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The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which have been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.
The non-U.S. standard catalog lists non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date acquired, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found is also given.
The Non-U.S. Standard Catalog lists Non-U.S. imagery acquired by LANDSAT 1 and LANDSAT 2 which has been processed and input to the data files during the referenced month. Data, such as date required, cloud cover and image quality are given for each scene. The microfilm roll and frame on which the scene may be found are also given.
The scientific data transmitted continuously from all ALSEP (Apollo Lunar Surface Experiment Package) stations on the Moon and recorded on instrumentation tapes at receiving stations distributed around the Earth were processed. The processing produced sets of computer-compatible digital tapes, from which various other data sets convenient for analysis were generated. The seismograms were read, various types of seismic events were classified; the detected events were cataloged.
The H-aplha and Na I D-line regions of the M6 giant star ZZ Canis Minoris (ZZ CMi) were observed with the Kitt Peak coude feed telescope and a CCD detector. It is shown that ZZ CMi has similar spectroscopic and photoproperties to the symbiotic star EG And. The data are used to argue for the classification of ZZ CMi as a symbiotic star despite its current listing in the General Catalog of Variable Stars (GCVS) as a semi-regular variable. The infrared magnitudes of ZZ CMi and the known symbiotic stars are compared in a table.
The application of SETI data to radio astronomy is studied. The number of continuum radio sources in the 1-10 GHz region to be counted and cataloged is predicted. The radio luminosity functions for steep and flat spectrum sources at 2, 8, and 22 GHz are derived using the model of Peacock and Gull (1981). The relation between source number and flux density is analyzed and the sensitivity of the system is evaluated.
A model was developed to determine the origin of orbital impacts measured on the training surfaces of LDEF. The model calculates the expected debris impact crater distribution around LDEF as a function of debris orbital parameters. The results show that only highly elliptical, low inclination orbits could be responsible for these impacts. The most common objects left in this type of orbit are orbital transfer stages used by the U.S. and ESA to place payloads into geosynchronous orbit. Objects in this type of orbit are difficult to catalog by the U.S. Space Command; consequently there are independent reasons to believe that the catalog does not adequately represent this population. This analysis concludes that the relative number of cataloged objects with highly elliptical, low inclination orbits must be increased by a factor of 20 to be consistent with the LDEF data.
Peak-ring basins (large impact craters exhibiting a single interior ring) are important to understanding the processes controlling the morphological transition from craters to large basins on planetary bodies. New image and topography data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) and Lunar Reconnaissance Orbiter (LRO) spacecraft have helped to update the catalogs of peak-ring basins on Mercury and the Moon [1,2] and are enabling improved calculations of the morphometric properties of these basins. We use current orbital altimeter measurements from the Mercury Laser Altimeter (MLA) [3] and the Lunar Orbiter Laser Altimeter (LOLA) [4], as well as stereo-derived topography [5], to calculate the floor depths and peak-ring heights of peak-ring basins on Mercury and the Moon. We present trends in these parameters as functions of rim-crest diameter, which are likely to be related to processes controlling the onset of peak rings in these basins.
Flooding events are becoming increasingly frequent worldwide and are known to cause extensive damage. Public optical and radar satellite imagery can be used to detect large areas of inundation in rural areas, however, long revisit times and coarse spatial resolution limit applications for short-lived events and urban areas. Commercial constellations such as those operated by Planet offer increased spatial and temporal resolution and can supplement mapping efforts to provide more information to disaster response, relief, and mitigation efforts. Deep learning requires high quality labeled data for training across coincident sensors. The FloodPlanet dataset presented here contains labeled surface water for 18 events across the world based on Planetscope imagery with coincident Harmonized Landsat Sentinel-2 ( HLS) or Sentinel-1 and builds upon the previously existing Sen1Floods11, xBD, and NASA Sentinel-1 datasets. Sen1Floods11 includes 4,831 512x512 pixel overlapping tiles of coincident Sentinel-1 and Sentinel-2 data observing 11 flood events across the world from 2017-2019. The dataset contains a combination of automated and hand-labeled surface water for use in training and validation of inundation modeling efforts. The xBD dataset identifies flood-damaged buildings and indicates the scale of damage to each (none, minor, moderate, and major) from four flood events which occurred in the United States, India, Nepal, and Bangladesh from the same time period. The NASA dataset contains hand-labeled water bodies observed in Sentinel-1 imagery during five flood events within the 2017-2019 period. The effort presented here utilizes observations from these previously investigated flood events to generate labels of surface water at the 3-5m spatial resolution provided by Planetscope and facilitate the comparison between public and commercial data. A data pipeline was built which uses clustering algorithms to pick the most suitable overlapping chips between the public data and PlanetScope data for manual labeling. Labels were created manually using NASA’s ImageLabeler tool and include areas of high- and low-confidence water. The high confidence designation is reserved for areas of open, unobstructed water while low confidence is used for areas of suspected water beneath vegetation, clouds, or cloud shadows. Expected to be released in late 2022, the FloodPlanet dataset will include tiled imagery with a unique ID for each 1024x1024 pixel tile, 7 bands of HLS data, and high- and low-confidence flood labels in both shapefile and tiff formats. The authors will follow Spatial Temporal Access Catalog (STAC) guidelines to release FloodPlanet on the Radiant Earth ML hub, which hosts public datasets for machine learning.
