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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Thermal Band Characterization of LANDSAT-4 Thematic Mapper

A quick look monitor in the spacecraft control center was used to measure the TM Band 6 shutter background and the 34.7 C internal blackbody signal on over 50 dates. Comparison of relative internal gains between the four channels to prelaunch values showed changes over 9 months of up to 5%, while 512 x 512 subsections of the original 10 daytime scenes showed scene counts that ranged from 135 down to 62. A night scene of the Buffalo area was used to determine channel gain relative to the mean and to discern a systematic along scan pattern in a difference between forward and reverse scan counts of up to 0.5. A corrected digital image was produced and individual gains and offsets were calculated for the four channels. At satellite radiance was determine and noise equivalent temperature difference was calculated. The calibration data and the Buffalo scene, with the corrections and estimates of the atmospheric transmission and radiance, were used to make a temperature estimate for an area of Lake Erie of 21 C to 27 C. Local records of the temperature showed 21 C.

Lansing, J. C.↗
NASA NTRS1995

Satellite-derived interannual variability of West African rainfall during 1983-88

Two satellite algorithms for rain estimation are used to study the interannual variability of West African rainfall during contrasting years of the period 1983-88. The first algorithm uses a frequency of occurrence index quantifying the number of times Meteosat thermal infrared radiance below 2.107 W/sq m/sr/micrometer (-40 C) occurs during the rainy season. The second algorithm uses the average Meteosat thermal infrared radiance over the period of interest. Appropriate calibrations are performed using these satellite parameters and ground-based rainfall observations. Separate calibration and equations are considered for each of three suggested subrainfall zones in West Africa: two Sahelian zones located just north of 9 deg N (one east and one west of 5 deg W) and the region extending south from 9 deg N to the coast. Over 80% of the variance in the ground-based rainfall data is explained by both algorithms in regions located north of 9 deg N, but poor correlations between observed and estimated rainfall exist south of 9 deg N. The interannual variability of rainfall in the Sahel is well described by that of cold clouds and average radiances. The satellite estimates also reveal substantial longitudinal variability in the anomaly fields, indicating that some Sahelo-Soudanian areas may receive above average rainfall during a year cataloged as dry. The latitudinal displacement and the extent of the cloud band associated with the intertropical convergence zone (ITCZ), as derived from cold cloud indices, indicate a northward displacement of the ITCZ in some, but not all, wet years in the Sahel. No systematic anomalous southward displacement of the ITCZ is evident in dry years. Drought in the Sahel appears to be more closely linked to the lattitudinal extent and the intensity of the convection within the ITCZ.

Ba, Mamoudou B.↗
NASA NTRS1993

Using AVIRIS for in-flight calibration of the spectral shifts of SPOT-HRV and of AVHRR?

The response of a satellite sensor varies during its lifetime; internal calibration devices can be used to follow the sensor degradation or in-flight calibrations are conducted from estimates of the radiance at satellite level for well predictable situations. Changes in gain are evaluated assuming that the spectral response of the sensor is stable with time; i.e., that the filter response as well as the optics or the electronics are not modified since the prelaunch determinations. Nevertheless, there is some evidence that the SPOT interferometer filters are affected by outgassing effects during the launch. Tests in vacuum chambers indicated a narrowing of the filters with a shift of the upper side towards the blue of about 10 nm which is more over consistant with the loss of gain observed during the launch. Also, during the lifetime of SPOT, the relationship between the loss of sensitivity and the filter bandwidth may correspond to this effect. On the other hand, the inconsistancy of the NOAA7 calibration between two methods (desert and ocean) having a different spectral sensitivity may indicate a spectral problem with a shift of the central wavelength of -20 nm. The basic idea here is to take advantage of the good spectral definition of AVIRIS to monitor these potential spectral degradations with an experimental opportunity provided by a field campaign held in La Crau (S.E. of France) in June 1991 which associated ground-based measurements and AVIRIS, SPOT2, NOAA-11 overpasses over both the calibration site of La Crau and an agricultural area.

