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At least 271 records · Page 15

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Development of a Consistent MODIS and VIIRS Cloud Detection Approach for CERES

A consistent cloud fraction record across various satellite platforms is essential for maintaining a long-term and stable climate data record of Earth's energy budget. With the Aqua satellite nearing the end of its operational lifetime, the continuation of this record relies on utilizing VIIRS observations from NOAA20 for cloud detection in NASA’s Clouds and Earth’s Radiant Energy System (CERES) project. However, integrating data from VIIRS and MODIS instruments poses challenges due to their distinct characteristics, such as varying spatial resolutions and different spectral channels. As a result, deriving consistent cloud properties from these two sensors without introducing artificial discontinuities in the time series remains a complex and challenging task. This paper will present progress toward developing a unified MODIS and VIIRS cloud mask using common channels to produce consistent cloud properties for CERES next edition (Ed5) Earth radiation budget data products. The fundamental approach taken in the CERES cloud mask is to compare the observed radiances to the expected background clear sky radiances. Therefore, one vital step is to compute clear sky radiances with a radiative transfer model that accurately accounts for satellite-specific, spectrally dependent surface reflectance, surface emission, and atmospheric absorption. Refined radiative transfer models and updated ancillary data inputs including surface emissivity maps, IGBP, snow and ice maps are incorporated into the processing framework to improve cloud detection consistency and accuracy. Pixel level cloud mask results and monthly global cloud fraction comparisons between MODIS and VIIRS will be presented to evaluate their consistency. Remaining challenges will be discussed. It is expected that this work will contribute consistent cloud properties for CERES that adequately bridges the MODIS and VIIRS imager data records.

CERES↗

DOE OSTI2025

SITCOMTN-165: Surface brightness profiles around massive galaxies in LSSTComCam data

Low surface brightness photometry of massive galaxies can probe the extended stellar halos and intracluster light but is often limited by background subtraction and masking systematics. Here we present radial surface brightness profiles for the brightest cluster galaxy of Abell 360 and 2dFGRS TGS323Z113 using Rubin Observatory Commissioning Camera (LSSTComCam) Data Preview 1 in the g, r, and z bands. Our results show that the LSSTComCam data can go down to ~28 mag arcsec^-2 in the r band. Comparison to DECaLS measurements processed with Legacyhalos shows good agreement of surface brightness profiles at small radii while the LSSTComCam data extend deeper at larger radii.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2008

The Bess Investigation of the Origin of Cosmic-ray Antiprotons and Search for Cosmological Antimatter

The Balloon-borne Experiment with a Superconducting Spectrometer (BESS) collaboration has made precise measurements of the spectra of cosmic ray antiprotons and light nuclei and conducted a sensitive search for antinuclei. Ten BESS high-latitude flights, eight from Canada and two from Antarctica, span more than a Solar cycle between 1993 and 2007/2008. BESS measurements of low-energy antiprotons constrain candidate models for dark matter including the possible signature of primordial black hole evaporation. The stringent BESS measurements of antiprotons and the elemental and isotopic spectra of H and He provide strong constraints on models of cosmic-ray transport in the Galaxy and Solar System. BESS has also reported the first antideuterium upper limit. BESS employs a superconducting magnetic-rigity spectrometer with time-of-flight and aerogel Cherenkov detectors to identify incident particles by charge, charge sign, mass, and energy. The BESS-Polar long-duration instrument has reduced lower energy limit of 100 MeV (top of the atmosphere) to increase its sensitivity to possible primary antiproton sources. BESS-Polar II was rebuilt with extended magnet lifetime, improved detector and electronic performance, and greater data storage capacity. It was flown fro Antarctica December 2007-January 2008, recording about 4.6 bission events during 24.5 days at float altitude with the magnet on. During the flight the influence of a high-speed stream in the Solar wind was observed. Details of the BESS-Polar II instrument and flight performance are reported elsewhere at this conference. The successful BESS-Polar II flight at Solar minimum is especially important. Most cosmic-ray antiprotons are secondary products of nuclear interactions of primary cosmic-ray nuclei with the interstellar gas, giving a spectrum that peaks at about 2 GeV and falls rapidly to higher and lower energies. However, BESS data taken in the previous Solar minimum show a small excess over secondary expectations at low energies, possibly suggesting the presence of an additional component that may be masked at higher levels of Solar modulation. The high-statistics Solar minimum data obtained by BESS-Polar II will provide a difinitive test of this component. We will review the BESS program and report the latest results including the antiproton and proton spectra measured in the BESS-Polar I flight, the search for cosmic antinuclei, and the status of the BESS-Polar II analysis.