While supernova remnants (SNRs) are widely thought to be powerful cosmicray accelerators, indirect evidence comes from a small number of well-studied cases. Here we systematically determine the gamma-ray emission detected by the ermi Large Area Telescope (LAT) from all known Galactic SNRs, disentangling them from the sea of cosmic-ray generated photons in the Galactic plane. Using LAT data we have characterized the 1-100 GeV emission in 279 regions containing SNRs, accounting for systematic uncertainties caused by source misattribution and instrumental response. We classified 30 sources as SNRs, using spatial overlap with the radio emission position. For all the remaining regions we evaluated upper limits on SNRs' emission. In the First Fermi-LAT SNR Catalog there is a study of the common characteristics of these SNRs, such as comparisons between GeV, radio and TeV quantities. We show that previously satisfactory models of SNRs' GeV emission no longer adequately describe the data. To address the question of cosmic ray (CR) origins, we also examine the SNRs' maximal CR contribution assuming the GeV emission arises solely from proton interactions. Improved breadth and quality of multiwavelength (MW) data, including distances and local densities, and more, higher resolution gamma-ray data with correspondingly improved Galactic diffuse models will strengthen this constraint.
The GEOS 3 significant waveheight and ground wind speed estimation algorithms are derived and then applied to all GEOS 3 data in the South Atlantic Bight. The investigation area is divided into five geographical sectors and significant waveheight and wind speed histograms are presented in each sector by month and by season. In the discussion of the histograms, definite seasonal trends are identified and examined.
Several 3.8 cm radar frames were calibrated empirically by histogram fitting, because no instrument background data is available. Then data were corrected for geometric distortion by: (1) redetermining position of individual frames using most accurate recent lunar ephemerides; (2) reprojecting frames into simple cylindrical map projection; (3) using most recent catalog of lunar craters to determine the exact positions of features identifiable on radar frames; and (4) correcting for apparent distortion (misplacement of features in frames) by resampling using a different bilinear interpolation derived for each of the parallelopideds of the set defined for each frame. A hardcopy set of corrected frames was produced. Attempts to produce a mosaic of such corrected frames continue. The resulting mosaic can be used to show the systematic relationship between photographic thermal IR and radar data at different wavelengths in a region dominated by both mare and highland terrain.
While supernova remnants (SNRs) are widely thought to be powerful cosmic-ray accelerators, indirect evidence comes from a small number of well-studied cases. Here we systematically determine the gamma-ray emission detected by the Fermi Large Area Telescope (LAT) from all known Galactic SNRs, disentangling them from the sea of cosmic-ray generated photons in the Galactic plane. Using LAT data we have characterized the 1-100 GeV emission in 279 regions containing SNRs, accounting for systematic uncertainties caused by source misattribution and instrumental response. We classified 30 sources as SNRs, using spatial overlap with the radio emission position. For all the remaining regions we evaluated upper limits on SNRs' emission. In the First Fermi-LAT SNR Catalog there is a study of the common characteristics of these SNRs, such as comparisons between GeV, radio and TeV quantities. We show that previously satisfactory models of SNRs' GeV emission no longer adequately describe the data. To address the question of cosmic ray (CR) origins, we also examine the SNRs' maximal CR contribution assuming the GeV emission arises solely from proton interactions. Improved breadth and quality of multiwavelength (MW) data, including distances and local densities, and more, higher resolution gamma-ray data with correspondingly improved Galactic diffuse models will strengthen this constraint.
