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All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Wind tunnel experiments will continue to be a primary source of validation data for many types of mathematical and computational models in the aerospace industry. The increased emphasis on accuracy of data acquired from these facilities requires understanding of the uncertainty of not only the measurement data but also any correction applied to the data. One of the largest and most critical corrections made to these data is due to wall interference. In an effort to understand the accuracy and suitability of these corrections, a statistical validation process for wall interference correction methods has been developed. This process is based on the use of independent cases which, after correction, are expected to produce the same result. Comparison of these independent cases with respect to the uncertainty in the correction process establishes a domain of applicability based on the capability of the method to provide reasonable corrections with respect to customer accuracy requirements. The statistical validation method was applied to the version of the Transonic Wall Interference Correction System (TWICS) recently implemented in the National Transonic Facility at NASA Langley Research Center. The TWICS code generates corrections for solid and slotted wall interference in the model pitch plane based on boundary pressure measurements. Before validation could be performed on this method, it was necessary to calibrate the ventilated wall boundary condition parameters. Discrimination comparisons are used to determine the most representative of three linear boundary condition models which have historically been used to represent longitudinally slotted test section walls. Of the three linear boundary condition models implemented for ventilated walls, the general slotted wall model was the most representative of the data. The TWICS code using the calibrated general slotted wall model was found to be valid to within the process uncertainty for test section Mach numbers less than or equal to 0.60. The scatter among the mean corrected results of the bodies of revolution validation cases was within one count of drag on a typical transport aircraft configuration for Mach numbers at or below 0.80 and two counts of drag for Mach numbers at or below 0.90.

Walker, Eric L.↗
NASA NTRS2020

Land-cover Change in the Caucasus Mountains Since 1987 Based on the Topographic Correction of Multi-temporal Landsat Composites

Mountainous regions are changing rapidly across the world due to both land-use change and climate change. Given the importance of mountainous regions for ecosystem services and endemic biodiversity, monitoring these changes is essential. Satellite data provide a great resource to map land-cover change in mountainous regions, however mapping is especially challenging there because topographic complexity affects reflectance. The so called ‘topographic effect’ has been successfully corrected for in case studies of small areas, but a comparison of large-area classifications and land-cover change analyses with and without topographic correction is missing. Here, we performed a long-term land-cover change assessment for a large mountainous region, i.e., the Caucasus Mountains with topographic correction. Our two goals were 1) to examine the effect of topographic correction on land-cover classification for a large mountainous region, and 2) to assess land-cover changes since 1987 across the Caucasus based on the full Landsat archive. Both the complex topography and the history of land-use changes, especially after the collapse of the Soviet Union in 1991, make the Caucasus Mountains an ideal study area to understand topographic effects on large-area land-cover mapping for the last three decades. First, we compared a non-topographically-corrected Landsat classification for 2015 with a classification that was topographically-corrected with an enhanced C-correction for the same year and assessed the accuracy of both. Second, we derived topographically-corrected Landsat classifications for six dates to assess changes in cropland and forest from 1987 to 2015, based on class probabilities and post-classification comparisons. In regard to our first goal, topographic correction improved the overall accuracy of the classification only by 2% (from 79 to 81%), but disagreement rates were as high as 100% in mountainous regions, especially among forest types. In regard to our second goal, we found that cropland loss was the most prevalent change process since 1987. Cropland loss was particularly widespread in Georgia and Armenia until 2000, and in Azerbaijan until 2005. The North Caucasus (the Russian Federation) had more stable cropland over time, most likely due to different land reforms after the collapse of the Soviet Union, and the prevalence of flat landscapes and very fertile soils, which make cultivation easier than in the South Caucasus. Rates of forest change throughout the Caucasus Mountains were surprisingly low, with forest loss and forest gain was most likely due to cropland abandonment and less grazing pressure. Our results highlight both the importance and the feasibility of topographic correction for accurate large-area land-cover classifications in steep terrain.

