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NASA NTRS1995

Determination of the in-flight spectral calibration of AVIRIS using atmospheric absorption features

Spectral calibration of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) as data are acquired in flight is essential to quantitative analysis of the measured upwelling spectral radiance. In each spectrum measured by AVIRIS in flight, there are numerous atmospheric gas absorption bands that drive this requirement for accurate spectral calibration. If the surface and atmospheric properties are measured independently, these atmospheric absorption bands may be used to deduce the in-flight spectral calibration of an imaging spectrometer. Both the surface and atmospheric characteristics were measured for a calibration target during an in-flight calibration experiment held at Lunar Lake, Nevada on April 5, 1994. This paper uses upwelling spectral radiance predicted for the calibration target with the MODTRAN radiative transfer code to validate the spectral calibration of AVIRIS in flight.

Green, Robert O.↗

NASA NTRS1994

Radiative transfer code based estimation of atmospheric parameters for inversion of imaging spectrometer measured radiance to apparent surface reflectance

Surface reflectance is required to quantitatively investigate molecular absorption and particle scattering properties of materials on the Earth's surface. Atmospheric aerosol optical depth, surface pressure and water vapor are required to constrain a radiative transfer code for the inversion of measured spectral radiance to apparent surface reflectance. A suite of algorithms using nonlinear least squares fitting techniques are described that directly estimate these atmospheric parameters from spectral radiance measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The derived atmospheric parameters are used to constrain a radiative transfer code for the inversion of the imaging spectrometer radiance to apparent reflectance. The derived apparent reflectance is validated with respect to in situ measurement on the same target.

Green, Robert O.↗

NASA NTRS1986

Absolute radiometric calibration of the Thematic Mapper

Calibration data for the solar reflective bands of the Landsat-5 TM obtained from five in-flight absolute radiometric calibrations from July 1984-November 1985 at White Sands, New Mexico are presented and analyzed. Ground reflectance and atmospheric data were utilized to predict the spectral radiance at the entrance pupil of the TM and the average number of digital counts in each TM band. The calibration of each of the TM solar reflective bands was calculated in terms of average digital counts/unit spectral radiance for each band. It is observed that for the 12 reflectance-based measurements the rms variation from the means as a percentage of the mean is + or - 1.9 percent; for the 11 measurements in the IR bands, it is + or - 3.4 percent; and the rms variation for all 23 measurements is + or - 2.8 percent.

Slater, P. N.↗

NASA NTRS1994

Mercury: Mid-infrared (7.3 - 13.5 microns) spectroscopic observations showing features characteristic of plagioclase

Mid-infrared spectroscopic observations of the surface of Mercury are reported for the wavelength range 7.3 to 13.5 microns. The observed spectral radiance emanated from equatorial and low latitude regions between 110-130 deg Mercurian longitude. The area is primarily an intercrater plain. The spectra show distinct and recognizable features, the principal Christiansen emission peak being the most prominent. The Christiansen feature strongly suggests the presence of plagioclase (Ca,Na)(Al,Si)AlSi2O8, (in particular labradorite: Ab(50) - Ab(30)). In addition we have studied the effects of thermal gradients to gain insight into the effects of thermal conditions on the spectral radiance of rock samples. This simulates the thermophysical effects as the rotating surface of Mercury is alternately heated and cooled. The spectral features of the samples are retained; however, the relative and absolute amplitudes vary as illustrated by laboratory reflectance and emittance spectra from quartzite.

Kozlowski, R. W. H.↗

NASA NTRS1990

Photosynthetic accessory pigments - Evidence for the influence of phycoerythrin on the submarine light field

Upwelled water-leaving spectral radiances and the submarine light-field source are theorized to have the physical scattering and absorption effects of photosynthetic accessory pigments. A laser is employed to induce phycoerythrin pigment fluorescence, and the presence of the photosynthetic accessory pigment is measured in oceanic waters with a spectral fluorescence method. Experimental data from active-passive correlation spectroscopy demonstrate that water-leaving spectral radiances of about 600 nm are highly correlated with phycoerythrin pigment fluorescence. Because the data on the phycoerythrin and chlorophyll fluorescences are entered randomly in the correlation the results are considered unambiguous. An estimate of the photopigment is derived that agrees with measurements of its laser-induced fluorescence.

