Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Color”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Space Environmental Effects on Colored Coatings and Anodizes

Colored coatings and anodizes are used on spacecraft as markers and astronaut visual aids. These materials must be stable in the space environment and withstand atomic oxygen, ultraviolet radiation, particulate radiation, thermal cycling, and high vacuum without significant change in optical and mechanical properties. A variety of colored coatings and anodizes have been exposed to simulated space environments at Marshall Space Flight Center and also actual space environment as part of the Passive Optical Sample Assembly (POSA) - I flight experiment. Colored coatings were developed by AZ Technology, Huntsville, AL, under a NASA contract for International Space Station (ISS). These include yellow, red, blue, and black paints suitable for Extra-Vehicular Activity (EVA) visual aids and ISS emblems. AaChron, Inc., Minneapolis, MN, developed stable colored anodizes, also in yellow, red, blue, and black, for astronaut visual aids. These coatings were exposed in the laboratory to approximately 550 equivalent sun-hours of solar ultraviolet radiation and approximately 1 x 10(exp 21) atoms/sq cm of atomic oxygen in vacuum. The AZ Technology yellow colored coating, designated TMS800IY, and all four AaChron colored anodizes were flown on POSA-I. POSA-I was a Risk Mitigation Experiment for ISS. It was attached to the exterior of the Mir space station docking module by EVA and was exposed for 18 months. The laboratory-simulated space environment, the natural space environment and the unique environment of an orbiting, active space station and their effects on these developmental materials are discussed.

Kamenetzky, Rachel R.↗
NASA NTRS2001

Satellite Ocean Color: Present Status, Future Challenges

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.

Gregg, Watson W.↗
NASA NTRS2001

Spectral Data Assimilation for Merging Satellite Ocean Color Imagery

The Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) project was initiated 'to develop a methodology and operational capability to combine data products from various ocean color missions in a manner that ensures the best possible global coverage and best exploits the complementary missions of the sensors'. While the merging of data from multiple sources has already been implemented for sea surface temperature (SST), altimetry or clouds, this is a new topic in ocean color science. Merging ocean color data has obvious advantage in terms of spatial and temporal coverage of the global ocean but data merging should also result in new, more diverse and improved data products with lower uncertainties. The merging of ocean color satellite data is generally considered at the level of the global gridded products, i.e., NASA Level-3 and, more specifically, for the merging of chlorophyll a concentration data, [Ch1]. This approach limits computational issues and deals with a unique, simple quantity, [Ch1]. However, ocean color data merging can also be conducted at the level of water-leaving radiances, LwN(lamda), using either empirical or semi-analytical algorithms. Although more challenging, this latter approach is potentially extremely powerful as it can achieve good consistency in the final data products and can take advantage of both the specificities and differences of each source of data. The demonstration of the feasibility of such approach is the main objective of our SIMBIOS work. Here, we use a semi-analytical algorithm to merge Rrs (or, equivalently LwN) data from different sources to estimate [Ch1]. The model also allows for the retrieval of other quantities such as the combined absorption of colored detrital particulate and dissolved organic matter at 443 nm, a(sub cdm)(443) and the particulate backscattering, b(sub bp)(443).

Siegel, David A.↗
NASA NTRS2010

Single sensor processing to obtain high resolution color component signals

A method for generating color video signals representative of color images of a scene includes the following steps: focusing light from the scene on an electronic image sensor via a filter having a tri-color filter pattern; producing, from outputs of the sensor, first and second relatively low resolution luminance signals; producing, from outputs of the sensor, a relatively high resolution luminance signal; producing, from a ratio of the relatively high resolution luminance signal to the first relatively low resolution luminance signal, a high band luminance component signal; producing, from outputs of the sensor, relatively low resolution color component signals; and combining each of the relatively low resolution color component signals with the high band luminance component signal to obtain relatively high resolution color component signals.

