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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Television cameras employing solid-state imaging sensors for manned spacecraft applications

The Space Shuttle television system incorporates a versatile complement of TV equipment which allows the positioning, quantity, and performance capabilities of the multiple TV cameras to vary as dictated by the particular mission. However, current TV camera technology employing glass enclosed, vacuum processed image sensors results in a bulky device that restricts its location and versatility. Problems and potential solutions that can be achieved through the employment of solid-state image sensors for both monochrome and color applications are discussed.

Embrey, B. C., Jr.↗
NASA NTRS2001

SIMBIOS Normalized Water-Leaving Radiance Calibration and Validation: Sensor Response, Atmospheric Corrections, Stray Light and Sun Glint

This Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) contract supports acquisition of match up radiometric and bio-optical data for validation of Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) and other ocean color satellites, and evaluation of uncertainty budgets and protocols for in situ measurements of normalized water leaving radiances.

Mueller, James L.↗
NASA NTRS2020

Overcoming Dimensionality Barriers in Satellite Data to Elucidate SPECTRAL-SPATIAL-TEMPORAL Trends in the Ocean

The weighted harmonic mean of spectral wavelengths can be used as an index of optical water types that share similar spectral signatures.This technique can be translated to relate spectral shape between sensors of varying spectral resolution.The output along a continuum of color values enables spatio-temporal analysis of subtle spectral shifts.Directional trends in absorption and backscatter data lend a hidden context to changes in water color. Conceptualization of multiple data dimensions is imperative as passive/active sensors grow increasingly sophisticated in nature.

Vandermeulen, Ryan↗
NASA NTRS2022

Spatial Characterization of PACE OCI ETU Using Time-Delay Mode

The OCI (Ocean Color Instrument) is the main sensor on the upcoming PACE (Plankton Aerosol Cloud ocean Ecosystem) mission. OCI has two hyperspectral CCD sensors covering 340nm to 885nm and 9 SWIR (Short Wave IR) bands from 940nm to 2260nm. SWIR bands have nominal 1km ground pixel size and CCD bands have native 1/8 km ground pixel size in diagnostic mode that will be aggregated into 1km pixels to improve SNR and meet the data rate constraints. OCI has a rotating telescope that is synchronized to the readout of the CCD and SWIR detectors. Full pre-launch system level testing for the OCI ETU (Engineering Test Unit) was completed in June 2021.With time-delayed scan mode, a sub-pixel level time-delay step is applied to the detector readout. This sub-pixel level time-delay step causes a sub-pixel level shift in the start of the data collection. After collecting time-delay step scans with different step sizes, a scan profile with sub-pixel resolution can be constructed. 1/8 and 1/4 of CCD pixel resolutions were achieved using this mode. In this paper, the OCI time-delayed scan mode will be described as well as how it was used to calculate OCI’s high spatial resolution PSF (Point Spread Function), IFOV (instantaneous Field of View), MTF (Modulation Transfer Function), and BBR (Band to Band Registration).

PACE↗
NASA NTRS1977

Visible and infrared imaging radiometers for ocean observations

The technology of visible and infrared imaging sensors designed for the remote monitoring of the oceans is assessed. 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 (OCS) and the Ocean Temperature Scanner (OTS). The Coastal Zone Color Scanner (CZCS) and Advanced Very High Resolution Radiometer (AVHRR), are reviewed with emphasis on design specifications, expected completion, and anticipated performance. Finally, recent technology advances and their probable impact on sensor design are examined.

Barnes, W. L.↗
NASA NTRS2001

Biogeochemical Response to Mesoscale Physical Forcing in the California Current System

In the first part of the project, we investigated the local response of the coastal ocean ecosystems (changes in chlorophyll, concentration and chlorophyll, fluorescence quantum yield) to physical forcing by developing and deploying Autonomous Drifting Ocean Stations (ADOS) within several mesoscale features along the U.S. west coast. Also, we compared the temporal and spatial variability registered by sensors mounted in the drifters to that registered by the sensors mounted in the satellites in order to assess the scales of variability that are not resolved by the ocean color satellite. The second part of the project used the existing WOCE SVP Surface Lagrangian drifters to track individual water parcels through time. The individual drifter tracks were used to generate multivariate time series by interpolating/extracting the biological and physical data fields retrieved by remote sensors (ocean color, SST, wind speed and direction, wind stress curl, and sea level topography). The individual time series of the physical data (AVHRR, TOPEX, NCEP) were analyzed against the ocean color (SeaWiFS) time-series to determine the time scale of biological response to the physical forcing. The results from this part of the research is being used to compare the decorrelation scales of chlorophyll from a Lagrangian and Eulerian framework. The results from both parts of this research augmented the necessary time series data needed to investigate the interactions between the ocean mesoscale features, wind, and the biogeochemical processes. Using the historical Lagrangian data sets, we have completed a comparison of the decorrelation scales in both the Eulerian and Lagrangian reference frame for the SeaWiFS data set. We are continuing to investigate how these results might be used in objective mapping efforts.

