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A technique is described by which an ERTS investigator can obtain absolute target reflectances by correcting spacecraft radiance measurements for variable target irradiance, atmospheric attenuation, and atmospheric backscatter. A simple measuring instrument and the necessary atmospheric measurements are discussed, and examples demonstrate the nature and magnitude of the atmospheric corrections.
Purpose: Positron emission tomography (PET) imaging of yttrium-90 in the liver post radioembolization has been shown useful for personalized dosimetry calculations and evaluation of extrahepatic deposition. The purpose of this study was to quantify the benefits of several MR-based data correction approaches offered by using a combined PET/MR system to improve Y-90 PET imaging. In particular, the feasibility of motion and partial volume corrections were investigated in a controlled phantom study. Methods: The ACR phantom was filled with an initial concentration of 8 GBq of Y-90 solution resulting in a contrast of 10:1 between the hot cylinders and the background. Y-90 PET motion correction through motion estimates from MR navigators was evaluated by using a custom-built motion stage that simulated realistic amplitudes of respiration-induced liver motion. Finally, the feasibility of an MR-based partial volume correction method was evaluated using a wavelet decomposition approach. Results: Motion resulted in a large (∼40%) loss of contrast recovery for the 8 mm cylinder in the phantom, but was corrected for after MR-based motion correction was applied. Partial volume correction improved contrast recovery by 13% for the 8 mm cylinder. Conclusions: MR-based data correction improves Y-90 PET imaging on simultaneous PET/MR systems. Assessment of these methods must be studied further in the clinical setting.
The author has identified the following significant results. A technique is described by which an ERTS investigator can obtain absolute target reflectances by correcting spacecraft radiance measurements for variable target irradiance, atmospheric attenuation, and atmospheric backscatter. A simple measuring instrument and the necessary atmospheric measurements are discussed, and examples demonstrate the nature and magnitude of the atmospheric corrections. Preliminary results indicate that the radiant power measuring instrument will provide one technique for calibrating ERTS-1 data. The March 27, 1973 mission was significant in the NASA C-130 aircraft and ERTS-1 simultaneously passed over the test sites where RPMI's were being deployed to measure solar and atmospheric parameters and site reflectance.
A remote multiplexer/digitizer unit (RMDU), a part of the airborne integrated flight test data system, was subjected to an accuracy study. The study was designed to show the effects of temperature, altitude, and vibration on the RMDU. The RMDU was subjected to tests at temperatures from -54 C (-65 F) to 71 C (160 F), and the resulting data are presented here, along with a complete analysis of the effects. The methods and means used for obtaining correctable data and correcting the data are also discussed.
Geoid undulations derived from Doppler satellite positioning are compared with corresponding values derived from terrestrial and satellite information using three different procedures. Doppler undulations are compared with uncorrected gravimetric undulations, and systematic differences of 1.6 m and 0.4 m are found for western and eastern U.S. stations, respectively. The systematic difference of 1.6 m was reduced to 0.1 m when terrain-related corrections were applied. Undulations computed from a spherical harmonic expansion to degree 180 yielded standard deviations only slightly poorer than the combined data. A more systematic difference in the western than in the eastern stations remained.
Long exposures with the original Hubble Space Telescope (HST) Wide Field Camera (WFC) through the F555W and F785LP filters show gradients in the background following standard pipeline calibration. We show that these gradients also appear in stellar photometry, and thus must be predominantly the result of inaccurate flatfielding at a level of 10 to 20%. Color errors may be even larger. Applying corrections to the flatfield frames based on the background structure leads to an improved accuracy of approximately 4% for single-measurement photometry within a single CCD chip, compared to the approximately 10% accuracy suggested by previous studies. We have reanalyzed the F555W and F785LP calibration photometry to derive zero points appropriate for corrected data; these new zero points have internal consistency at a level of approximately 1.2%, based on comparison between the chip-to-chip offsets and the sky levels observed in corrected images. This indicates that relative photometry approaching 1 to 2% is achievable with the WFC. The new zero point values for corrected data are 22.90, 23.04, 23.04, and 22.96 (F555W), and 21.56, 21.64, 21.44, and 21.47 (F785LP) for chips WF1-WF4, respectively. Comparison is made with other zero points, and the applicability of 'delta flats' is briefly discussed.