Large-area mapping↗
NASA NTRS2014

Characterization of Artifacts Introduced by the Empirical Volcano-Scan Atmospheric Correction Commonly Applied to CRISM and OMEGA Near-Infrared Spectra

The empirical volcano-scan atmospheric correction is widely applied to Martian near infrared CRISM and OMEGA spectra between 1000 and 2600 nanometers to remove prominent atmospheric gas absorptions with minimal computational investment. This correction method employs division by a scaled empirically-derived atmospheric transmission spectrum that is generated from observations of the Martian surface in which different path lengths through the atmosphere were measured and transmission calculated using the Beer-Lambert Law. Identifying and characterizing both artifacts and residual atmospheric features left by the volcano-scan correction is important for robust interpretation of CRISM and OMEGA volcano scan corrected spectra. In order to identify and determine the cause of spectral artifacts introduced by the volcano-scan correction, we simulated this correction using a multiple scattering radiative transfer algorithm (DISORT). Simulated transmission spectra that are similar to actual CRISM- and OMEGA-derived transmission spectra were generated from modeled Olympus Mons base and summit spectra. Results from the simulations were used to investigate the validity of assumptions inherent in the volcano-scan correction and to identify artifacts introduced by this method of atmospheric correction. We found that the most prominent artifact, a bowl-shaped feature centered near 2000 nanometers, is caused by the inaccurate assumption that absorption coefficients of CO2 in the Martian atmosphere are independent of column density. In addition, spectral albedo and slope are modified by atmospheric aerosols. Residual atmospheric contributions that are caused by variable amounts of dust aerosols, ice aerosols, and water vapor are characterized by the analysis of CRISM volcano-scan corrected spectra from the same location acquired at different times under variable atmospheric conditions.

OMEGA Near Infrared↗
NASA NTRS2016

Limb Correction of Polar-Orbiting Imagery for the Improved Interpretation of RGB Composites

Red-Green-Blue (RGB) composite imagery combines information from several spectral channels into one image to aid in the operational analysis of atmospheric processes. However, infrared channels are adversely affected by the limb effect, the result of an increase in optical path length of the absorbing atmosphere between the satellite and the earth as viewing zenith angle increases. This paper reviews a newly developed technique to quickly correct for limb effects in both clear and cloudy regions using latitudinally and seasonally varying limb correction coefficients for real-time applications. These limb correction coefficients account for the increase in optical path length in order to produce limb-corrected RGB composites. The improved utility of a limb-corrected Air Mass RGB composite from the application of this approach is demonstrated using Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. However, the limb correction can be applied to any polar-orbiting sensor infrared channels, provided the proper limb correction coefficients are calculated. Corrected RGB composites provide multiple advantages over uncorrected RGB composites, including increased confidence in the interpretation of RGB features, improved situational awareness for operational forecasters, and the ability to use RGB composites from multiple sensors jointly to increase the temporal frequency of observations.

satellite imagery↗
NASA NTRS2022

An Adaptation of ISO 11204 using Customized Correction Grades to Mitigate Ambient Noise Effects when Computing Sonic Boom Loudness Levels

A spectral-based correction adapted from ISO 11204 [1] is investigated here to mitigate the effects of ambient noise contamination of sonic booms recorded by noise monitors during field tests. The algorithm from sections 5.4.2 and 7 of ISO 11204 is customized using six nonstandard correction grades in addition to implementing the two standardized grades described in ISO 11204. The six nonstandard grades allow for more aggressive correction of the levels of the sonic boom spectrum when they are proximate to the ambient spectrum. Of the eight correction grades, the most aggressive custom correction grade, termed “Custom F” here, performed best under the conditions that were studied. Consequently, “Custom F” is recommended for use when processing in-field recordings of X-59 sonic booms. To evaluate the eight correction grades, mock X-59 acoustic recordings were generated using predicted ground-level X-59 sonic booms. These ground-level waveforms were created by Doebler [2] by propagating nearfield CFD solutions of the X-59 C612A configuration to the ground using PCBoom [3] (please see Acknowledgements and Refs. [4, 5, 2, 6]). To generate the mock acoustic recordings from those ground-level waveforms, they were further modified using turbulence filters developed during the NASA SonicBAT effort [7], post boom noise audio clips from the NASA SonicBAT tests [7], and ambient noise from the NASA QSF18 test [8, 9]. These mock acoustic recordings enabled evaluation of the ambient noise mitigation methods since the proper loudness levels of the X-59 waveforms in absence of ambient noise are known. Specifically, these known levels provide a benchmark against which the corrected loudness levels are compared, where the corrected loudness levels are computed when ambient noise is present within the waveforms. Importantly, similar analyses using in-field recordings are not possible since the proper loudness levels of the sonic boom waveforms in absence of ambient noise are unknowable when analyzing in-field recordings. Consequently, if additional analyses of ambient noise mitigation methods are needed, then use of mock recordings like those used here is recommended.

