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At least 433 records · Page 24

Machine Learning Based Crater Detection for Terrain Relative Navigation

As Lunar exploration continues to become more commonplace, reliable methods of precise Terrain Relative Navigation (TRN) are needed. While there are many TRN techniques available, one that has received increased interest in the past few years is that of crater based navigation. Crater based navigation has numerous benefits, including being a human recognizable feature (important for crewed missions), as well as the fact that craters are often possible hazards that need to be detected and avoided. The use of crater based navigation has been limited however. This has been due to the difficulty of running such algorithms on board a spacecraft, as well as the difficulty in procuring large amounts of the required training data. This paper presents a new rendering tool for generating large amounts of high quality training data. It then looks at two recently developed machine learning techniques for crater detection and crater identification in real-time on near-future space hardware.

computer vision↗

Evidence for Chemical Processing of Precometary Icy Grains In Circumstellar Environments of Pre-Main-Sequence Stars

We report the detection of a broad absorption feature near 2166 cm-1 in the spectrum of the Taurus cloud source Elias 18. This pre-main-sequence source is the second in Taurus, the third in our survey, and the fifth known in the sky to show the broad 2166 cm-1 absorption feature. Of equal importance, this feature is not seen toward several other embedded sources in our survey, nor is it seen toward the source Elias 16, located behind the Taurus cloud. Laboratory experiments with interstellar ice analogs show that such a feature is associated with a complex C=-N containing compound [called X(C=-N)] that results from high-energy processing (ultraviolet irradiation or ion bombardment) of simple ice components into more complex, organic components, We find a nonlinear anticorrelation between the abundance of X(C=-N) and frozen CO in non- polar lattices. We find no correlation between the abundance of X(C=-N) and frozen CO in polar lattices. Because the abundances of frozen CO and H20 are strongly correlated with each other and with visual extinction toward sources embedded in and located behind the Taurus molecular cloud, these ice components usually are associated with intracloud material. Our results indicate that X(C=-N) molecules result from chemical processing of dust grains dominated by nonpolar icy mantles in the local environments of pre-main- sequence stars. Such processing of icy grains in the early solar system may be an important source of organic compounds observed in minor solar system bodies. The delivery of these organic compounds to the surface of the primitive Earth through comet impacts may have provided the raw materials for prebiotic chemistry.

Teglier, Stephen C.↗

Evidence for chemical processing of precometary icy grains in circumstellar environments of pre-main-sequence stars

We report the detection of a broad absorption feature near 2166/cm in the spectrum of the Taurus cloud cource Elias 18. This pre-main-sequence source is the second in Taurus, the third in our survey, and the fifth known in the sky to show the broad 2166/cm absorption feature. Of equal importance, this feature is not seen toward several other embedded sources in our survey, nor is it seen toward the source Elias 16, located behind the Taurus cloud. Laboratory experiments with interstellar ice analogs show that such a feature is associated with a complex C triple bonded to N containing compound (called X(C triple bonded to N)) that results from high-energy processing (ultraviolet irradiation or ion bombardment) of simple ice components into more complex, organic components. We find a nonlinear anticorrelation between the abundance of X(C triple bonded to N) and frozen CO components in nonpolar lattices. We find no correlation between the abundance of X(C triple bonded to N) and frozen CO in polar lattices. Because the abundances of frozen CO and H2O are strongly correlated with each other and with visual extinction toward sources embedded in and located behind the Taurus molecular cloud, these ice components usually are associated with intracloud material. Our results indicate that X(C triple bonded to N) molecules result from chemical processing of dust grains dominated by nonpolar icy mantles in the local environments of pre-main-sequence stars. Such processing of icy grains in the early solar system may be an important source of organic compounds observed in minor solar system bodies. The delivery of these organic compounds to the surface of the primitive Earth through comet impacts may have provided the raw materials for prebiotic chemistry.

Tegler, Stephen C.↗

Thematic Mapper Data Quality and Performance Assessment in Renewable Resources/agriculture Remote Sensing

It is believed that the increased spatial resolution will provide solutions to proportion estimation error due to mixed pixels, and the increased spectral resolution will provide for the identification of important agricultural features such as crop stage, and condition. The results of analyses conducted relative to these hypothesis from sample segments extracted from the 4-band Detroit scene and the 7-band Mississippi County, Arkansas engineering test scene are described. Several studies were conducted to evaluate the geometric and radiometric performance of the TM to determine data viability for the more pertinent investigations of TM utility. In most cases this requirement was more than sufficiently satisfied. This allowed the opportunity to take advantage of detailed ground observations for several of the sample segments to assess class separability and detection of other important features with TM. The results presented regarding these TM characteristics show that not only is the increased definition of the within scene variance captured by the increased spatial and spectral resolution, but that the mid-IR bands (5 and 7) are necessary for optimum crop type classification. Both qualitative and quantitative results are presented that describe the improvements gained with the TM both relative to the MSS and on its own merit.

