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NASA NTRS1982

The reduction, verification and interpretation of MAGSAT magnetic data over Canada

Research into an approach for altitude adjustments for MAGSAT or similar data acquired over a range of altitudes is progressing. The technique shows promise not only in the production of refined anomaly maps but also in the derivation of regional charts of the magnetic elements from satellite and ground data. Correlations between MAGSAT anomalies and other geophysical and geological data are being explored further and quantitative modelling of some features has begun. The form of some anomalies may change as the maps are refined by the technique being developed. Emphasis is being given to the Canadian regions, although analogous features elsewhere are being considered.

Coles, R. L.↗

NASA NTRS1976

Landsat Signature Development Program

The Landsat Signature Development Program, LSDP, is designed to produce an unsupervised classification of a scene from a Landsat tape. This classification is based on the clustering tendencies of the multispectral scanner data processed from the scene. The program will generate a character map that, by identifying each of the general classes of surface features extracted from the scene data with a specific line printer symbol, indicates the approximate locations and distributions of these general classes within the scene. Also provided with the character map are a number of tables each of which describes either some aspect of the spectral properties of the resultant classes, some inter-class relationship, the incidence of picture elements assigned to the various classes in the character map classification of the scene, or some significant intermediate stage in the development of the final classes.

Hall, R. N.↗

DOE OSTI2024

Radiation-Induced Noise Resilience of Neuromorphic Architectures

Neuromorphic event-based networks use asynchronous time-dependent information to extract features from input data that can allow for edge-based distributed applications such as object recognition. The noise resilience properties of such networks, especially in the context of space applications, are yet to be explored. In this paper, we use the hierarchy of time surfaces (HOTS) algorithm, which is one of the neuromorphic algorithms, to understand the least and most resilient modules in a neuromorphic network. The HOTS algorithm relies on the computing of time surfaces that maps the temporal delays between neighboring pixels into normalized features that involve many computations that are also found in other neuromorphic networks such as exponential decays, distance computations, etcetera. We implemented HOTS on a Digilent PYNQ board with a Xilinx Zynq 7020 system on a chip, and we subjected the boards running the HOTS network inference to neutron radiation at the Los Alamos Neutron Science Center. Furthermore, we used simulation models from our previous similar experiments on the event-based sensor to create a neutron induced noise model to quantify the effect of this noise on the overall performance of the network. This experiment provides the preliminary measurements of the reliability of the HOTS algorithm and proposes methods to create a more reliable HOTS architecture in future spacecraft missions.

Engineering↗

DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1972

Remote sensing of soils, land forms, and land use in the northern great plains in preparation for ERTS applications

Research to determine the optimum time or season for obtaining imagery to identify and map soil limitations was conducted in the proposed Oahe irrigation project area in South Dakota. The optimum time for securing photographs or imagery is when the soil surface patterns are most apparent. For cultivated areas similar to the study area, May is the optimum time. The fields are cultivated or the planted crop has not yet masked soil surface features. Soil limitations in 59 percent of the field of the flight line could be mapped using the above criteria. The remaining fields cannot be mapped because the vegetation or growing crops do not express features related to soil differences. This suggests that imagery from more than one year is necessary to map completely the soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations of Oahe area by remote sensing techniques. Imagery from the other times studied is not suitable for identifying and mapping soil limitations because the vegetative cover masked the soil surface and does not reflect soil differences.

Frazee, C. J.↗

NASA NTRS1988

Automated extraction of absorption features from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Geophysical and Environmental Research Imaging Spectrometer (GERIS) data

Automated techniques were developed for the extraction and characterization of absorption features from reflectance spectra. The absorption feature extraction algorithms were successfully tested on laboratory, field, and aircraft imaging spectrometer data. A suite of laboratory spectra of the most common minerals was analyzed and absorption band characteristics tabulated. A prototype expert system was designed, implemented, and successfully tested to allow identification of minerals based on the extracted absorption band characteristics. AVIRIS spectra for a site in the northern Grapevine Mountains, Nevada, have been characterized and the minerals sericite (fine grained muscovite) and dolomite were identified. The minerals kaolinite, alunite, and buddingtonite were identified and mapped for a site at Cuprite, Nevada, using the feature extraction algorithms on the new Geophysical and Environmental Research 64 channel imaging spectrometer (GERIS) data. The feature extraction routines (written in FORTRAN and C) were interfaced to the expert system (written in PROLOG) to allow both efficient processing of numerical data and logical spectrum analysis.