Willart-Soufflet, Veronique↗
NASA NTRS2019

Calibration Plan for the Ocean Color Instrument (OCI) Engineering Test Unit

The basic product measured by OCI is the top-of atmosphere (TOA) radiance at different wavelengthsThree types of calibration/characterization are necessary for ocean color processing: - Prelaunch calibration/characterization (absolute/spectral calibration and image artifacts) - On-orbit calibration (solar diffuser and lunar measurements) - Vicarious calibration (in-situ measurements of water-leaving radiance)

Meister, Gerhard↗
DOE OSTI2025

Comparison of atomized mass and crater volume in laser ablation

The extent and dynamics of laser ablation are typically studied using crater imaging or by invoking the relationship between atomic emission and the mass removed. The former is a static view of a dynamic process and requires the accumulation of multiple shots in one location. The latter is complex and not absolute without calibration of the optical system with a standard of spectral radiance. We measure the mass of the atomized plume by laser atomic-absorption spectroscopy at 2 µs without external mass calibration; mass uncertainty in laser-ablation atomic absorption spectroscopy (LA-AAS) results from uncertainties in line area fitting, tabulated oscillator strengths, and partition functions as well as a <10% underrepresentation of the mass due to treating the plasma as a single thermodynamic equilibrium. The LA-AAS-measured mass pertains to the atoms in the probed charge states and does not include condensed or molecular species. The ablation efficiency at 300 mbar of helium varies significantly between the two focusing conditions used. A comparison of crater-derived masses and LA-AAS masses suggests that more defocused ablation may result in significant redeposition of material in the crater, distorting the conclusions from drilling studies and crater imaging. More focused ablation conditions result in crater-derived masses that exceed those measured with LA-AAS and suggest melt expulsion or phase explosion.

Merten, Jonathan [Arkansas State University, Jones↗
NASA NTRS2020

S-NPP and N20 VIIRS RSB Bands Detector-to-Detector Calibration Differences Assessment Using a Homogeneous Ground Target

The S-NPP and N20 satellites have successfully operated since their launches on October 28, 2011 and November 18, 2017, respectively. This paper provides an assessment of the detector calibration stability for the reflective solar bands (RSBs) observed from both S-NPP and N20 VIIRS. Top-of-atmosphere radiances from near-nadir observations over the homogeneous Libya 4 desert site are extracted from the S-NPP VIIRS Collection 1 and N20 Collection 2 Level-1B products. The radiances from individual detectors per Half‐angle Mirror side are studied. The comparisons of the normalized radiance to all detector average values indicate that the detector calibration differences are wavelength dependent. The S-NPP detector differences have been slowly increasing in the past 8.5 years and bands M1-M4 have 1.3%- 2.2% detector differences in 2019. N20 detector differences are stable and small in the past two years except SWIR M bands. N20 M10 and M11 have 1.3% and 2.1% detector differences, respectively. S-NPP DNB detector differences are about 0.8% and N20 DNB detector differences are about 0.5%. Most bands HAM side differences are less than 0.25% in the past years except N20 VIIRS M1 HAM side differences are 0.57% in 2018 and 0.54% in 2019. The Libya 4 images have small but noticeable striping in S-NPP M1-M4 data as well as in N20 M1, M8, M10, and M11 data. These study results have been applied in the S-NPP Collection 2 new algorithm to remove the detector differences. This research help scientists and VIIRS users better understand detector calibration differences in different version VIIRS products.

Libya 4↗
NASA NTRS2018

An Accurate Method for Correcting Spectral Convolution Errors in Intercalibration of Broadband and Hyperspectral Sensors