Sonic boom↗
NASA NTRS1981

Ellipsoidal corrections for geoid undulation computations using gravity anomalies in a cap

Ellipsoidal correction terms have been derived for geoid undulation computations when the Stokes equation using gravity anomalies in a cap is combined with potential coefficient information. The correction terms are long wavelength and depend on the cap size in which its gravity anomalies are given. Using the regular Stokes equation, the maximum correction for a cap size of 20 deg is -33 cm, which reduces to -27 cm when the Stokes function is modified by subtracting the value of the Stokes function at the cap radius. Ellipsoidal correction terms were also derived for the well-known Marsh/Chang geoids. When no gravity was used, the correction could reach 101 cm, while for a cap size of 20 deg the maximum correction was -45 cm. Global correction maps are given for a number of different cases. For work requiring accurate geoid computations these correction terms should be applied.

Rapp, R. H.↗
NASA NTRS1984

Wind tunnel wall interference correction for aircraft models

Wall interference correction procedures seek to determine the required changes in certain flow or geometric parameters so that the difference between the flow properties at the model's surface in the tunnel and free air are minimized. A transonic and a linear correction procedure were developed for aircraft models. In addition to Mach number and angle of attack corrections, an estimate of the accuracy of the corrections is provided by the transonic correction procedure. Lift, pitching moment and pressure measurements near the tunnel walls are required. The efficiency and accuracy of the correction procedure are improved. Moreover, correction of both the wing and tail angles of attack is allowed. The procedure is valid for transonic as well as subcritical flows. However, for subcritical flows further approximations and simplifying assumptions are made, leading to a very simple and efficient correction procedure.

Rizk, M. H.↗
NASA NTRS1983

Determination of corrections to flow direction measurements obtained with a wing-tip mounted sensor

The nature of corrections for flow direction measurements obtained with a wing-tip mounted sensor was investigated. Corrections for the angle of attack and sideslip, measured by sensors mounted in front of each wing tip of a general aviation airplane, were determined. These flow corrections were obtained from both wind-tunnel and flight tests over a large angle-of-attack range. Both the angle-of-attack and angle-of-sideslip flow corrections were found to be substantial. The corrections were a function of the angle of attack and angle of sideslip. The effects of wing configuration changes, small changes in Reynolds number, and spinning rotation on the angle-of-attack flow correction were found to be small. The angle-of-attack flow correction determined from the static wind-tunnel tests agreed reasonably well with the correction determined from flight tests.

Moul, T. M.↗
NASA NTRS1994

Correlated environmental corrections in TOPEX/POSEIDON, with a note on ionospheric accuracy

Estimates of the effectiveness of an altimetric correction, and interpretation of sea level variability as a response to atmospheric forcing, both depend upon assuming that residual errors in altimetric corrections are uncorrelated among themselves and with residual sea level, or knowing the correlations. Not surprisingly, many corrections are highly correlated since they involve atmospheric properties and the ocean surface's response to them. The full corrections (including their geographically varying time mean values), show correlations between electromagnetic bias (mostly the height of wind waves) and either atmospheric pressure or water vapor of -40%, and between atmospheric pressure and water vapor of 28%. In the more commonly used collinear differences (after removal of the geographically varying time mean), atmospheric pressure and wave height show a -30% correlation, atmospheric pressure and water vapor a -10% correlation, both pressure and water vapor a 7% correlation with residual sea level, and a bit surprisingly, ionospheric electron content and wave height a 15% correlation. Only the ocean tide is totally uncorrelated with other corrections or residual sea level. The effectiveness of three ionospheric corrections (TOPEX dual-frequency, a smoothed version of the TOPEX dual-frequency, and Doppler orbitography and radiopositioning integrated by satellite (DORIS) is also evaluated in terms of their reduction in variance of residual sea level. Smooth (90-200 km along-track) versions of the dual-frequency altimeter ionosphere perform best both globally and within 20 deg in latitude from the equator. The noise variance in the 1/s TOPEX inospheric samples is approximately (11 mm) squared, about the same as noise in the DORIS-based correction; however, the latter has its error over scales of order 10(exp 3) km. Within 20 deg of the equator, the DORIS-based correction adds (14 mm) squared to the residual sea level variance.