Kruse, Fred A.↗

DOE OSTI2022

Experimental observations of detached bow shock formation in the interaction of a laser-produced plasma with a magnetized obstacle

The magnetic field produced by planets with active dynamos, like the Earth, can exert sufficient pressure to oppose supersonic stellar wind plasmas, leading to the formation of a standing bow shock upstream of the magnetopause, or pressure-balance surface. Scaled laboratory experiments studying the interaction of an inflowing solar wind analog with a strong, external magnetic field are a promising new way to study magnetospheric physics and to complement existing models, although reaching regimes favorable for magnetized shock formation is experimentally challenging. This paper presents experimental evidence of the formation of a magnetized bow shock in the interaction of a supersonic, super-Alfvenic plasma with a strongly magnetized obstacle at the OMEGA laser facility. The solar wind analog is generated by the collision and subsequent expansion of two counter- propagating, laser-driven plasma plumes. The magnetized obstacle is a thin wire, driven with strong electrical currents. Hydrodynamic simulations using the FLASH code predict that the colliding plasma source meets the criteria for bow shock formation. Spatially resolved, optical Thomson scat- tering measures the electron number density, and optical emission lines provide a measurement of the plasma temperature, from which we infer the presence of a fast magnetosonic shock far upstream of the obstacle. Proton images provide a measure of large-scale features in the magnetic field topology, and reconstructed path-integrated magnetic field maps from these images suggest the formation of a bow shock upstream of the wire and as a transient magnetopause. We compare features in the reconstructed fields to two-dimensional MHD simulations of the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2008

Geologic Mapping of the Marius Quadrangle, the Moon

The authors seek to construct a 1:2,500,000-scale map of Lunar Quadrangle 10 (LQ10 or the Marius Quadrangle) to address outstanding questions about the Moon's volcanologic history and the role of impact basins in lunar geologic evolution. The selected quadrangle contains Aristarchus plateau and the Marius hills, Reiner Gamma, and Hevelius crater. By generating a geologic map of this region, we can constrain the temporal (and possibly genetic) relations between these features, revealing more information about the Moon's chemical and thermal evolution. Although many of these individual sites have been investigated using Lunar Orbiter, Clementine, Lunar Prospector and Galileo data, no single investigation has yet attempted to constrain the stratigraphic and geologic relationships between these features. Furthermore, we will be able to compare our unit boundaries on the eastern boundary of the proposed map area with those already mapped in the Copernicus Quadrangle. Geologic mapping of the Marius Quadrangle would provide insight to the following questions: the origin, evolution, and distribution of mare volcanism; the timing and effects of the major basin-forming impacts on lunar crustal stratigraphy; and, the Moon's important resources, where they are concentrated, and how they can be accessed.

Gregg, Tracy K. P.↗

NASA NTRS2003

The Importance of Chaos and Lenticulae on Europa for the JIMO Mission

The Galileo Solid State Imaging (SSI) experiment provided high-resolution images of Europa's surface allowing identification of surface features barely distinguishable at Voyager's resolution. SSI revealed the visible pitting on Europa's surface to be due to large disrupted features, chaos, and smaller sub-circular patches, lenticulae. Chaos features contain a hummocky matrix material and commonly contain dislocated blocks of ridged plains. Lenticulae are morphologically interrelated and can be divided into three classes: domes, spots, and micro-chaos. Domes are broad, upwarped features that generally do not disrupt the texture of the ridged plains. Spots are areas of low albedo that are generally smooth in texture compared to other units. Micro-chaos are disrupted features with a hummocky matrix material, resembling that observed within chaos regions. Chaos and lenticulae are ubiquitous in the SSI regional map observations, which average approximately 200 meters per pixel (m/pxl) in resolution, and appear in several of the ultra-high resolution, i.e., better than 50 m/pxl, images of Europa as well. SSI also provided a number of multi-spectral observations of chaos and lenticulae. Using this dataset we have undertaken a thorough study of the morphology, size, spacing, stratigraphy, and color of chaos and lenticulae to determine their properties and evaluate models of their formation. Geological mapping indicates that chaos and micro-chaos have a similar internal morphology of in-situ degradation suggesting that a similar process was operating during their formation. The size distribution denotes a dominant size of 4-8 km in diameter for features containing hummocky material (i.e., chaos and micro-chaos). Results indicate a dominant spacing of 15 - 36 km apart. Chaos and lenticulae are generally among the youngest features stratigraphically observed on the surface, suggesting a recent change in resurfacing style. Also, the reddish non-icy materials on Europa's surface have high concentrations in many chaos and lenticulae features. Nonetheless, a complete global map of the distribution of chaos and lenticulae is not possible with the SSI dataset. Only <20% of the surface has been imaged at 200 m/pxl or better resolution, mostly of the near-equatorial regions. Color and ultra-high-res images have much less surface coverage. Thus we suggest that full global imaging of Europa at 200 m/pxl or better resolution, preferably in multi-spectral wavelengths, should be a high priority for the JIMO mission.