Mitchell, John↗

DOE OSTI2019

Pan-arctic river bank erosion and accretion, and planform metrics measured over intervals ranging from 1973 to 2016

This dataset provides the tabular summary of analysis of 17 reaches of 15 Arctic rivers for river bank erosion and accretion rates, as well as, river channel properties such as channel width, bank curvature, and the aspect/orientation of the river banks. These rivers include the: Chandalar River, Alaska, Colville River, Alaska; Indigirka River, Russia; Kolyma River, Russia; Koyukuk River, Alaska; Lena River, Alaska; Noatak River, Alaska; Ob River, Russia; Pechora River, Russia; Tanana River, Alaska, Selawik River, Alaska; Taz River, Russia; Yana River, Russia; Yenisei River, Russia; and the Yukon River, Alaska. The dataset was generated from a total of 129 images including: Landsat, higher resolution satellite imagery, and aerial photography over time periods ranging from the 1970s and 2016. A full list of the image dates, row and path (for Landsat), and pixel resolutions is provided in the dataset. Masks for the Chandalar River, Tanana River, and Yukon at Holy Cross were obtained from Brown et al. (2020). The masks were analyzed using the Spatially Continuous Riverbank Erosion and Accretion Measurements (SCREAM) software detailed in Rowland et al. 2016. The masks used in this analysis can be found an accompanying dataset (doi:10.15485/1571527).In files with “summary” in the name, the data is provided at a pixel level, where each mapped bank pixel has an associated erosion or accretion value, a channel width, a curvature value, and an aspect each river and time period will have an individual file. Files with “Segments” in name provide data that is averaged along segments of the rivers. These data are consolidated into a single file each for the erosion and accretion measurements. These segments are approximately 10 channel widths in length. In addition to erosion and accretion rates, the segment-based results include area measurements of erosion and accretion, islands, and channels. Revisions 2023:-Data added for the Koyukuk River for time periods of 1978-2012, 1978-2018, and 2012-2018. ---Data added from the Chandalar River, Tanana River, and Yukon River at Holy Cross based on masks obtained from Brown et al. (2020).-Updated the values for Drainage area and river slope, see methods below-Added values for meant topographic slope for upstream contributing area, long term averaged annual maximum monthly flow, average annual maximum monthly flow for the time period of erosion record, and added the river slope extracted from the Lin et al. (2020) data product.-Add field for River Planform Multi threaded (M) or Single threaded-Added ‘ConsolidatedErosionSegments.csv’ which provides the same data as AllRiversErosionSegments.csv rebinned with averages along river segments based on upstream drainage area instead of channel segments based on lengths set to approximately 10 channel widths.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1978

LANDSAT image differencing as an automated land cover change detection technique

Image differencing was investigated as a technique for use with LANDSAT digital data to delineate areas of land cover change in an urban environment. LANDSAT data collected in April 1973 and April 1975 for Austin, Texas, were geometrically corrected and precisely registered to United States Geological Survey 7.5-minute quadrangle maps. At each pixel location reflectance values for the corresponding bands were subtracted to produce four difference images. Areas of major reflectance differences are isolated by thresholding each of the difference images. The resulting images are combined to obtain an image data set to total change. These areas of reflectance differences were found, in general, to correspond to areas of land cover change. Information on areas of land cover change was incorporated into a procedure to mask out all nonchange areas and perform an unsupervised classification only for data in the change areas. This procedure identified three broad categories: (1) areas of high reflectance (construction or extractive), (2) changes in agricultural areas, and (3) areas of confusion between agricultural and other areas.

Stauffer, M. L.↗

DOE OSTI2021

Pink-beam serial femtosecond crystallography for accurate structure factor determination at an X-ray free-electron laser

Diffraction images with crystal hits from the large bandwidth (2.2 % BW) data set (thaumatin 6), and nominal SASE (0.17 % BW) data set (thaumatin 8 + thaumatin 10) with bad pixel masks, online indexing results and CrystFEL stream files from final processing.