Zlotnicki, V.↗
NASA NTRS1996

A New Correction Technique for Strain-Gage Measurements Acquired in Transient-Temperature Environments

Significant strain-gage errors may exist in measurements acquired in transient-temperature environments if conventional correction methods are applied. As heating or cooling rates increase, temperature gradients between the strain-gage sensor and substrate surface increase proportionally. These temperature gradients introduce strain-measurement errors that are currently neglected in both conventional strain-correction theory and practice. Therefore, the conventional correction theory has been modified to account for these errors. A new experimental method has been developed to correct strain-gage measurements acquired in environments experiencing significant temperature transients. The new correction technique has been demonstrated through a series of tests in which strain measurements were acquired for temperature-rise rates ranging from 1 to greater than 100 degrees F/sec. Strain-gage data from these tests have been corrected with both the new and conventional methods and then compared with an analysis. Results show that, for temperature-rise rates greater than 10 degrees F/sec, the strain measurements corrected with the conventional technique produced strain errors that deviated from analysis by as much as 45 percent, whereas results corrected with the new technique were in good agreement with analytical results.

Richards, W. Lance↗
NASA NTRS2011

Correcting Attenuation of Reflectivity in Terminal Doppler Weather Radar

This paper documents the implementation of the algorithm for correcting attenuations in the TDWR reflectivity, and examines the impacts of performing the correction algorithm on the accuracy of the resultant precipitation products on the basis of stage IV gauge-radar analyses over six storm events (four warm season events and two cool season events). Three primary findings are summarized below: 1. Correcting for attenuation tends to improve the overall bias, the conditional bias, and the correlation between the TDWR-based rainfall estimates and stage IV values regardless of season and correction schemes. 2. Attenuation correction is overall beneficial to the accuracy of resulting rainfall estimates for the warm season. By contrast, for the cool season, despite potential improvements in the bias and correlation, attenuation correction can be undesirable when there is clear evidence of bright band enhancement arising from low freezing levels. To elaborate, in these situations spurious high precipitation rates over the melting layer can yield elevated values in specific attenuation factor K, which in turn, may lead to an artificially higher reflectivity adjustment at farther range. 3. Ingesting 3-D spatially variable RUC temperature and imposing a temperature threshold in general tend to degrade the accuracy of corrected rainfall estimates for the warm season. For the cool season, in theory they would help avoid applying correction to areas within and above the melting layer. In practice, due to the variable depth of the melting layer below the freezing level, it is difficult to determine the temperature for the lower boundary of the melting layer a priori.

Ding, Feng↗
NASA NTRS2012

Correction Technique for Raman Water Vapor Lidar Signal-Dependent Bias and Suitability for Water Wapor Trend Monitoring in the Upper Troposphere

The MOHAVE-2009 campaign brought together diverse instrumentation for measuring atmospheric water vapor. We report on the participation of the ALVICE (Atmospheric Laboratory for Validation, Interagency Collaboration and Education) mobile laboratory in the MOHAVE-2009 campaign. In appendices we also report on the performance of the corrected Vaisala RS92 radiosonde measurements during the campaign, on a new radiosonde based calibration algorithm that reduces the influence of atmospheric variability on the derived calibration constant, and on other results of the ALVICE deployment. The MOHAVE-2009 campaign permitted the Raman lidar systems participating to discover and address measurement biases in the upper troposphere and lower stratosphere. The ALVICE lidar system was found to possess a wet bias which was attributed to fluorescence of insect material that was deposited on the telescope early in the mission. Other sources of wet biases are discussed and data from other Raman lidar systems are investigated, revealing that wet biases in upper tropospheric (UT) and lower stratospheric (LS) water vapor measurements appear to be quite common in Raman lidar systems. Lower stratospheric climatology of water vapor is investigated both as a means to check for the existence of these wet biases in Raman lidar data and as a source of correction for the bias. A correction technique is derived and applied to the ALVICE lidar water vapor profiles. Good agreement is found between corrected ALVICE lidar measurments and those of RS92, frost point hygrometer and total column water. The correction is offered as a general method to both quality control Raman water vapor lidar data and to correct those data that have signal-dependent bias. The influence of the correction is shown to be small at regions in the upper troposphere where recent work indicates detection of trends in atmospheric water vapor may be most robust. The correction shown here holds promise for permitting useful upper tropospheric water vapor profiles to be consistently measured by Raman lidar within NDACC (Network for the Detection of Atmospheric Composition Change) and elsewhere, despite the prevalence of instrumental and atmospheric effects that can contaminate the very low signal to noise measurements in the UT.