Spaun, Nicole A.↗

NASA NTRS2008

Geologic Map of the V-1 Snegurochka Planitia Quadrangle: Progress Report

Geologic mapping of Snegurochka Planitia (V-1) reveals a complex stratigraphy of tectonic and volcanic features that can provide insight into the geologic history of Venus and Archean Earth [1,2] including 1) crustal thickening environments and processes, 2) the nature of diapirism, 3) the nature and origin of deformation belts, and 4) the origin and context of regional plains-forming volcanism. This abstract presents our progress in mapping the spatial and stratigraphic relationships of these features in the region surrounding the north pole of Venus.

Hurwitz, Debra M.↗

NASA NTRS2004

Modeling Forest Understory Fires in an Eastern Amazonian Landscape

Forest understory fires are an increasingly important cause of forest impoverishment in Ammonia, but little is known of the landscape characteristics and climatic phenomena that determine their occurrence. We developed empirical functions relating the occurrence of understory fires to landscape features near Paragominas, a 35- yr-old ranching and logging center in eastern Ammonia. An historical sequence of maps of forest understory fire was created based on field interviews With local farmers and Landsat TM images. Several landscape features that might explain spatial variations in the occurrence of understory fires were also mapped and co-registered for each of the sample dates, including: forest fragment size and shape, forest impoverishment through logging and understory fires, source of ignition (settlements and charcoal pits), roads, forest edges, and others. The spatial relationship between forest understory fire and each landscape characteristic was tested by regression analyses. Fire probability models were then developed for various combinations of landscape characteristics. The analyses were conducted separately for years of the El Nino Southern Oscillation (ENSO), which are associated with severe drought in eastern Amazonia, and non-ENS0 years. Most (91 %) of the forest area that burned during the 10-yr sequence caught fire during ENSO years, when severe drought may have increased both forest flammability and the escape of agricultural management fires. Forest understory fires were associated with forest edges, as reported in previous studies from Ammonia. But the strongest predictor of forest fire was the percentage of the forest fragment that had been previously logged or burned. Forest fragment size, distance to charcoal pits, distance to agricultural settlement, proximity to forest edge, and distance to roads were also correlated with forest understory fire. Logistic regression models using information on fragment degradation and distance to ignition sources accurately predicted the location of lss than 80% of the forest fires observed during the ENSO event of 1997- 1998. In this Amazon landscape, forest understory fire is a complex function of several variables that influence both the flammability and ignition exposure of the forest.

Alencar, A. A. C.↗

NASA NTRS1974

Multidisciplinary study of Wyoming test sites

The author has identified the following significant results. Investigation of a variety of applications of EREP photographic data demonstrated that EREP S-190 data offer a unique combination of synoptic coverage and image detail. The broad coverage is ideal for regional geologic mapping and tectonic analysis while the detail is adequate for mapping of crops, mines, urban areas, and other relatively small features. The investigative team at the University of Wyoming has applied the EREP S-190 data to: (1) analysis of photolinear elements of the Powder River Basin, southern Montana, and the Wind River Mountains; (2) drainage analysis of the Powder River Basin and Beartooth Mountains; (3) lithologic and geologic mapping in the Powder River Basin, Black Hills, Green River Basin, Bighorn Basin and Southern Bighorn Mountains; (4) location of possible mineralization in the Absaroka Range; and (5) land use mapping near Riverton and Gillette. All of these applications were successful to some degree. Image enhancement procedures were useful in some efforts requiring distinction of small objects or subtle contrasts.