Alvra↗

DOE OSTI2021

KAZRCORGE

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorge.c1 (ge=general sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

KAZRCORMD

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcormd.c1 (md=moderate sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

KAZRCORHI

For the Ka ARM Zenith Radar (KAZR) data stream, kazrcorhi.c1 (hi=high sensitivity), produces significant detection mask, corrects reflectivity for gaseous attenuation, and dealiases mean Doppler velocity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

KAZRCORGE-c0

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

KAZRCORHI-c0

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

KAZRCORMD-c0

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

CSAPR2 cell-tracking data collected during TRACER

One of the challenges of analyzing convective cell properties is quick evolution of the individual convective cells. While the operational radar data provide great a data set to analyze the evolution of radar observables of convective precipitation clouds statistically, previous studies also suggested that, because of the quick evolution of cell life cycle, conventional radar volume scan strategies taking ~5-7 minutes might not capture the detailed evolution. The TRACER campaign deployed CSAPR2, which performed frequent update of RHI and sector PPI scans to track convective cells every < 2 minutes guided by a new cell-tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. The submitted data files are CSAPR2 data in CfRadial format collected during the TRACER field campaign from June to September 2020. The data files include processed radar variables including: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1992

Some observations on spin detector response during Galileo high gain antenna deployment

This paper summarizes a dynamic analysis conducted in support of the investigation of the anomalous deployment of the Galileo High Gain Antenna on April 11, 1991. The work was focused on modeling the spacecraft spin dynamics to predict and compare the spin detector telemetry during the antenna deployment for possible cause scenarios. The effects of analog and digital low-pass filtering, digitization, and telemetry on the reported spin rate were studied as well. The high frequency phenomena in the spin detector response are masked by the filtering and sampling of the telemetry data. However, the observed spin detector telemetery is consistent with a single rib popping free, and is most likely associated with a rib near the spin detector, or 180 deg opposite.

Peng, Chia-Yen↗

NASA NTRS1992

'Intermittent' solar periodicities

The signal from a stable periodicity can seem to be intermittent when it is partially masked by an unmodelled window function or when the data set is too short to resolve closely spaced periodicities. By taking this into account, short-lived periodicities in solar data can be reinterpreted as evidence for continuously periodic behavior. The periodic sources are located in the solar interior and caused by global oscillation modes. The convective envelope acts as the window for these sources. Recent reports of seven periodicities from 100 to 1000 days are compared with this model. Precise long-term values for the periodicities are predicted and they agree closely with observations. Some elements are suggested that might explain the well-documented 155-day periodicity. Conventional filtering methods to suppress effects of the 11-year cycle are criticized as inadequate.

Wolff, Charles L.↗

NASA NTRS1992

Technologies for automating rotorcraft nap-of-the-earth flight

This paper discusses the technologies required for automating rotorcraft nap-of-the-earth flight, where the use of natural obstacles for masking from the enemy is intentional and the danger of undesirable obstacles such as enemy traps is real. Specifically, the automatic guidance structure is modeled by three decision-making levels: the far-field mission planning and the mid-field terrain-masking trajectory shaping are both driven by prestored terrain data, whereas the nearfield obstacle detection/avoidance is driven by real-time on-board sensor data. This paper summarizes the far-field and mid-field accomplishments, and reports on the status of the more-recent efforts in obstacle detection and avoidance development. Obstacle detection is based primarily on passive imaging sensors for the desirable properties of covertness and wide field of view, although active sensors are included in the structure to provide the much needed high resolution for thin-wire detection.

Cheng, Victor H. L.↗

NASA NTRS2012

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Lyapustin, A.↗

DOE OSTI2024

Automated Assembly Progress Monitoring in Modular Construction Factories Using Computer Vision-Based Instance Segmentation

Modular construction has recently gained interest as a transformative construction method. In this method, a large portion of the construction is performed inside factories, where processes are fast-paced and interdependent; therefore, any deviation from the schedule can delay the production. Such deviations are frequent in modular factories due to the labor-intensive nature of the tasks. This propagation of delays can be mitigated by continuously monitoring each process; however, current manual monitoring methods are laborious, and recently proposed contact sensor-based methods are intrusive to the work. In addition, recent computer vision-based monitoring methods inside factories are limited to detection algorithms that fail to provide the pixel-level accuracy required for assembly progress monitoring in highly occluded factory scenes, and they require a large number of manual annotations. Therefore, this paper proposes a method to monitor the installation of subassemblies in modular construction factories using mask R-CNN instance segmentation and improves the data efficiency of the model using a copy-paste augmentation method. This method was validated on the CCTV videos captured from a modular construction factory in the US, resulting in a 9% mAP improvement in segmentation.

computer vision↗