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Results for “spectral responsivity”

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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

An assessment of the impact of system spectral response parameters on spectral shape and algal bloom detection for the GeoXO ocean color instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A large dataset in-situ spectra, from a variety of locations and water cases collected with an above water spectrometer, was used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX.

Monica Cook↗
NASA NTRS1977

Field measurements of the spectral response of natural waters

The spectral response (air-water interface reflectance and water-volume scattering) of turbid river water (99 mg/liter suspended solids) and relatively clear lake water (10 mg/liter suspended solids) was measured in situ with a field spectroradiometer. The influence of the river bottom on the spectral response of the water also was determined by using a modified Secchi disc approach. The results indicated that turbid river water had a higher spectral response than clear lake water (about 6 percent) in the red (0.6-0.7 micron) and near-infrared (0.7-0.9 micron) portions of the spectrum. Also, the reflectance characteristics of the river bottom did not influence the spectral response of the turbid river water when the water was deeper than 30 cm

Bartolucci, L. A.↗
NASA NTRS1981

Spectral response from blackbody measurements

Far-infrared and submillimeter detector responsivity and spectral response measurements can be performed simultaneously by sweeping the temperature of a cooled blackbody. Such measurements yield n simultaneous linear equations for n blackbody temperatures. Matrix inversion solutions are observed to fail due to a matrix ill-conditioned for inversion. However, an unconditionally convergent iterative solution can be performed. Results for a gallium-doped germanium detector are described.

Moore, W. J.↗
NASA NTRS2000

Calibration of the ROSAT HRI Spectral Response

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Prestwich, Andrea H.↗
NASA NTRS1998

Calibration of the ROSAT HRI Spectral Response

The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases-with time and also is a function of position on the detector. To complicate matters further, the satellite is "wobbled", possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT HRI from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.

Prestwich, Andrea↗
NASA NTRS1976

Spectral response measurements with white light bias

The spectral response of solar cells such as the CdS/Cu2S cell is non-linear with distinct quenching and enhancement bands. One possible technique to produce standardized solar efficiencies is to fold in spectral response with a standard solar spectrum. The spectral response of a cell was measured in a way which matched cell behavior under white light illumination. A technique was developed to measure the response of a cell to low intensity chopped monochromatic light while the cell is also illuminated with a white light bias corresponding to AMI.

Devaney, W.↗
NASA NTRS1979

Solar cell spectral response characterization

The absolute spectral response of solar cells is reported in the 400-1000-nm spectral region. Measurements were performed using two different types of monochromatic sources: amplitude-stabilized CW laser lines and interference filters with an incandescent lamp. Both types of calibration procedures use electrical substitution radiometry as the basis of traceability to absolute SI units. The accuracy of the calibration is shown to be limited by the nonideal characteristics of the solar cells themselves, specifically spatial nonuniformities and nonlinearities induced by high light levels.

Zalewski, E. F.↗
NASA NTRS1984

Spectral response curve models applied to forest cover-type discrimination

The potential of remote sensing systems to provide a cost-effective inventory tool in the case of forest resources is currently of interest to a variety of natural resources management agencies. A number of studies have been performed regarding the use of Landsat data for mapping forest resources in Michigan. The present paper is concerned with current research, which has been directed toward the development and evaluation of computer-implemented classifications for the identification and characterization of coniferous forest types in Michigan's northern Lower Peninsula. Attention is given to the characteristic response curves from Landsat MSS data, spectral response curve models, and forest cover-type discrimination. It is found that spectral response curve models can be used to evaluate and explain the characteristic spectral responses of coniferous forest types on a snow-covered, winter Landsat scene.

Hudson, W. D.↗
NASA NTRS2019

LANDSAT 9 Thermal Infrared Sensor 2 Spectral Response Test: Updates and Perspective

The Thermal Infrared Sensor 2 (TIRS-2) pre-launch spectral characterization at telescope and detector subsystem level provided a strong indication that the spectral response requirements will be met. Confidence in the validity of these results was strengthened through comparison to component-level measurements. This work reviews the modifications to the test setup to reduce spectral response uncertainties further in preparation for instrument-level testing. We developed a methodology to improve alignment repeatability of the upgraded system. Preliminary indications show that the spectral response will contribute a relatively small amount to the overall TIRS-2 radiometric uncertainty budget, which is expected to meet its radiometric requirements. Through spectral response testing, as part of a comprehensive pre-launch test program, TIRS-2 is expected to achieve the performance necessary for a variety of environmental applications.

spectral response↗
NASA NTRS2019

Landsat 9 TIRS-2 Spectral Response Test: Updates & Perspective

The Thermal Infrared Sensor 2 (TIRS-2) pre-launch spectral characterization at telescope and detector subsystem level provided a strong indication that the spectral response requirements will be met. Confidence in the validity of these results was strengthened through comparison to component-level measurements. This work reviews the modifications to the test setup to reduce spectral response uncertainties further in preparation for instrument-level testing. We developed a methodology to improve alignment repeatability of the upgraded system. Preliminary indications show that the spectral response will contribute a relatively small amount to the overall TIRS-2 radiometric uncertainty budget, which is expected to meet its radiometric requirements. Through spectral response testing, as part of a comprehensive pre-launch test program, TIRS-2 is expected to achieve the performance necessary for a variety of environmental applications.