Houston, R. S.↗

NASA NTRS1984

Nimbus 7 SMMR derived seasonal variations in the water vapor, liquid water, and surface winds over the global oceans

A study based on monthly mean maps of atmospheric water vapor, liquid water, and surface wind derived from Nimbus-7 SMMR over the oceans for 13 months, is examined. A discussion of the retrieval technique used to derive the parameters is presented. The seasonal changes in the strength and position of several of the parameter features are revealed by the December 1978 and June 1979 maps. Zonal averages of the water vapor, liquid water, and surface wind for December and June are compared with information derived from conventional measurements and the results are presented in graphs.

Prabhakara, C.↗

DOE OSTI2022

Experimental observations of detached bow shock formation in the interaction of a laser-produced plasma with a magnetized obstacle

The magnetic field produced by planets with active dynamos, like the Earth, can exert sufficient pressure to oppose supersonic stellar wind plasmas, leading to the formation of a standing bow shock upstream of the magnetopause, or pressure-balance surface. Scaled laboratory experiments studying the interaction of an inflowing solar wind analog with a strong, external magnetic field are a promising new way to study magnetospheric physics and to complement existing models, although reaching regimes favorable for magnetized shock formation is experimentally challenging. This paper presents experimental evidence of the formation of a magnetized bow shock in the interaction of a supersonic, super-Alfvenic plasma with a strongly magnetized obstacle at the OMEGA laser facility. The solar wind analog is generated by the collision and subsequent expansion of two counterpropagating, laser-driven plasma plumes. The magnetized obstacle is a thin wire, driven with strong electrical currents. Hydrodynamic simulations using the FLASH code predict that the colliding plasma source meets the criteria for bow shock formation. Spatially resolved, optical Thomson scattering measures the electron number density, and optical emission lines provide a measurement of the plasma temperature, from which we infer the presence of a fast magnetosonic shock far upstream of the obstacle. Proton images provide a measure of large-scale features in the magnetic field topology, and reconstructed path-integrated magnetic field maps from these images suggest the formation of a bow shock upstream of the wire and as a transient magnetopause. Finally, we compare features in the reconstructed fields to two-dimensional MHD simulations of the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

DECADE+ DES Y3 Weak Lensing Mass Map: A 13,000 deg $\^{} 2$ View of Cosmic Structure from 270 Million Galaxies

We present the largest galaxy weak lensing mass map of the late-time Universe, reconstructed from 270 million galaxies in the DECADE and DES Year 3 datasets, covering 13,000 square degrees. We validate the map through systematic tests against observational conditions (depth, seeing, etc.), finding the map is statistically consistent with no contamination. The large area covered by the mass map makes it a well-suited tool for cosmological analyses, cross-correlation studies and the identification of large-scale structure features. We demonstrate its potential by detecting cosmic filaments directly from the mass map for the first time and validating them through their association with galaxy clusters selected using the Sunyaev-Zeldovich effect from Planck and ACT DR6.

Gatti, M.↗

DOE OSTI2025

DECADE+DES Y3 Weak Lensing Mass Map: A 13,000 deg$^2$ View of Cosmic Structure from 270 Million Galaxies

Gatti, M. [Chicago U., KICP] (ORCID:00000001613487↗

DOE OSTI2021

Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene

Abstract We present a way to dramatically accelerate Gaussian process models for interatomic force fields based on many-body kernels by mapping both forces and uncertainties onto functions of low-dimensional features. This allows for automated active learning of models combining near-quantum accuracy, built-in uncertainty, and constant cost of evaluation that is comparable to classical analytical models, capable of simulating millions of atoms. Using this approach, we perform large-scale molecular dynamics simulations of the stability of the stanene monolayer. We discover an unusual phase transformation mechanism of 2D stanene, where ripples lead to nucleation of bilayer defects, densification into a disordered multilayer structure, followed by formation of bulk liquid at high temperature or nucleation and growth of the 3D bcc crystal at low temperature. The presented method opens possibilities for rapid development of fast accurate uncertainty-aware models for simulating long-time large-scale dynamics of complex materials.

Chemistry↗

DOE OSTI2022

Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to ``identify, define, and catalog publicly disclosed cybersecurity vulnerabilities''. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytics tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve ~10-fold data compression of ~140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.

Panchal, Khyati↗