The intercalibration between a broadband and a hyperspectral satellite Earth observation system requires the convolution of the hyperspectral data with the spectral response functions (SRFs) of the corresponding broadband channels. There are two potential issues associated with the convolution procedure. First, the finite resolution of a hyperspectral spectrum, that is, the deviation from the highly accurate line-by-line monochromatic radiances, will contribute to convolution errors. The magnitude of the errors depends on the spectral resolution and the SRF shape of the hyperspectral instrument. This type of the convolution error has not been well recognized, and there is a lack of corresponding discussion in most published papers. Although it is small as compared with the instrument accuracy of existing hyperspectral sounders, the error is deemed to be signicant when it is compared with the stringent calibration requirement imposed by future climate missions like the Climate Absolute Radiance and Refractivity Observatory (CLARREO). Second, some broadband channels are insufficiently covered by the hyperspectral data, causing spectral gaps that lead to convolution errors. Although several methods have been developed to fill the spectral gaps and hence compensate for the second type of convolution error, the correction accuracy may still need improvement especially when a large spectral gap needs to be lled. This paper presents a methodology to accurately quantify and compensate for both types of convolution errors. This methodology utilizes the available hyperspectral information to correct the scene-dependent convolution errors due to either the limited spectral resolution or spectral gaps. We use simulations to characterize the intercalibration errors between the Moderate resolution Imaging Spectroradiometer (MODIS) and current operational infrared sounders. We demonstrate that convolution errors can be effectively removed to meet the highly accurate intersatellite calibration requirement proposed by the Climate Absolute Radiance and Refractivity Observatory. Our methodology is also validated using real satellite data for the intercalibration between Aqua MODIS and Aqua Atmospheric Infrared Sounders (AIRS). Our study demonstrates that the accurate characterization and correction for the convolution errors greatly reduces the scene-dependent and spectrally dependent errors, being critical to the consistency check between Infrared Atmospheric Sounding Interferometer (IASI) and AIRS using the double-difference method. The convolution correction also facilitates the evaluation for other intercalibration errors (e.g., the drift of MODIS SRFs). Our derived SRF shift values from MODIS-AIRS (after convolution error corrections) and from MODIS-IASI intercalibration are consistent with each other. We further extend the methodology to study the calibration of a broadband channel which is either completely or largely uncovered bya hyperspectral measurement.The large spectral gap-filling methodology is validated by demonstrating the accurate prediction of the MODIS radiance of band 29 using the Cross-track Infrared Sounder spectra, with the real IASI spectral data being used as the reference.

Correction Method↗
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 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 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 NTRS2019

Extreme Case of Spectral Band Difference Correction Between the OSIRIS-REX-NAVCAM2 and DSCOVR-EPIC Imagers

Earth-viewed images acquired during a recent asteroid intercept mission present a unique opportunity for radiometric calibration of visible imagers onboard a space exploration probe. Measurements from the CERES consistent DSCOVR-EPIC imager act as a reference in providing spatially, temporally, and angularly matched radiance values for deriving OSIRIS-REx-NavCam sensor calibration gains. The calibration is accomplished using an optimized all-sky tropical ocean ray-matching technique, which employs complex pixel remapping, navigation correction, and angular geometry consideration. Of critical consideration in this specific inter-calibration event is the extreme difference in spectral response function (SRF) width between the NavCam and EPIC imagers, which could cause a rather large bias. The NASA-LaRC SCIAMACHY based online spectral band adjustment factor (SBAF) calculation tool provides an empirical solution to such potential spectral-difference-induced biases through a high spectral- resolution hyper spectral convolution approach. The adjustments produced from this tool can effectively reduce the calibration gain bias of NavCam2 by nearly 6%, thereby adjusting the NavCam2 sensor to within 3.2% of its prelaunch calibration. These results highlight the capability of the SBAF tool to account for exceptionally disparate SRFs.

Scarino, Benjamin↗
NASA NTRS2019

Independent Calibration Approach for the CLARREO Pathfinder Mission

A CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF) mission has been funded to demonstrate retrieval of SI-traceable spectral reflectance with absolute uncertainty <0.3% (k=1). The mission consists of a Reflected Solar spectrometer that will be hosted on the International Space Station (ISS) in the 2023 timeframe and rely on a ratioing radiometer approach to retrieve the unprecedented accuracy. Demonstrating that the accuracy is achieved through an Independent Calibration effort similar in philosophy to the efforts in metrology laboratories relying on multiple, independent measurements to improve credibility for a sensor’s absolute and relative uncertainty error budgets. These measurements use different traceability paths and multiple instrument approaches and CPF’s Independent Calibration will be similar in this regard. The Independent Calibration relies on a pre-launch absolute radiometric calibration obtained from additional testing done after instrument thermal-vacuum (TVAC) testing. The added radiometric calibration is combined with a high fidelity instrument model to provide an on-orbit radiometric calibration independent from the ratioing radiometer approach. The current work describes the post-TVAC testing portion of the CPF Independent Calibration Plan and the Independent Model Development as well as planned on-orbit Evaluation of the Independent Calibration.