Niiler, Pearn P.↗
NASA NTRS2002

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

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.

McClain, Charles↗
NASA NTRS2016

Atmospheric Correction for Satellite Ocean Color Radiometry

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.

MODIS↗
NASA NTRS1979

Applications of remote sensing for water quality and biological measurements in coastal waters

Potential applications of remote sensing technology to the study of coastal marine environments are reviewed, emphasizing water quality and biological measurements. Parameters measurable by airborne or spaceborne remote sensors include particulates, measured by visual or multispectral photography, chlorophyll a, measured by the Ocean Color Scanner or Coastal Zone Color Scanner, temperature distributions, by IR or microwave sensors, and salinity, by means of microwave radiometers. Research projects in which wide area synoptic or repetitive remote sensing can make a major contribution include the study of estuarine and continental shelf sediment transport dynamics, marine pollutant transport, marine phytoplankton dynamics and ocean fronts.

Johnson, R. W.↗
NASA NTRS2019

Vicarious Calibration of GOCI for the SeaDAS Ocean Color Retrieval

A key on-orbit calibration step for satellite remote sensing of ocean color is the vicarious calibration. This establishes the final gains for each spectral band on the sensor that minimize bias in the retrieved ocean color signal. The vicarious calibration is specific to the instrument and the atmospheric correction algorithm. The vicarious calibration gains for the Geostationary Ocean Color Imager (GOCI) are presented here, which were derived to optimize the performance ofNASA's standard atmospheric correction algorithm as implemented in the l2gen code and distributed through the SeaDAS open-source software package. Following NASA's protocols, the near-infrared(NIR) bands were calibrated first, and the visible bands were then calibrated relative to this fixed NIR calibration. The gain for the 745-nm NIR band was derived using a fixed aerosol model, which waschosen based on the Angstrom Coefficients derived from MODIS onAqua (MODISA). For the vicarious gains of the visible bands, twosources for the target water-leaving radiances were tested: matchupsfrom MODISA and climatological data from SeaWiFS. A validation analysis using AERONET-OC data shows an improvement in sensor performance when compared with results using the current vicarious gains and results using no vicarious calibration. Good agreement was found in vicarious gains derived using both concurrent MODISA and climatological SeaWiFS as vicarious calibration data sources. These results support the use of a concurrent sensor for the vicarious calibration when in situ data are not available and demonstrate that using climatology from a well-calibrated sensor like SeaWiFSfor the vicarious calibration is a valid alternative when it is not possible to use a concurrent sensor or in situ data. We recommend using the gains derived from concurrent GOCI matchups with MODISA for GOCI processing in SeaDAS/l2gen.

Concha, Javier↗
NASA NTRS2019

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗
NASA NTRS1970

Classifying forest and nonforest land on space photographs

Although the research reported is in its preliminary stages, results show that: (1) infrared color film is the best single multiband sensor available; (2) there is a good possibility that forest can be separated from all nonforest land uses by microimage evaluation techniques on IR color film coupled with B/W infrared and panchromatic films; and (3) discrimination of forest and nonforest classes is possible by either of two methods: interpreters with appropriate viewing and mapping instruments, or programmable automatic scanning microdensitometers and automatic data processing.

Aldrich, R. C.↗
NASA NTRS2012

Satellite Observation Systems for Polar Climate Change Studies

The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques will be discussed. An important issue is the organization and storage of hundreds of terabytes of data collected by even just a few of these satellite sensors. Advances in mass storage and computer technology have made it possible to overcome many of the collection and archival problems and the availability of comprehensive satellite data sets put together by NASA's Earth Observing System project will be discussed.