Glenn, William E.↗
NASA NTRS2012

Single Lens Dual-Aperture 3D Imaging System: Color Modeling

In an effort to miniaturize a 3D imaging system, we created two viewpoints in a single objective lens camera. This was accomplished by placing a pair of Complementary Multi-band Bandpass Filters (CMBFs) in the aperture area. Two key characteristics about the CMBFs are that the passbands are staggered so only one viewpoint is opened at a time when a light band matched to that passband is illuminated, and the passbands are positioned throughout the visible spectrum, so each viewpoint can render color by taking RGB spectral images. Each viewpoint takes a different spectral image from the other viewpoint hence yielding a different color image relative to the other. This color mismatch in the two viewpoints could lead to color rivalry, where the human vision system fails to resolve two different colors. The difference will be closer if the number of passbands in a CMBF increases. (However, the number of passbands is constrained by cost and fabrication technique.) In this paper, simulation predicting the color mismatch is reported.

bipartite filter↗
NASA NTRS2018

Hawkeye Ocean Color Instrument – Performance Summary

Hawkeye is an ocean color instrument that is part of the SeaHawk satellite developed for SOCON, the Sustained Ocean Color Observations using Nanosatellites program funded by the Gordon and Betty Moore Foundation and managed by the University of North Carolina – Wilmington (UNC-W). HawkEye has spectral characteristics similar to SeaWiFS, but with 8 times finer resolution and a smaller field of view more appropriate for lakes, rivers, and near-shore terrestrial environments. With a volume of only 10 X 10 X 10 cm (a CubeSat 1U), it can produce 8 bands of image data in a single pass, each with 1800 x 6000 pixels, with a resolution of 120 meters per pixel. This paper will present a short summary of instrument design, the spacecraft interface, and “lessons learned” during this effort. Scientists considering using linear arrays in a pushbroom mode for remote sensing will find this useful. Much of the discussion will center on optical performance, such as flat field calibration, polarization effects, stray light, out-of-band response, and exposure linearity. Images from field tests will be shown.The Hawkeye instrument is an ocean color measuring instrument designed to fly on the SeaHawk satellite developed for SOCON, the Sustained Ocean Color Observations using Nanosatellites program funded by the Gordon and Betty Moore Foundation and managed by the University of North Carolina – Wilmington (UNC-W). The Hawkeye instrument measures ocean color in 8 spectral bands, similar to SeaWiFS, except Band 7, which is shifted to a slightly lower wavelength to avoid the oxygen absorption feature that a wider band overlapped on SeaWiFS. The instrument is approximately 1/3rd the volume of the entire satellite, which is a 3U Cubesat manufactured by Clydespace in Glasgow, Scotland. The purpose of this instrument is to ascertain the quality of ocean color data possible with such a small, inexpensive instrument and bus. The nominal orbit is 540 km, and the nominal pixel geometric instantaneous field of view (GIFOV) 120 meters on a side. Each band will produce an image 1800 x 6000 pixels in size, for a total field of view of 216 X 720 km.2) DESIGN CONCEPTThe Hawkeye instrument uses linear arrays in pushbroom mode to collect data over a two dimensional area. The instrument has 4 linear CCD arrays, the Onsemi KLI-4104, to collect the 8 bands of data. Figure 1 illustrates the optical design for two bands, sharing a single array.

Hawkeye↗
NASA NTRS2019

Using Graph Coloring to Compute Total Derivatives More Efficiently in OpenMDAO

When they are applicable, gradient based optimization algorithms are the most efficient way to solve design optimization problems. Although gradient based methods are generally efficient, they can be made significantly more so through the usage of analytic techniques to compute the necessary total derivatives. The traditional forward (direct) and reverse (adjoint) analytic techniques have computational costs that scale linearly with the number of design variables and the number of constraints, respectively. In this work, we present an application of a graph coloring algorithm to the analytic techniques for computing total derivative Jacobians in order to achieve much better computational scaling than the pure analytic methods can provide alone. A detailed theoretical explanation of how coloring algorithms interact with analytic derivative methods is presented that illustrates specific types of sparsity patterns that must be present in total derivative Jacobians in order for this coloring technique to be effective. The new technique has been implemented as a feature in the OpenMDAO framework and the implementation is demonstrated on two example problems. The performance on the example problems up to 50% reduction in compute cost for optimizations with bi-directional coloring compared to traditional constraint aggregation. Additionally, the results show how coloring technique alleviates some of the numerical difficulties that constraint aggregation can cause, leading to the ability to solve larger problems. It is expected that the new method will have wide applicability to multidisciplinary optimization problems, and that its availability in OpenMDAO will offer significant computational savings for users without the need for them to implement the coloring algorithm themselves.