A technique is described by which ERTS investigators can obtain and utilize solar and atmospheric parameters to transform spacecraft radiance measurements to absolute target reflectance signatures. A radiant power measuring instrument (RPMI) and its use in determining atmospheric paramaters needed for ground truth are discussed. The procedures used and results achieved in processing ERTS CCTs to correct for atmospheric parameters to obtain imagery are reviewed. Examples are given which demonstrate the nature and magnitude of atmospheric effects on computer classification programs.
To perform Micrometeoroid and Orbital Debris (MMOD) analyses, NASA describes the orbital debris particle environment using the ORDEM 3 tool and the micrometeoroid environment using the MEM 3 tool. Both output files that detail the flux of particles as a function of several parameters. European MMOD analyses use different tools to perform similar functions, including the Meteoroid And Space debris Terrestrial Environment Reference (MASTER) environment model, which outputs flux data in the Standard Environment Interface (STENVI) format. The NASA Johnson Space Center Hypervelocity Impact Technology Group was asked to create a converter to translate flux data from the output file formats used by ORDEM 3.x and MEM 3 into the STENVI file format. Validation was performed to ensure that the converter was reproducing the input data correctly. The Bumper 3 MMOD risk assessment tool has a capability for reading ORDEM 3.x, MEM 3, and STENVI environment file formats and was used to compare MMOD risk results generated using the converter’s output STENVI files to the risk results generated using the input ORDEM 3.x and MEM 3 igloo files. Specific point comparisons validated that the converter translated the environment data correctly, producing the intended output. However, realistic risk assessments showed that the bin methodology employed by Bumper for determining particle flux as a function of particle size when reading files in STENVI format produces much higher MMOD risk than the point-interpolation methodology used in Bumper risk assessments using ORDEM and MEM. Modifications to how Bumper 3 reads STENVI files during analyses are considered to improve Bumper’s ability to perform useful analyses with environment files in this format.
To perform Micrometeoroid and Orbital Debris (MMOD) analyses, NASA describes the orbital debris particle environment using the ORDEM 3 tool and the micrometeoroid environment using the MEM 3 tool. Both output files that detail the flux of particles as a function of several parameters. European MMOD analyses use different tools to perform similar functions, including the Meteoroid And Space debris Terrestrial Environment Reference (MASTER) environment model, which outputs flux data in the Standard Environment Interface (STENVI) format. The NASA Johnson Space Center Hypervelocity Impact Technology Group was asked to create a converter to translate flux data from the output file formats used by ORDEM 3.x and MEM 3 into the STENVI file format. Validation was performed to ensure that the converter was reproducing the input data correctly. The Bumper 3 MMOD risk assessment tool has a capability for reading ORDEM 3.x, MEM 3, and STENVI environment file formats and was used to compare MMOD risk results generated using the converter’s output STENVI files to the risk results generated using the input ORDEM 3.x and MEM 3 igloo files. Specific point comparisons validated that the converter translated the environment data correctly, producing the intended output. However, realistic risk assessments showed that the bin methodology employed by Bumper for determining particle flux as a function of particle size when reading files in STENVI format produces much higher MMOD risk than the point-interpolation methodology used in Bumper risk assessments using ORDEM and MEM. Modifications to how Bumper 3 reads STENVI files during analyses are considered to improve Bumper’s ability to perform useful analyses with environment files in this format.
The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility recently deployed its First ARM Mobile Facility (AMF1) to La Jolla, California as part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) campaign. Some of the goals behind EPCAPE were to characterize the diurnal and seasonal cycles of stratocumulus clouds and to investigate the cloud-aerosol-radiation interactions and feedbacks in the area. The deployment of the AMF1 for a full year from 15 February 2023 to 14 February 2024 aided in addressing these scientific questions. While AMF1 collected data year-round, enhanced measurements were taken during two intensive operational periods (IOPs). The first IOP occurred from April to June and focused on the chemistry of low clouds (EPCAPE_Chem), while the second IOP occurred from July to September and was focused on the radiation of high clouds (EPCAPE_Radiation). Several cloud radars were deployed with AMF1 to collect valuable data on cloud properties that will help users address key science objectives. As in past ARM campaigns, a1-level radar data is extensively analyzed and calibration techniques are performed to generate b1-level data (Matthews et al. 2023, Feng et al. 2024). Radar data at the b1-level are of the highest quality and thus can be used to examine scientific questions. The status of the a1-level data and the a1-to-b1 process for the EPCAPE radars is subsequently detailed in this document.