Bizzell, R. M.↗

The Geostationary Fourier Transform Spectrometer

The Geostationary Fourier Transform Spectrometer (GeoFTS) is an imaging spectrometer designed for an earth science mission to measure key atmospheric trace gases and process tracers related to climate change and human activity. The GeoFTS instrument is a half meter cube size instrument designed to operate in geostationary orbit as a secondary "hosted" payload on a commercial geostationary satellite mission. The advantage of GEO is the ability to continuously stare at a region of the earth, enabling frequent sampling to capture the diurnal variability of biogenic fluxes and anthropogenic emissions from city to continental scales. The science goal is to obtain a process-based understanding of the carbon cycle from simultaneous high spatial resolution measurements of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and chlorophyll fluorescence (CF) many times per day in the near infrared spectral region to capture their spatial and temporal variations on diurnal, synoptic, seasonal and interannual time scales. The GeoFTS instrument is based on a Michelson interferometer design with a number of advanced features incorporated. Two of the most important advanced features are the focal plane arrays and the optical path difference mechanism. A breadboard GeoFTS instrument has demonstrated functionality for simultaneous measurements in the visible and IR in the laboratory and subsequently in the field at the California Laboratory for Atmospheric Remote Sensing (CLARS) observatory on Mt. Wilson overlooking the Los Angeles basin. A GeoFTS engineering model instrument is being developed which will make simultaneous visible and IR measurements under space flight like environmental conditions (thermal-vacuum at 180 K). This will demonstrate critical instrument capabilities such as optical alignment stability, interferometer modulation efficiency, and high throughput FPA signal processing. This will reduce flight instrument development risk and show that the GeoFTS design is mature and flight ready.

Carbon exchanges↗

Textural features for radar image analysis

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

Shanmugan, K. S.↗

A Machine Learning Approach to Determine Surface Radiative Fluxes based on CERES Observations

The Clouds and Earth’s Radiant Energy System (CERES) projects provides satellite-based observations of the radiative fluxes and clouds systems. CERES climate quality data products typically take several months of calibration and validation before release to the public. An alternative data product, Fast Longwave and Shortwave radiative Flux (FLASHFlux), was created to provide data to the applied sciences and educational users. FLASHFlux provides Top-of-Atmosphere radiative fluxes, Clouds properties, and parameterized surface radiative fluxes within four days for footprint (Level 2) data. We investigate the use of Artificial Neural Network (ANN) using MODerate resolution Imaging Spectroradiometer (MODIS) derived clouds properties and meteorology from the Global Assimilation and Meteorology Office (GMAO) scaled to the CERES footprint from the CERES Clouds Radiative Swath (CRS) data product to compute surface radiative fluxes. We test ANN produce fluxes against surface fluxes produced from the Fu-Liou model used in CRS and the Langley Parameterized Shortwave Algorithm (LPSA) and Langley Parameterized Longwave Algorithm (LPLA) used in FLASHFlux. We also validated each model with ground-based observations. Furthermore, we investigate Leave-One-Feature-Out Importance (LOFO) to evaluate the significance of each feature in our training and provide insight for future models. Advances in machine learning, along with increases in computational capabilities and available data allow us to estimate effects of unresolved processes in our climate without direct modeling. This work evaluates the ability to create accurate data-driven models to supplement or replace current models that estimate surface radiative fluxes.

Climatology↗

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗

Toward real-time performance benchmarks for Ada

Benchmarks are developed to measure the Ada notion of time, the Ada features believed important to real-time performance, and other time-related features that are not part of the language, but are part of the run-time system; these benchmarks are then applied to the language and run-time system, and the results evaluated.

Clapp, Russell M.↗

Toward real-time performance benchmarks for Ada

The issue of real-time performance measurements for the Ada programming language through the use of benchmarks is addressed. First, the Ada notion of time is examined and a set of basic measurement techniques are developed. Then a set of Ada language features believed to be important for real-time performance are presented and specific measurement methods discussed. In addition, other important time related features which are not explicitly part of the language but are part of the run-time related features which are not explicitly part of the language but are part of the run-time system are also identified and measurement techniques developed. The measurement techniques are applied to the language and run-time system features and the results are presented.