Trajectory↗
NASA NTRSDate not supplied

An Intercomparison of High Spectral Resolution Lidar and Satellite Ocean Color Backscatter Retrievals

We present an intercomparison of satellite ocean color and high spectral resolution lidar (HSRL) retrievals of upper ocean particulate backscattering (bbp) and diffuse attenuation coefficients (Kd). Ocean retrievals of bbp and Kd have been performed over a wide variety of optical and ecological domains using the NASA Langley Research Center HSRL-1 (532 nm) and the recently upgraded HSRL-2 (532 & 355 nm). These datasets provide a unique opportunity to perform a critical assessment of the HSRL technique and to explore the utility of HSRL measurements for evaluating the quality of ocean color remote sensing retrievals on regional scales. A matchup dataset of co-located and high-quality HSRL and ocean color remote sensing measurements was created using data from research flights conducted over the western North Atlantic Ocean during the NASA sponsored SABOR, NAAMES, and ACTIVATE campaigns. Overall, comparisons showed a strong agreement between HSRL and ocean color retrievals of bbp and Kd, providing confidence in our ability to retrieve upper ocean optical properties using oceanographic lidar. However, comparisons from individual flights can exhibit deviations that were not attributed to shifts in water column optical domains. In one of these cases, the simultaneous HSRL atmosphere-ocean retrievals from two consecutive days and within the same region were used to identify ocean color atmospheric correction errors resulting from the presence of absorbing aerosols. These results highlight the utility of airborne HSRL as a standalone ocean observing technology and as an independent and calibrated technique for assessing the quality of ocean color remote sensing retrievals.

Brian Collister↗
NASA NTRSDate not supplied

Principal Component and Machine Learning Approach to Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals can be limited spatially due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals. Despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we developed a spatial gap filling approach applying machine learning approach to hyperspectral instruments to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral components that describe the scattering and absorption of the atmosphere mixed with the surface spectral signatures. The coefficients of the principal components are used to train a neural network to predict ocean color properties derived from a standard MODIS ocean color algorithm. We apply the approach to two hyperspectral UV/VIS sensors, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) onboard upcoming NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the first NASA and Smithsonian geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) spectrometer to better understand diurnal variability in inland and coastal ocean ecology.

Zachary Fasnacht↗
NASA NTRS2019

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗
NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗
NASA NTRS2024

Machine Learning Based Aerosol and Ocean Color Joint Retrieval Algorithm for Multiangle Polarimeters over Coastal Waters

NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, recently launched in February 2024, carries two multiangle polarimeters (MAPs): the UMBC Hyper-Angular Rainbow Polarimeter (HARP2) and SRON Spectropolarimeter for Planetary Exploration One (SPEXone). Measurements from these MAPs will greatly advance ocean ecosystem and aerosol studies as their measurements contain rich information on microphysical properties of aerosols and hydrosols. The Multi-Angular Polarimetric Ocean coLor (MAPOL) joint retrieval algorithm has been developed to retrieve aerosol and ocean color information, which uses a vector radiative transfer (RT) model as the forward model. The RT model is computationally expensive, which makes processing a large amount of data challenging. FastMAPOL was developed to expedite retrieval using neural networks to replace the RT forward models. As a prototype study, FastMAPOL was initially limited to open ocean applications where the ocean Inherent Optical Properties (IOPs) were parameterized in terms of one parameter: chlorophyll-a concentration (Chla). In this study we further expand the FastMAPOL joint retrieval algorithm to incorporate NN based forward models for coastal waters, which use multi-parameter bio-optical models. In addition, aerosols are represented by six components, i.e., fine mode non absorbing insoluble (FNAI), brown carbon (BrC), black carbon (BC), fine mode non absorbing soluble (FNAS), sea salt (SS) and non-spherical dust (Dust). Sea salt and dust are coarse mode aerosols, while the other components are in the fine mode. The sizes and spectral refractive indices are fixed for each aerosol component, while their abundances are retrievable. The multi-parameter bio-optical model and aerosol components are chosen to represent the coastal marine environment. The retrieval algorithm is applied to synthetic measurements in three different configurations ofMAPs in the PACE mission: HARP2 observations only, SPEXone observations only and combined HARP2 and SPEXone observations. The retrieval results from synthetic measurements show that for aerosol retrieval the SPEXone-only configuration works equally well with the HAPR2-only configuration. On the other hand, for ocean color retrieval the SPEXone instrument provides better information due to its larger spectral coverage. For the surface parameters (wind speed), HARP2 measurements provide better information due to its wide field of view. Combined measurement configuration HARP2+SPEXone performed the best to retrieve all aerosol, ocean color and surface parameters. We also studied the impact of sun glint to aerosol and ocean color retrievals. The retrieval test revealed that wind speed and absorbing aerosol retrieval improves significantly when including measurements at glint geometries. Furthermore, the retrieval algorithm is equipped with modules for atmospheric correction and bidirectional reflectance distribution (BRDF) correction to obtain the remote sensing reflectance, which enables ocean biogeochemistry studies using the PACE polarimeter data.