The new version of the NASA Orbital Debris Engineering Model (ORDEM2008) requires accurate populations as input template files to be used in the calculation of orbital debris fluxes on chosen spacecraft or within telescope/radar fields-of-view. Populations in ORDEM2008 are derived from a consortium of data and modeling. Geosynchronous (GEO) satellites and debris form a distinct ORDEM2008 population that is applied to the distinct analysis of GEO fluxes. Low Earth orbit (LEO) populations are derived by combining modeling results with ground-based data, primarily from radar systems and in-situ data. In contrast, the GEO region has not been as well observed. The distance between orbiting objects and ground-based instruments precludes the wide usage of radar as a means of observation. Instead, optical instruments dominate in the study of GEO. Of these, the NASA sponsored Michigan Orbital Debris Survey Telescope (MODEST) has provided 4 years of surveys of the region detecting cataloged objects (correlated targets) and non-cataloged objects (uncorrelated targets) to an estimated minimum size of 30 cm. This paper describes the methods of combining NASA launch database and satellite breakup and orbital propagation modeling with MODEST 2004-to-2006 uncorrelated target data to attain a GEO environment to 10 cm. Assuming that MODEST uncorrelated targets are breakup debris allows for the extension of the debris survey data to smaller sizes with the NASA Standard Breakup model. Each orbit within the total resulting GEO population is marked by a random argument of perigee and nearly constant mean motion, eccentricity, inclination, and node over the nearly 3 years of observation. Lack of published references of past breakups in GEO is mitigated by the orbital propagation of MODEST extended data to 1995 (the beginning epoch of ORDEM2008).
The new version of the NASA Orbital Debris Engineering Model (ORDEM2010) requires accurate populations as input files to be used in the calculation of orbital debris fluxes on chosen spacecraft or within telescope/radar fields-of-view. Populations in ORDEM2010 are derived from an amalgam of data and modeling. Geosynchronous orbit (GEO) satellites and debris form a distinct ORDEM2010 population that is applied to the distinct analysis of GEO fluxes. Low Earth orbit (LEO) populations are derived by combining modeling results with ground-based data, primarily from radar systems, and in-situ data. In contrast, the GEO region has not been as well observed. The distance between orbiting objects and ground-based instruments precludes the wide usage of radar as a means of observation. Instead, optical instruments dominate in the study of GEO. Of these, the NASA sponsored Michigan Orbital Debris Survey Telescope (MODEST) has provided 3 years of surveys of the region detecting cataloged objects (correlated targets) and non-cataloged objects (uncorrelated targets) to an estimated minimum size of 30 cm. This paper describes the methods of combining NASA launch database and satellite breakup and orbital propagation modeling with MODEST 2004-to-2006 uncorrelated target data to attain a GEO environment to 10 cm. Assuming that MODEST uncorrelated targets are breakup debris allows for the extension of the debris survey data to smaller sizes using the NASA Standard Breakup Model. Each orbit within the total resulting GEO population is marked by a random argument of perigee and nearly constant mean motion, eccentricity, inclination, and right ascension of ascending node (RAAN) over the nearly 3 years of observation. Lack of published references of past breakups in GEO is mitigated by the orbital propagation of MODEST extended data to 1995 (the beginning epoch of ORDEM2010).
The incorporation of precision inertial control on LST could exert a strong influence on the philosophy of and techniques for carrying out astronomical observations. In conjunction with a fine guidance star sensor, the inertial reference unit (IRU) described herein could easily expand LST capability to include observations such as (1) tracking of solar system objects, including specific points of interest on the planets; (2) rapid repositioning of scanning sensors on distributed objects such as nebulae and galaxies; (3) carrying out unified star catalog measurements to eliminate the overlap problem which exists in all ground procedures; and (4) carrying out various astrometric measurements with 'real time' data reduction capability.
Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.
This poster describes techniques developed for manipulating large full-sky data sets for the Extreme Ultraviolet Explorer project. The authors have adapted the quatrilateralized cubic sphere indexing algorithm to allow us to efficiently store and process several types of large data sets, such as full-sky maps of photon counts, exposure time, and count rates. A variation of this scheme is used to index sparser data such as individual photon events and viewing times for selected areas of the sky, which are eventually used to create EUVE source catalogs.