MOHAVE-2009↗
NASA NTRSDate not supplied

Transonic Correction to Theodorsen's Theory for Oscillating Airfoil in Pitch and Plunge Toward Flutter

This paper presents a transonic correction method for an oscillating airfoil in pitch and plunge. The proposed method applies correction functions to the Theodorsen’s theory to capture the transonic nonlinear aero- dynamics. These correction functions apply necessary corrections to the amplitudes and the phase angles of the unsteady lift and pitching moment coefficients to account for transonic aerodynamics. The proposed method also postulates a correction for the motion of the aerodynamic center which could be induced by moving shocks. A series of unsteady RANS CFD simulations of the airfoil at the mean aerodynamic chord of the Transonic Truss-Braced Wing aircraft are conducted using FUN3D to provide data to construct these transonic correction functions. The computed responses of the unsteady lift and pitching moment coefficients using these transonic correction functions match the CFD simulation results very well even when the pitching moment coefficient is highly nonlinear. A flutter analysis of an airfoil in pitch and plunge illustrates the potential use of the proposed transonic correction method.

Transonic Flutter↗
NASA NTRS2014

Extending 3D Near-Cloud Corrections from Shorter to Longer Wavelengths

Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

aerosol optical depth↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗
NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗
NASA NTRS1976

Absolute oscillator strengths for the iron group - A correction to the data of Warner for the second spectra and a comment on some of the semiempirical results of Kurucz and Peytremann

It has already been shown that the Fe II absolute oscillator strengths (f-values) measured by Warner (1967) contain a systematic error, the magnitude of which depends on the energy of the transition's upper level. The present paper demonstrates that this error affects all of Warner's oscillator strengths for the second spectra of the iron group and develops a correction formula for Warner's results. A comparison of the corrected f-values with other measured f-values for Ti II, V II, and Fe II indicates that the correction improves the usefulness of Warner's data and that the corrected f-values have no large systematic dependence on wavelength, level energy, or line strength. Solar abundances for iron-group elements computed using the original and corrected f-values are compared with recently suggested abundances, and it is found that the corrected f-values yield more consistent results. Semiempirical oscillator strengths calculated by Kurucz and Peytremann (1975) for Fe I, Ti II, and V II are also compared with measured data to evaluate the accuracy of the calculations. It is found that the absolute scales of these results are roughly correct, but some of them are subject to very large errors.

Smith, P. L.↗
NASA NTRS1982

LANDSAT-D accelerated payload correction subsystem output computer compatible tape format

The NASA GSFC LANDSAT-D Ground Segment (GS) is developing an Accelerated Payload Correction Subsystem (APCS) to provide Thematic Mapper (TM) image correction data to be used outside the GS. This correction data is computed from a subset of the TM Payload Correction Data (PCD), which is downlinked from the spacecraft in a 32 Kbps data stream, and mirror scan correction data (MSCD), which is extracted from the wideband video data. This correction data is generated in the GS Thematic Mapper Mission Management Facility (MMF-T), and is recorded on a 9-track 1600 bit per inch computer compatible tape (CCT). This CCT is known as a APCS Output CCT (AOT). The AOT follows standardized corrections with respect to data formats, record construction and record identification. Applicable documents are delineated; common conventions which are used in further defining the structure, format and content of the AOT are defined; and the structure and content of the AOT are described.

Source record↗