Clapp, Russell M.↗

Near-Infrared Spectra of Type Ia Supernovae

We report near-infrared (NIR) spectroscopic observations of 12 'branch-normal' Type Ia supernovae (SNe Ia) that cover the wavelength region from 0.8 to 2.5 microns. Our sample more than doubles the number of SNe Ia with published NIR spectra within 3 weeks of maximum light. The epochs of observation range from 13 days before maximum light to 18 days after maximum light. A detailed model for a Type Ia supernovae is used to identify spectral features. The Doppler shifts of lines are measured to obtain the velocity and thus the radial distribution of elements. The NIR is an extremely useful tool to probe the chemical structure in the layers of SNe Ia ejecta. This wavelength region is optimal for examining certain products of the SNe Ia explosion that may be blended or obscured in other spectral regions. We identify spectral features from Mg II, Ca II, Si II, Fe II, Co II, Ni II, and possibly Mn II. We find no indications for hydrogen, helium, or carbon in the spectra. The spectral features reveal important clues about the physical characteristics of SNe Ia. We use the features to derive upper limits for the amount of unburned matter, to identify the transition regions from explosive carbon to oxygen burning and from partial to complete silicon burning, and to estimate the level of mixing during and after the explosion. Elements synthesized in the outer layers during the explosion appear to remain in distinct layers. That provides strong evidence for the presence of a detonation phase during the explosion as it occurs in delayed detonation or merger models. Mg II velocities are found to exceed 11,000 - 15,000 km/s, depending on the individual SNe Ia. That result suggests that burning during the explosion reaches the outermost layers of the progenitor and limits the amount of unburned material to less than 10% of the mass of the progenitor. Small residuals of unburned material are predicted by delayed detonation models but are inconsistent with pure deflagration or merger models. Differences in the spectra of the individual SNe Ia demonstrate the variety of these events.

Marion, G. H.↗

Coastal High-resolution Observations and Remote Sensing of Ecosystems (C-HORSE)

Coastal benthic marine ecosystems, such as coral reefs, seagrass beds, and kelp forests are highly productive as well as ecologically and commercially important resources. These systems are vulnerable to degraded water quality due to coastal development, terrestrial run-off, and harmful algal blooms. Measurements of these features are important for understanding linkages with land-based sources of pollution and impacts to coastal ecosystems. Challenges for accurate remote sensing of coastal benthic (shallow water) ecosystems and water quality are complicated by atmospheric scattering/absorption (approximately 80+% of the signal), sun glint from the sea surface, and water column scattering (e.g., turbidity). Further, sensor challenges related to signal to noise (SNR) over optically dark targets as well as insufficient radiometric calibration thwart the value of coastal remotely-sensed data. Atmospheric correction of satellite and airborne remotely-sensed radiance data is crucial for deriving accurate water-leaving radiance in coastal waters. C-HORSE seeks to optimize coastal remote sensing measurements by using a novel airborne instrument suite that will bridge calibration, validation, and research capabilities of bio-optical measurements from the sea to the high altitude remote sensing platform. The primary goal of C-HORSE is to facilitate enhanced optical observations of coastal ecosystems using state of the art portable microradiometers with 19 targeted spectral channels and flight planning to optimize measurements further supporting current and future remote sensing missions.

Coasts↗

Design improvement of a pump wear ring labyrinth seal

The investigation was successful in obtaining two improved designs for the impeller wear ring seal of the liquid hydrogen turbopump of interest. A finite difference computer code was extensively used in a parametric computational study in determining a cavity configuration with high flow resistance due to turbulence dissipation. These two designs, along with that currently used, were fabricated and tested. The improved designs were denoted Type O and Type S. The measurements showed that Type O and Type S given 67 and 30 percent reduction in leakage over the current design, respectively. It was found that the number of cavities, the step height and the presence of a small stator groove are quite important design features. Also, the tooth thickness is of some significance. Finally, the tooth height and an additional large cavity cut out from the stator (upstream of the step) are of negligible importance.

Rhode, David L.↗

Mimas: Tectonic structure and geologic history

Mimas, the innermost of the major saturnian satellites, occupies an important place in comparative studies of icy satellites. It is the smallest icy satellite known to have a mostly spherical shape. Smaller icy objects like Hyperion and Puck are generally irregular in shape, while larger ones like Miranda and Enceladus are spherical. Thus Mimas is near the diameter where the combination of increasing surface gravity and internal heating begin to have a significant effect on global structure. The nature and extent of endogenic surface features provide important constraints on the interior structure and history of this transitional body. The major landforms on Mimas are impact craters. Mimas has one of the most heavily cratered surfaces in the solar system. The most prominent single feature on Mimas is Herschel, an unrelaxed complex crater 130 km in diameter. The only other recognized landforms on Mimas are tectonic grooves and lineaments. Groove locations were mapped by Schenk, but without analysis of groove structures or superposition relationships. Mimas' tectonic structures are remapped here in more detail than previously has been done, as part of a general study of tectonic features on icy satellites.

