ohlhorst, C. W.

1982-01-01

High altitude ocean color scanner ratios of band 2 (456 to 476 nanometers) to band 4 (539 to 559 nanometers) and band 1 (418 to 438 nanometers) to band 3 (498 to 518 nanometers) had high correlation coefficient values (-0.928 and 0.891 respectively) with seven boat sampled chlorophyll a measurements. The range of chlorophyll a concentrations was small (1.7-2.58 mg/cu m.). Each ratio was used to calculate chlorophyll a values for the center pixel of each scan line on flight lines 5 and 6. The two ratios produced dissimilar chlorophyll a trends. Due to the high noise level in the scanner data, no reliable synoptic chlorophyll a map could be generated with either ratio algorithm.

A new fringeline-tracking approach for color Doppler ultrasound imaging phase unwrapping

NASA Astrophysics Data System (ADS)

Saad, Ashraf A.; Shapiro, Linda G.

2008-03-01

Color Doppler ultrasound imaging is a powerful non-invasive diagnostic tool for many clinical applications that involve examining the anatomy and hemodynamics of human blood vessels. These clinical applications include cardio-vascular diseases, obstetrics, and abdominal diseases. Since its commercial introduction in the early eighties, color Doppler ultrasound imaging has been used mainly as a qualitative tool with very little attempts to quantify its images. Many imaging artifacts hinder the quantification of the color Doppler images, the most important of which is the aliasing artifact that distorts the blood flow velocities measured by the color Doppler technique. In this work we will address the color Doppler aliasing problem and present a recovery methodology for the true flow velocities from the aliased ones. The problem is formulated as a 2D phase-unwrapping problem, which is a well-defined problem with solid theoretical foundations for other imaging domains, including synthetic aperture radar and magnetic resonance imaging. This paper documents the need for a phase unwrapping algorithm for use in color Doppler ultrasound image analysis. It describes a new phase-unwrapping algorithm that relies on the recently developed cutline detection approaches. The algorithm is novel in its use of heuristic information provided by the ultrasound imaging modality to guide the phase unwrapping process. Experiments have been performed on both in-vitro flow-phantom data and in-vivo human blood flow data. Both data types were acquired under a controlled acquisition protocol developed to minimize the distortion of the color Doppler data and hence to simplify the phase-unwrapping task. In addition to the qualitative assessment of the results, a quantitative assessment approach was developed to measure the success of the results. The results of our new algorithm have been compared on ultrasound data to those from other well-known algorithms, and it outperforms all of them.

Validation of Ocean Color Satellite Data Products in Under Sampled Marine Areas. Chapter 6

NASA Technical Reports Server (NTRS)

Subramaniam, Ajit; Hood, Raleigh R.; Brown, Christopher W.; Carpenter, Edward J.; Capone, Douglas G.

2001-01-01

The planktonic marine cyanobacterium, Trichodesmium sp., is broadly distributed throughout the oligotrophic marine tropical and sub-tropical oceans. Trichodesmium, which typically occurs in macroscopic bundles or colonies, is noteworthy for its ability to form large surface aggregations and to fix dinitrogen gas. The latter is important because primary production supported by N2 fixation can result in a net export of carbon from the surface waters to deep ocean and may therefore play a significant role in the global carbon cycle. However, information on the distribution and density of Trichodesmium from shipboard measurements through the oligotrophic oceans is very sparse. Such estimates are required to quantitatively estimate total global rates of N2 fixation. As a result current global rate estimates are highly uncertain. Thus in order to understand the broader biogeochemical importance of Trichodesmium and N2 fixation in the oceans, we need better methods to estimate the global temporal and spatial variability of this organism. One approach that holds great promise is satellite remote sensing. Satellite ocean color sensors are ideal instruments for estimating global phytoplankton biomass, especially that due to episodic blooms, because they provide relatively high frequency synoptic information over large areas. Trichodesmium has a combination of specific ultrastructural and biochemical features that lend themselves to identification of this organism by remote sensing. Specifically, these features are high backscatter due to the presence of gas vesicles, and absorption and fluorescence of phycoerythrin. The resulting optical signature is relatively unique and should be detectable with satellite ocean color sensors such as the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS).