Hoge, Frank E.↗

NASA NTRS1993

High-speed spatial scanning pyrometer

A high-speed spatial scanning pyrometer has been designed and developed to measure spectral radiance temperatures at multiple target points along the length of a rapidly heating/cooling specimen in dynamic thermophysical experiments at high temperatures (above about 1800 K). The design, which is based on a self-scanning linear silicon array containing 1024 elements, enables the pyrometer to measure spectral radiance temperatures (nominally at 650 nm) at 1024 equally spaced points along a 25-mm target length. The elements of the array are sampled consecutively every 1 microsec, thereby permitting one cycle of measurements to be completed in approximately 1 msec. Procedures for calibration and temperature measurement as well as the characteristics and performance of the pyrometer are described. The details of sources and estimated magnitudes of possible errors are given. An example of measurements of radiance temperatures along the length of a tungsten rod, during its cooling following rapid resistive pulse heating, is presented.

Cezairliyan, A.↗

NASA NTRS1984

Aboveground Biomass Estimation in a Tidal Brackish Marsh Using Simulated Thematic Mapper Spectral Data

Spectral radiance data were collected from the ground and from a low altitude aircraft in an attempt to gain some insight into the potential utility of actual Thematic Mapper data for biomass estimation in wetland plant communities. No attempt was made to distinguish individual plant species within brackish marsh plant associations. Rather, it was decided to lump plant species with similar canopy morphologies and then estimate from spectral radiance data the biomass of the group. The rationale for such an approach is that plants with a similar morphology will produce a similar reflecting or absorping surface (i.e., canopy) for incoming electromagnetic radiation. Variations in observed reflectance from different plant communities with a similar canopy morphology are more likely to be a result of biomass differences than a result of differences in canopy architecture. If the hypothesis that plants with a similar morphology exhibit similar reflectance characteristics is true, then biomass can be estimated based on a model for the dominant plant morphology within a plant association and the need for species discrimination has effectively been eliminated.

Hardisky, M.↗

NASA NTRS1996

SeaWiFs Technical Report Series. Volume 34: The Third SeaWiFS Intercalibration Round-Robin Experiment (SIRREX-3), 19-30 September 1994

This report presents results of the third Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round- Robin Experiment (SIRREX-3), which was held at the San Diego State University (SDSU) Center for Hydro-Optics and Remote Sensing (CHORS) on 19-30 September 1994. Spectral irradiances of FEL lamps belonging to each participant were intercompared by reference to the National Institute of Standards and Technology (NIST) scale of spectral irradiance using secondary standard lamps F268, F269, and F182, with a Type A uncertainty between 1.1-1.5%. This level of uncertainty was achieved despite difficulties with lamp F269. The average spectral irradiances of FEL lamps, compared in both SIRREX-2 and SIRREX-3, differed between the two experiments by 1.5%, which probably indicates that the values assigned to the secondary standard lamp at the time of SIRREX-2 were in error. With two exceptions, spectral radiance values of integrating sphere sources were measured during SIRREX-3 with uncertainties in temporal stability of less than 0.3% and absolute uncertainties of 1.5-2.0%. This is a significant improvement over similar intercomparisons in SIRREX- I and SIRREX-2. Plaque reflectances were intercompared with an uncertainty of about 1-2%, but the absolute uncertainty is undefined. Although this is an improvement over results of previous SIRREXS, the sources and magnitude of uncertainty associated with transfers of spectral radiance using plaques requires further evaluation in future experiments.

Hooker, Stanford B.↗

NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗

NASA NTRS1982

A climate index derived from satellite measured spectral infrared radiation

The vertical infrared radiative emitting structure (VIRES) climate index, based on radiative transfer theory and derived from the spectral radiances typically used to retrieve temperature profiles, is introduced. It is assumed that clouds and climate are closely related and a change in one will result in a change in the other. The index is a function of the cloud, temperature, and moisture distributions. It is more accurately retrieved from satellite data than is cloudiness per se. The VIRES index is based upon the shape and relative magnitude of the broadband weighting function of the infrared radiative transfer equation. The broadband weighting curves are retrieved from simulated satellite infrared sounder data (spectral radiances). The retrieval procedure is described and the error error sensitivities of the method investigated. Index measuring options and possible applications of the VIRES index are proposed.

Abel, M. D.↗

NASA NTRS2011

A Maximum Likelihood Approach to Determine Sensor Radiometric Response Coefficients for NPP VIIRS Reflective Solar Bands

Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.