Pearlman, Aaron↗
NASA NTRSDate not supplied

An Initial Assessment of the Impact of System Spectral Response Parameters on Driving Ocean Color Applications for the GeoXO Ocean Color Instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A dataset of high resolution (1 nm spectral sampling) in-situ spectra of red tide collected with an above water spectrometer, and associated K. brevis cell concentrations, were used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX. Future work will seek to expand this analysis to include a larger dataset that considers additional water cases.

Monica Cook↗
NASA NTRSDate not supplied

An Initial Assessment of the Impact of System Spectral Response Parameters on Driving Ocean Color Applications for the GeoXO Ocean Color Instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A dataset of high resolution (1 nm spectral sampling) in-situ spectra of red tide collected with an above water spectrometer, and associated K. brevis cell concentrations, were used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX. Future work will seek to expand this analysis to include a larger dataset that considers additional water cases.

M. Cook↗
NASA NTRS2018

Spectral Response and Effective Area Functions of the Hitomi Imaging Instruments

We describe the tools and the underlying methods and principles for generating the spectral response functions for the four imaging instruments that were flown on the Hitomi x-ray astronomy satellite [Soft X-ray Spectrometer, or SXS; Soft X-ray Imager, or SXI, and two Hard X-ray Imagers, or HXI]. In essence, the spectral response function is a temporally and spatially averaged effective area and line-spread-function. For model-fittingx-ray spectra from an instrument, the spectral response function encapsulates the end-to-end physics of the entire system from telescope to detector, and also includes satellite attitude drift, exposure corrections, and in the case of the HXIs, drift in the telescope/detector alignment system. Accuracy in the construction of the spectral response functions is, therefore, critical to maximize the science return from the data.

Yaqoob, Tahir↗
NASA NTRS2016

JPSS-1 VIIRS Version 2 At-Launch Relative Spectral Response Characterization and Performance

The relative spectral response (RSR) characterization of the JPSS-1 VIIRS spectral bands has achieved at launch status in the VIIRS Data Analysis Working Group February 2016 Version 2 RSR release. The Version 2 release improves upon the June 2015 Version 1 release by including December 2014 NIST TSIRCUS spectral measurements of VIIRS VisNIR bands in the analysis plus correcting CO2 influence on the band M13 RSR. The T-SIRCUS based characterization is merged with the summer 2014 SpMA based characterization of VisNIR bands (Version 1 release) to yield a fused RSR for these bands, combining the strengths of the T-SIRCUS and the SpMA measurement systems. The M13 RSR is updated by applying a model-based correction to mitigate CO2 attenuation of the SpMA source signal that occurred during M13 spectral measurements. The Version 2 release carries forward the Version 1 RSR for those bands that were not updated (M8-M12, M14-M16AB, I3-I5, DNBMGS). The Version 2 release includes band average (overall detectors and subsamples) RSR plus supporting RSR for each detector and subsample. The at-launch band average RSR have been used to populate Look-Up Tables supporting the sensor data record and environmental data record at-launch science products. Spectral performance metrics show that JPSS-1VIIRS RSR are compliant on specifications with a few minor exceptions. The Version 2 release, which replaces the Version 1 release, is currently available on the password-protected NASA JPSS-1 eRooms under EAR99 control.

Chris Moeller↗
NASA NTRS1993

Spectral response of a bilinear oscillator

An approximate analytical procedure is presented to estimate the response power spectral density of a randomly excited spring/mass/damper system having a bilinear spring. The approximate expression for the response spectrum is developed by representing the nonlinear oscillator as a linear system having a natural frequency that depends on the envelope of the random response. This approximate representation of the system leads to estimates of the response spectrum that agree extremely well with those obtained by direct numerical simulation of the governing equation.

Miles, R. N.↗
NASA NTRS1981

Low background spectral response of 30-130-micron detectors from blackbody measurements

Low background far infrared detector responsivity and low background spectral response calibrations can be performed simultaneously with a cooled, temperature-swept blackbody. This makes the use of a cooled, low background spectrometer unnecessary in many applications. Calibrations of a beryllium-doped germanium detector showing unwanted 100-micron response, and of a gallium-doped germanium detector, are described.

Moore, W. J.↗
NASA NTRS1974

Rapid measurements of areal sensitivity and areal spectral response of photodetectors

A flying spot scanning system was used to obtain areal sensitivity and areal spectral response data for nineteen photomultipliers. The efficiency of the electron optics was shown to be dependent upon the type of dynode structure used in the several photomultipliers. From areal sensitivity measurements it was found that the relative spectral response per unit area can vary over the face of a photomultiplier.

Youngbluth, O., Jr.↗