A novel color image encryption algorithm based on genetic recombination and the four-dimensional memristive hyperchaotic system

NASA Astrophysics Data System (ADS)

Chai, Xiu-Li; Gan, Zhi-Hua; Lu, Yang; Zhang, Miao-Hui; Chen, Yi-Ran

2016-10-01

Recently, many image encryption algorithms based on chaos have been proposed. Most of the previous algorithms encrypt components R, G, and B of color images independently and neglect the high correlation between them. In the paper, a novel color image encryption algorithm is introduced. The 24 bit planes of components R, G, and B of the color plain image are obtained and recombined into 4 compound bit planes, and this can make the three components affect each other. A four-dimensional (4D) memristive hyperchaotic system generates the pseudorandom key streams and its initial values come from the SHA 256 hash value of the color plain image. The compound bit planes and key streams are confused according to the principles of genetic recombination, then confusion and diffusion as a union are applied to the bit planes, and the color cipher image is obtained. Experimental results and security analyses demonstrate that the proposed algorithm is secure and effective so that it may be adopted for secure communication. Project supported by the National Natural Science Foundation of China (Grant Nos. 61203094 and 61305042), the Natural Science Foundation of the United States (Grant Nos. CNS-1253424 and ECCS-1202225), the Science and Technology Foundation of Henan Province, China (Grant No. 152102210048), the Foundation and Frontier Project of Henan Province, China (Grant No. 162300410196), the Natural Science Foundation of Educational Committee of Henan Province, China (Grant No. 14A413015), and the Research Foundation of Henan University, China (Grant No. xxjc20140006).

Light response of phytoplankton in the South Atlantic Ocean: Interpretation of observations and application to remote sensing

NASA Technical Reports Server (NTRS)

Hood, Raleigh R.

1995-01-01

A simplified, nonspectral derivation of a classical theory in plant physiology is presented and used to derive an absorption-based primary productivity algorithm. Field observations from a meridional transect (4 deg N to 42 deg S) in the Atlantic Ocean are then described and interpreted in this theoretical context. The observations include photosynthesis-irradiance curve parameters (alpha and P(sub max)), chlorophyll a and phaeopigment concentration, and estimated phytoplankton absorption coefficients at wavelength = 440 nm (a(sub ph)(440)). Observations near the top (50% I(sub 0)) and bottom (6% I(sub 0)) of the euphotic zone are contrasted. At both light levels, alpha, P(sub max), a(sub ph)(440), and pigment concentration varied similarly along the transect: values were highest at the equator and at the southern end of the transect and lowest in the central South Atlantic. It is concluded that this pattern was related to increased nutrient availability due to equatorial upwelling in the north, and increased wind mixing in the south. At the 50% light level, alpha increased relative to a(sub ph) at the southern end of the transect. This result appears to reflect a large-scale meridional (southward) increase in the average quantum efficiency of the photosynthetic units of the phytoplankton. A correlation analysis of the data reveals that at the 50% light level, variations in P(sub max) were more closely related to a(sub ph)(440) than chlorophyll concentration and that phytoplankton absorption explains 90% of the variability in P(sub max). In theory, this shows that the ratio of the average quantum efficiency of the photosynthetic units of the phytoplankton to the product of their average absorption cross section and turnover time is relatively constant. This result is used to simplify the absorption-based primary productivity algorithm derived previously. The feasibility of using this model to estimate production rate from satellite ocean color observations is discussed. It is concluded that an absorption-based algorithm should provide more accurate production rate estimates than one based upon chlorophyll (pigment) concentration.

Single-scale center-surround Retinex based restoration of low-illumination images with edge enhancement

NASA Astrophysics Data System (ADS)

Kwok, Ngaiming; Shi, Haiyan; Peng, Yeping; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Rahman, Md Arifur

2018-04-01

Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modifid as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.

Toward a multivariate reanalysis of the North Atlantic ocean biogeochemistry during 1998-2006 based on the assimilation of SeaWiFS chlorophyll data

NASA Astrophysics Data System (ADS)

Fontana, C.; Brasseur, P.; Brankart, J.-M.

2012-04-01

Today, the routine assimilation of satellite data into operational models of the ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "reanalysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale three-dimensional coupled physical-biogeochemical model of the North-Atlantic. The aim is on one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical-biogeochemical modelling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9 year-long period. In this frame, two experiences are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, the nitrate World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface chlorophyll concentrations analysis and forecast, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related litterature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentration deeper than 50 m. The assessement of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalysing the ocean biogeochemistry based on ocean color data.

Toward a multivariate reanalysis of the North Atlantic Ocean biogeochemistry during 1998-2006 based on the assimilation of SeaWiFS chlorophyll data

NASA Astrophysics Data System (ADS)

Fontana, C.; Brasseur, P.; Brankart, J.-M.