Lei, Ning↗

NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗

NASA NTRS1994

SeaWiFS technical report series. Volume 16: The second SeaWiFS Intercalibration Round-Robin Experiment, SIRREX-2, June 1993

The results of the second Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round-Robin Experiment (SIRREX-2), which was held at the Center for Hydro-Optics and Remote Sensing (CHORS) at San Diego State University on 14-25 Jun. 1993 are presented. SeaWiFS is an ocean color radiometer that is scheduled for launch in 1994. The SIRREXs are part of the SeaWiFS Calibration and Validation Program that includes the GSFC, CHORS, NIST, and several other laboratories. GSFC maintains the radiometric scales (spectral radiance and irradiance) for the SeaWiFS program using spectral irradiance standards lamps, which are calibrated by NIST. The purpose of each SIRREX is to assure that the radiometric scales which are realized by the laboratories who participate in the SeaWiFS Calibration and Validation Program are correct; that is, the uncertainties of the radiometric scales are such that measurements of normalized water-leaving radiance using oceanographic radiometers have uncertainties of 5%. SIRREX-1 demonstrated, from the internal consistency of the results, that the program goals would not be met without improvements to the instrumentation. The results of SIRREX-2 demonstrate that spectral irradiance scales realized using the GSFC standard irradiance lamp (F269) are consistent with the program goals, as the uncertainty of these measurements is assessed to be about 1%. However, this is not true for the spectral radiance scales, where again the internal consistency of the results is used to assess the uncertainty. This is attributed to inadequate performance and characterization of the instrumentation. For example, spatial nonuniformities, spectral features, and sensitivity to illumination configuration were observed in some of the integrating sphere sources. The results of SIRREX-2 clearly indicate the direction for future work, with the main emphasis on instrument characterization and the assessment of the measurement uncertainties so that the results may be stated in a more definitive manner.

Hooker, Stanford B.↗

NASA NTRS2000

Mapping Agricultural Crops with AVIRIS Spectra in Washington State

Spectroscopy is used in the laboratory to measure the molecular components and concentrations of plant constituents to answer questions about the plant type, status, and health. Imaging spectrometers measure the upwelling spectral radiance above the Earth's surface as images. Ideally, imaging spectrometer data sets should be used to understand plant type, plant status, and health of plants in an agricultural setting. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set was acquired over agricultural fields near Wallula, Washington on July 23rd, 1997. AVIRIS measures upwelling radiance spectra through 224 spectral channels with contiguous 10-nm sampling from 400 to 2500 run in the solar-reflected spectrum. The spectra are measured as images of 11 by up to 800 km with 20-m spatial resolution. The spectral images measured by AVIRIS represent the integrated signal resulting from: the solar irradiance; two way transmittance and scattering of the atmosphere; the absorptions and scattering of surface materials; as well as the spectral, radiometric and spatial response functions of AVIRIS. This paper presents initial research to derive properties of the agricultural fields near Wallula from the calibrated spectral images measured by AVIRIS near the top of the atmosphere.

Green, Robert O.↗

NASA NTRS1998

Mapping Agricultural Crops with AVIRIS Spectra in Washington State

Spectroscopy is used in the laboratory to measure the molecular components and concentrations of plant constituents to answer questions about the plant type, status, and health. Imaging spectrometers measure the upwelling spectral radiance above the Earth's surface as images. Ideally, imaging spectrometer data sets should be used to understand plant type, plant status, and health of plants in an agricultural setting. An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set was acquired over agricultural fields near Wallula, Washington on July 23rd, 1997. AVIRIS measures upwelling radiance spectra through 224 spectral channels with contiguous 10-nm sampling from 400 to 2500 nm in the solar-reflected spectrum. The spectra are measured as images of 11 by up to 800 km with 20-m spatial resolution. The spectral images measured by AVIRIS represent the integrated signal resulting from: the solar irradiance; two way transmittance and scattering of the atmosphere; the absorptions and scattering of surface materials; as well as the spectral, radiometric and spatial response functions of AVIRIS. This paper presents initial research to derive properties of the agricultural fields near Wallula from the calibrated spectral images measured by AVIRIS near the top of the atmosphere.

Green, Robert↗

NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗

NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗

NASA NTRS2021

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement–Southern Great Plains Site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to get a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near boundary layer top. We also explore how differences in retrievals may impact results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval showed some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

boundary-layer observation↗