Comiso, Josefino C.↗
NASA NTRS1999

Robotic Rock Classification

This report describes a three-month research program undertook jointly by the Robotics Institute at Carnegie Mellon University and Ames Research Center as part of the Ames' Joint Research Initiative (JRI.) The work was conducted at the Ames Research Center by Mr. Liam Pedersen, a graduate student in the CMU Ph.D. program in Robotics under the supervision Dr. Ted Roush at the Space Science Division of the Ames Research Center from May 15 1999 to August 15, 1999. Dr. Martial Hebert is Mr. Pedersen's research adviser at CMU and is Principal Investigator of this Grant. The goal of this project is to investigate and implement methods suitable for a robotic rover to autonomously identify rocks and minerals in its vicinity, and to statistically characterize the local geological environment. Although primary sensors for these tasks are a reflection spectrometer and color camera, the goal is to create a framework under which data from multiple sensors, and multiple readings on the same object, can be combined in a principled manner. Furthermore, it is envisioned that knowledge of the local area, either a priori or gathered by the robot, will be used to improve classification accuracy. The key results obtained during this project are: The continuation of the development of a rock classifier; development of theoretical statistical methods; development of methods for evaluating and selecting sensors; and experimentation with data mining techniques on the Ames spectral library. The results of this work are being applied at CMU, in particular in the context of the Winter 99 Antarctica expedition in which the classification techniques will be used on the Nomad robot. Conversely, the software developed based on those techniques will continue to be made available to NASA Ames and the data collected from the Nomad experiments will also be made available.

Hebert, Martial↗
NASA NTRS2017

Atmospheric Correction for Hyperspectral Ocean Color Retrieval with Application to the Hyperspectral Imager for the Coastal Ocean (HICO)

The classical multi-spectral Atmospheric Correction (AC) algorithm 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 scattering by aerosols from the measured top-of-atmosphere (TOA) radiance, compensate for the absorption by atmospheric gases, and correct for reflection and refraction of the air-sea interface. In this work, we present and evaluate an improved AC for hyperspectral sensors developed within NASA's Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Data Analysis System software package (SeaDAS). The improvement is based on combining the classical AC approach of multi-spectral capabilities to correct for the atmospheric path radiance, extended to hyperspectral, with a gas correction algorithm to compensate for absorbing gases in the atmosphere, including water vapor. The SeaDAS-hyperspectral version is capable of operationally processing the AC of any hyperspectral airborne or spaceborne sensor. The new algorithm development was evaluated and assessed using the Hyperspectral Imager for Coastal Ocean (HICO) scenes collected at the Marine Optical BuoY (MOBY) site, and other SeaWiFS Bio-optical Archive and Storage System (SeaBASS) and AERosol Robotic NETwork - Ocean Color (AERONET-OC) coastal sites. A hyperspectral vicarious calibration was applied to HICO, showing the validity and consistency of HICO's ocean color products. The hyperspectral AC capability is currently available in SeaDAS to the scientific community at https://oceancolor.gsfc.nasa.gov/.

Ocean Color↗
NASA NTRS1981

Remote sensing of the diffuse attenuation coefficient of ocean water

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.

Austin, R. W.↗
NASA NTRS2010

Achieving Global Ocean Color Climate Data Records

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.

Franz, Bryan↗
DOE OSTI2024

Unraveling sources of emission heterogeneity in Silicon Vacancy color centers with cryo-cathodoluminescence microscopy

Diamond color centers have proven to be versatile quantum emitters and exquisite sensors of stress, temperature, electric and magnetic fields, and biochemical processes. Among color centers, the silicon-vacancy (SiV - ) defect exhibits high brightness, minimal phonon coupling, narrow optical linewidths, and high degrees of photon indistinguishability. Yet the creation of reliable and scalable SiV - -based color centers has been hampered by heterogeneous emission, theorized to originate from surface imperfections, crystal lattice strain, defect symmetry, or other lattice impurities. Here, we advance high-resolution cryo-electron microscopy combined with cathodolumines cence spectroscopy and 4D scanning transmission electron microscopy (STEM) to elucidate the structural sources of heterogeneity in SiV - emission from nanodiamond with sub-nanometer-scale resolution. Our diamond nanoparticles are grown directly on TEM membranes from molecular-level seedings, representing the natural formation conditions of color centers in diamond. We show that individual subcrystallites within a single nanodiamond exhibit distinct zero-phonon line (ZPL) energies and differences in brightness that can vary by 0.1 meV in energy and over 70% in brightness. These changes are correlated with the atomic-scale lattice structure. We find that ZPL blue shifts result from tensile strain, while ZPL red shifts are due to compressive strain. We also find that distinct crystallites host distinct densities of SiV - emitters and that grain boundaries impact SiV - emission significantly. Finally, we interrogate nanodiamonds as small as 40 nm in diameter and show that these diamonds exhibit no spatial change to their ZPL energy. Our work provides a foundation for atomic-scale structure-emission correlation, e.g., of single atomic defects in a range of quantum and two-dimensional materials.

36 MATERIALS SCIENCE↗