2013-01-01

Today, the routine assimilation of satellite data into operational models of ocean circulation is mature enough to enable the production of global reanalyses describing the ocean circulation variability during the past decades. The expansion of the "reanalysis" concept from ocean physics to biogeochemistry is a timely challenge that motivates the present study. The objective of this paper is to investigate the potential benefits of assimilating satellite-estimated chlorophyll data into a basin-scale three-dimensional coupled physical-biogeochemical model of the North Atlantic. The aim is on the one hand to improve forecasts of ocean biogeochemical properties and on the other hand to define a methodology for producing data-driven climatologies based on coupled physical-biogeochemical modeling. A simplified variant of the Kalman filter is used to assimilate ocean color data during a 9-year period. In this frame, two experiments are carried out, with and without anamorphic transformations of the state vector variables. Data assimilation efficiency is assessed with respect to the assimilated data set, nitrate of the World Ocean Atlas database and a derived climatology. Along the simulation period, the non-linear assimilation scheme clearly improves the surface analysis and forecast chlorophyll concentrations, especially in the North Atlantic bloom region. Nitrate concentration forecasts are also improved thanks to the assimilation of ocean color data while this improvement is limited to the upper layer of the water column, in agreement with recent related literature. This feature is explained by the weak correlation taken into account by the assimilation between surface phytoplankton and nitrate concentrations deeper than 50 meters. The assessment of the non-linear assimilation experiments indicates that the proposed methodology provides the skeleton of an assimilative system suitable for reanalyzing the ocean biogeochemistry based on ocean color data.

Modifications to Improve Data Acquisition and Analysis for Camouflage Design

DTIC Science & Technology

1983-01-01

terrains into facsimiles of the original scenes in 3, 4# or 5 colors in CIELAB notation. Tasks that were addressed included optimization of the...a histogram algorithm (HIST) was used as a first step In the clustering of the CIELAB values of the scene pixels. This algorithm Is highly efficient...however, an optimal process and the CIELAB coordinates of the final color domains can be Influenced by the color coordinate Increments used In the

Development of an acquisition protocol and a segmentation algortihm for wounds of cutaneous Leishmaniasis in digital images

NASA Astrophysics Data System (ADS)

Diaz, Kristians; Castañeda, Benjamín; Miranda, César; Lavarello, Roberto; Llanos, Alejandro

2010-03-01

We developed a protocol for the acquisition of digital images and an algorithm for a color-based automatic segmentation of cutaneous lesions of Leishmaniasis. The protocol for image acquisition provides control over the working environment to manipulate brightness, lighting and undesirable shadows on the injury using indirect lighting. Also, this protocol was used to accurately calculate the area of the lesion expressed in mm2 even in curved surfaces by combining the information from two consecutive images. Different color spaces were analyzed and compared using ROC curves in order to determine the color layer with the highest contrast between the background and the wound. The proposed algorithm is composed of three stages: (1) Location of the wound determined by threshold and mathematical morphology techniques to the H layer of the HSV color space, (2) Determination of the boundaries of the wound by analyzing the color characteristics in the YIQ space based on masks (for the wound and the background) estimated from the first stage, and (3) Refinement of the calculations obtained on the previous stages by using the discrete dynamic contours algorithm. The segmented regions obtained with the algorithm were compared with manual segmentations made by a medical specialist. Broadly speaking, our results support that color provides useful information during segmentation and measurement of wounds of cutaneous Leishmaniasis. Results from ten images showed 99% specificity, 89% sensitivity, and 98% accuracy.

Case studies of aerosol and ocean color retrieval using a Markov chain radiative transfer model and AirMSPI measurements

NASA Astrophysics Data System (ADS)

Xu, F.; Diner, D. J.; Seidel, F. C.; Dubovik, O.; Zhai, P.

2014-12-01

A vector Markov chain radiative transfer method was developed for forward modeling of radiance and polarization fields in a coupled atmosphere-ocean system. The method was benchmarked against an independent Successive Orders of Scattering code and linearized through the use of Jacobians. Incorporated with the multi-patch optimization algorithm and look-up-table method, simultaneous aerosol and ocean color retrievals were performed using imagery acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) when it was operated in step-and-stare mode with 9 viewing angles ranging between ±67°. Data from channels near 355, 380, 445, 470*, 555, 660*, and 865* nm were used in the retrievals, where the asterisk denotes the polarimetric bands. Retrievals were run for AirMSPI overflights over Southern California and Monterey Bay, CA. For the relatively high aerosol optical depth (AOD) case (~0.28 at 550 nm), the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration were compared to those reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California on 6 February 2013. For the relatively low AOD case (~0.08 at 550 nm), the retrieved aerosol concentration and size distribution were compared to those reported by the Monterey Bay AERONET site on 28 April 2014. Further, we evaluate the benefits of multi-angle and polarimetric observations by performing the retrievals using (a) all view angles and channels; (b) all view angles but radiances only (no polarization); (c) the nadir view angle only with both radiance and polarization; and (d) the nadir view angle without polarization. Optimized retrievals using different initial guesses were performed to provide a measure of retrieval uncertainty. Removal of multi-angular or polarimetric information resulted in increases in both parameter uncertainty and systematic bias. Potential accuracy improvements afforded by applying constraints on the surface and aerosol parametric models will also be discussed.