CLARREO Pathfinder↗
NASA NTRS2001

Hyperion On-Orbit Calibration Validation with AVIRIS in Argentina

This viewgraph presentation reviews the AVIRIS Argentina Campaign. 125 flight lines were collected for EO-1 science validation team and CONAE-funded investigators. The preliminary results from two vicarious calibration experiments conducted in Argentina are shown. AVIRIS has been shown to be well calibrated. Charts of optical depth measurements, calibration target measured surface reflectance, top-of atmosphere radiance, and images of various sites in Argentina are shown

imaging spectroscopy↗
NASA NTRSDate not supplied

TPSAS-NF1676L-32020-DND

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. The DSCOVR EPIC team released the version 2 dataset last year which included many enhancements, such as improved navigation, stray-light correction, and flat-fielding. Since there is no on-board calibration for EPIC, its 10 spectral channels must be calibrated using other methods, such as inter-calibrating with sensors with on-board calibration hardware. VIIRS is a well-calibrated instrument with similar spectral channels as EPIC. Spectral band induced radiance differences between VIIRS and EPIC are mitigated using Spectral Band Adjustment Factor (SBAF). We will extend the previous calibrations from prior studies to include more recent data by ray-matching EPIC with VIIRS over all-sky tropical ocean (ATO) and deep convective cloud (DCC) conditions. In addition to ATO and DCC ray-matching, we will validate these results by utilizing DCC as invariant targets to monitor sensor degradation. DCC behave as solar diffusers in the tropics and when collectively analyzed can be used to monitor the degradation of the EPIC sensor. Improvement to our dynamic navigation adjustment algorithm, as well as exploring the view angle response of the EPIC CCD array, will be examined for their effectiveness and presented at the conference.

C O Haney↗
NASA NTRS1996

Sea WiFS Technical Report Series: The fourth SeaWIFS Intercalibration Round-Robin Experiment (SIRREX-4), May 1995

This report documents the fourth Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Intercalibration Round-Robin Experiment (SIRREX-4), which was held at the National Institute of Standards and Technology (NIST) on 3-10 May 1995. The agenda for SIRREX-4 was established by a consensus reached at the conclusion of SIRREX-3: there should be an emphasis on training and work to foster and encourage uniform use of accepted protocols for calibrating radiometric instruments in the laboratory. The goal was to host the activity in a setting where proper techniques could be discussed and demonstrated. It seemed appealing to split the day between morning lectures and afternoon laboratory exercises or practicals. The former gave the user community a chance to present what was important to them and discuss it with acknowledged experts in radiometry, while the latter presented a unique opportunity for training and evaluation in the presence of these same experts. The five laboratory sessions were concerned with (1) determining the responsivity of a spectroradiometer and the spectral radiance of an unknown integrating sphere source, (2) demonstrating spectral field calibration procedures for an integrating sphere using three different instruments, (3) measuring spectral radiance using the plaque method, (4) setting up and aligning lamp calibration transfer standards using the NIST specifications for irradiance measurements, and (5) characterizing radiometric instruments. In addition to documenting some supplemental studies performed outside the laboratory sessions, this report includes an evaluation of the hardware that has been used during the SIRREX activities plus a critical evaluation of SIRREX objectives.

Johnson, B. Carol↗
NASA NTRS1989

Image processing software for providing radiometric inputs to land surface climatology models

During the First International Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE), 80 gigabytes of image data were generated from a variety of satellite and airborne sensors in a multidisciplinary attempt to study energy and mass exchange between the land surface and the atmosphere. To make these data readily available to researchers with a range of image data handling experience and capabilities, unique image-processing software was designed to perform a variety of nonstandard image-processing manipulations and to derive a set of standard-format image products. The nonconventional features of the software include: (1) adding new layers of geographic coordinates, and solar and viewing conditions to existing data; (2) providing image polygon extraction and calibration of data to at-sensor radiances; and, (3) generating standard-format derived image products that can be easily incorporated into radiometric or climatology models. The derived image products consist of easily handled ASCII descriptor files, byte image data files, and additional per-pixel integer data files (e.g., geographic coordinates, and sun and viewing conditions). Details of the solutions to the image-processing problems, the conventions adopted for handling a variety of satellite and aircraft image data, and the applicability of the output products to quantitative modeling are presented. They should be of general interest to future experiment and data-handling design considerations.

Newcomer, Jeffrey A.↗
NASA NTRS2000

MISR - Science Data Validation Plan

This Science Data Validation Plan describes the plans for validating a subset of the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 algorithms and data products and supplying top-of-atmosphere (TOA) radiances to the In-flight Radiometric Calibration and Characterization (IFRCC) subsystem for vicarious calibration.

MISR science data validation Plan↗