PACE↗
NASA NTRS1971

Experiment M410: Color patch photography

A slate that supported four calibrated color targets was photographed during Gemini 10 mission extravehicular activity to determine if existing outdoor-type color films can reproduce colored objects accurately in the space environment. The experiment resulted in the acquisition of sufficient information to confirm that objects can be photographed in space with good color fidelity by the use of existing materials. Available color film is balanced to the solar spectrum in space, and the effect of ultraviolet energy on film degradation appears to be negligible.

Brinkmann, J. R.↗
NASA NTRS1971

Spatial transform coding of color images.

The application of the transform-coding concept to the coding of color images represented by three primary color planes of data is discussed. The principles of spatial transform coding are reviewed and the merits of various methods of color-image representation are examined. A performance analysis is presented for the color-image transform-coding system. Results of a computer simulation of the coding system are also given. It is shown that, by transform coding, the chrominance content of a color image can be coded with an average of 1.0 bits per element or less without serious degradation. If luminance coding is also employed, the average rate reduces to about 2.0 bits per element or less.

Pratt, W. K.↗
NASA NTRS1973

Four wavelength lidar applied to determination of chlorophyll a concentration and algae color group

A technique for remote measurement of chlorophyll a density and determination of algae color group is described. In vivo fluorescence measurements of chlorophyll a for four color groups of algae (green, golden-brown, red, and blue-green) are described, and representative spectra are shown. The lidar equation is developed for the general case of a mixture of color groups showing the need for multicolor excitation. The lidar instrument which has been designed and fabricated at Langley Research Center for helicopter flights over surrounding portions of the Chesapeake Bay is described. The lidar package contains a unique four-color dye laser which permits multicolor excitation of chlorophyll a fluorescence from the various color groups of algae.

Jarrett, O., Jr.↗
NASA NTRS1977

A color prediction model for imagery analysis

A simple model has been devised to selectively construct several points within a scene using multispectral imagery. The model correlates black-and-white density values to color components of diazo film so as to maximize the color contrast of two or three points per composite. The CIE (Commission Internationale de l'Eclairage) color coordinate system is used as a quantitative reference to locate these points in color space. Superimposed on this quantitative reference is a perceptional framework which functionally contrasts color values in a psychophysical sense. This methodology permits a more quantitative approach to the manual interpretation of multispectral imagery while resulting in improved accuracy and lower costs.

Skaley, J. E.↗
NASA NTRS1980

Development and usage of a false color display technique for presenting Seasat-A scatterometer data

A computer generated false color program which creates digital multicolor graphics to display geophysical surface parameters measured by the Seasat-A satellite scatterometer (SASS) is described. The data is incrementally scaled over the range of acceptable values and each increment and its data points are assigned a color. The advantage of the false color display is that it visually infers cool or weak data versus hot or intense data by using the rainbow of colors. For example, with wind speeds, levels of yellow and red could be used to imply high winds while green and blue could imply calmer air. The SASS data is sorted into geographic regions and the final false color images are projected onto various world maps with superimposed land/water boundaries.

Jackson, C. B.↗
NASA NTRS1980

Theoretical mean colors for RR Lyrae variables

A hydrodynamically pulsating 0.6 solar mass model of a typical RR Lyrae variable was studied with a radiation transport-hydrodynamic computer program to predict theoretical T sub 3 and colors at many phases and to find the proper methods for getting mean colors and the consequent mean effective temperatures. The variable Eddington radiation approximation method was used with gray and with multifrequency absorption coefficients to represent the radiation flow in the outer optically thin layers. Comparison between observed and computed B-V colors indicate that these low Z population 2 models are reasonably accurate using King 1A composition opacities. The well known Oke, Giver, and Searle relation between B-V and T sub e reproduced. Mean colors were found by four different averaging methods. The method that gives a mean color and the mean T sub e closest to the nonpulsating model was the separate intensity means of B and V.

Davis, C. G.↗