Croft, Steven K.↗

Dynamic Moss Observed with Hi-C

The High‐resolution Coronal Imager (Hi‐C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi‐C imaged a large active region (AR11520) with 0.2‐0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi‐C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi‐C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Alexander, Caroline↗

Dynamic Moss Observed with Hi-C

The High-resolution Coronal Imager (Hi-C), flown on 11 July 2012, has revealed an unprecedented level of detail and substructure within the solar corona. Hi-­‐C imaged a large active region (AR11520) with 0.2-0.3'' spatial resolution and 5.5s cadence over a 5 minute period. An additional dataset with a smaller FOV, the same resolution, but with a higher temporal cadence (1s) was also taken during the rocket flight. This dataset was centered on a large patch of 'moss' emission that initially seemed to show very little variability. Image processing revealed this region to be much more dynamic than first thought with numerous bright and dark features observed to appear, move and disappear over the 5 minute observation. Moss is thought to be emission from the upper transition region component of hot loops so studying its dynamics and the relation between the bright/dark features and underlying magnetic features is important to tie the interaction of the different atmospheric layers together. Hi-C allows us to study the coronal emission of the moss at the smallest scales while data from SDO/AIA and HMI is used to give information on these structures at different heights/temperatures. Using the high temporal and spatial resolution of Hi-C the observed moss features were tracked and the distribution of displacements, speeds, and sizes were measured. This allows us to comment on both the physical processes occurring within the dynamic moss and the scales at which these changes are occurring.

Alexander, Caroline↗

Atmospheric Transport During the Transport and Chemical Evolution over the Pacific TRACE-P Experiment

Atmospheric transport over the Pacific Basin is described during NASA's Transport and Chemical Evolution Over the Pacific Experiment (TRACE-P) that was conducted between February - April 2001. The mission included extensive chemical sampling from two aircraft based primarily in Hong Kong and Yokota Air Base, Japan. Meteorological conditions during TRACE-P changed rapidly due to the seasonal winter/spring transition and the decay of prolonged ENSO cold phase (La Nina) conditions. To document these changes, TRACE-P was divided into two halves, and mean flow patterns during each half are presented and discussed. Important circulation features are the semi-permanent Siberian anticyclone and transient middle latitude cyclones that form near eastern Asia and then move eastward over the northern Pacific. Five-day backward trajectories from the various flight tracks show that air sampled by the aircraft had been transported from a variety of locations. Some parcels remained over the tropical western North Pacific during the entire period, while other important origins were Southeast Asia, Africa, and central Asia. Patterns of satellite-derived precipitation and lightning are described. TRACE-P occurs during a neutral to weak La Nina period of relatively cold sea surface temperatures in the tropical Pacific. Compared to climatology, the TRACE-P period exhibits deep convection located west of its typical position; however, tropospheric flow patterns do not exhibit a strong La Nina signal. Circulation patterns during TRACE-P are found to be generally similar to those during NASA's PEM WEST-B mission that occurred in the same region during February - March 1994.

Fuelberg, Henry E.↗

Celestial Mapping System and Digital Lunar Library Initiative

We are preparing to create an interactive, global 3D lunar environment with integrated dataset and AI/ML tools to provide unique value to mission planners, scientists and the entire lunar community. This lunar environment will be based on NASA Ames Celestial Mapping System (CMS) [1] and Digital Lunar Library (DLL) Initiative. CMS provides a 3D virtual Lunar Globe with extensive user friendly tool sets, that include high resolution terrain visualization, elevation profiles, measurement kits, slope analysis, path optimization, line of sight analysis, equipment planning and placement tools and many other functionalities [1]. It has a thick client with less overhead to access hardware resources. This allows features such as terrain profiling and distance calculations to be performed on the client and on the fly. The application is developed to provide situational and domain awareness on the Lunar surface, planning capabilities for equipment placements and traverse path optimization. As data becomes available, CMS has the capabilities to integrate data sets that change dynamically in real-time, which will be useful for monitoring satellites and remotely-sensed data on the Lunar surface. CMS supports importing synthetic features in a variety of 3D, 2D, vector and raster formats. In the future, these capabilities will be enhanced by incorporating AI/ML tools and a plug-in architecture to enable customization by the user groups. With the help of DLL we will be able to : 1) Amplify the value of lunar information with AI-powered data enhancements 2) Acquire and integrate lunar data with AI-assisted georectification and homogenization 3) Analyze lunar data with advanced 3D visualization, intelligent search-by-example 4) Apply lunar data insights to specific use cases with an open plug-in architecture. The CMS-DLL initiative will have several potential use cases for NASA and the lunar community in general, including subsurface lava tube visualization and analysis, soil analysis, in-situ lunar resource visualization and representation on 3D globe, and data analytics for utilization. REFERENCES: [1] https://celestial.arc.nasa.gov/

3D Globe↗