The ability of the soft matter interfaces beamline at National Synchrotron Light Source II to access x-ray energy in the tender x-ray regime, i.e., from 2.1 to 5 keV, enables new resonant x-ray scattering studies at the sulfur K-edge and others. We present a new approach to correct data acquired in the tender x-ray regime with a Pilatus3 detector in order to improve the data quality and to correct the various artifacts inherent to hybrid pixel detectors, such as variations in modules’ efficiency or noisy detector module junctions. Further, this new flatfielding significantly enhances the data quality and enables detection of weak scattering signals.
The Long Term Data Record (LTDR) project has the goal of developing a quality and consistent surface reflectance product from coarse resolution optical sensors. This paper focuses on the Advanced Very High Resolution Radiometer (AVHRR) part of the record, using the Moderate Resolution Imaging Spectrometer (MODIS) instrument as a reference. When a surface reflectance time series is acquired from satellites with variable observation geometry, the directional variation generates an apparent noise which can be corrected by modeling the bidirectional reflectance distribution function (BRDF). The VJB (Vermote, Justice and Bréon, 2009) method estimates a target’s BRDF shape using 5 years of observation and corrects for directional effects maintaining the high temporal resolution of the measurement using the instantaneous Normalized Difference Vegetation Index (NDVI). The method was originally established on MODIS data but its viability and optimization for AVHRR data have not been fully explored. In this study we analyze different approaches to find the most robust way of applying the VJB correction to AVHRR data, considering that high noise in the red band (B1) caused by atmospheric effect makes the VJB method unstable. Firstly, our results show that for coarse spatial resolution, where the vegetation dynamics of the target don’t change significantly, deriving BRDF parameters from 15+ years of observations reduces the average noise by up to 7% in the Near Infrared (NIR) band and 6% in the NDVI, in comparison to using 3-year windows. Secondly, we find that the VJB method can be modified for AVHRR data to improve the robustness of the correction parameters and decrease the noise by an extra 8% and 9% in the red and NIR bands with respect to using the classical VJB inversion. We do this by using the Stable method, which obtains the volumetric BRDF parameter (V) based on its NDVI dependency, and then obtains the geometric BRDF parameter (R) through the inversion of just one parameter.
Laboratory test set for integration of data compression and error correction encoding of digital communications system
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The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed the first ARM Mobile Facility (AMF1) to Houston, Texas for the Tracking Aerosol Convection Interactions Experiment (TRACER) field campaign. The TRACER campaign was conducted from October 1, 2021 to September 30, 2022, with an intensive operational period (IOP) from June 1 to September 30, 2022.
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed the second ARM Mobile Facility (AMF2) near Crested Butte, Colorado for the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign. The SAIL campaign occurred from September 1, 2021, to June 15 2023. To study the water cycle in the East River Watershed, ARM deployed a vertically pointing Ka-band ARM Zenith radar (KAZR) and a scanning X-band precipitation radar managed by Colorado State University (CSU XPRECIP), as shown in Figure 1.
Assembly drawings, logic schematics, and circuit schematics useful in maintaining the equipment of the DC/EC digital test system are reviewed. The drawings are organized in accordance with the reference designations of the hardware. The transmitter subsystem assembly drawings are emphasized.
An overall block diagram of the DC/EC digital system test is shown. The system is divided into two major units: the transmitter and the receiver. In operation, the transmitter and receiver are connected only by a real or simulated transmission link. The system inputs consist of: (1) standard format TV video, (2) two channels of analog voice, and (3) one serial PCM bit stream.