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At least 1,279 records · Page 71

Processing LiDAR Data to Predict Natural Hazards

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Fairweather, Ian↗

Preparing for Lunar Exploration: Geology and Field Training for Astronauts

NASA astronauts will soon return to the Moon, this time to the lunar south pole. Astronauts will perform traverses, make geologic observations, and collect samples to return to Earth. Lessons from Apollo show that science returns were optimized because crews were well-trained in both spacewalk operations and field geology. In that spirit, our team of geologists introduced a revised geologic training program for in-coming NASA astronauts that includes classroom activities and fieldwork and is split over 2 years. Year 1 focuses on an introduction to geologic concepts capped by a field exercise. Year two focuses on climate change, the Moon, other planets, and additional fieldwork. Our geology curriculum supports astronaut observations from the ISS and is the foundation for future Artemis geology training, which will include lunar science and increasingly complex field training in planetary-relevant locations. A final piece of our training program provides geology and field mapping experiences for NASA engineers, flight controllers, and managers, to help them understand the principles of fieldwork and relevance to lunar exploration. The Year 1 geology training must be an effective introduction for astronauts who have little or no background in geology. We focus the training around a narrowly defined field problem and use a week of classroom training to prepare the astronauts with the specific skills and background they need to carry out a field exercise on volcanic features, structures, and landforms of the Taos Plateau, New Mexico. Classroom modules are hands-on, using satellite imagery, maps, analog models, and samples, and provide the astronauts with specific and relevant experience in how to make observations and describe what they see, recognize, and interpret patterns, infer processes from products, and analyze relationships to build a story based on evidence from a variety of data sources. At the end of each classroom day, astronauts work in teams to build a preliminary geologic map of the field area, adding new observations and interpretations as they learn about topics in the classroom. Each team’s bucket list of target areas to visit helps shape their investigations during their week in the field. On the final day in the field, each astronaut team presents a geologic map, cross section, and geologic interpretation

Geology↗

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. In the first part of the investigation, spatial and spectral features were developed which were employed to automatically recognize terrain features through a clustering algorithm. In this part of the investigation, the size of the cell which is the number of digital picture elements used for computing the spatial and spectral features was varied. It was determined that the accuracy of terrain recognition decreases slowly as the cell size is reduced and coincides with increased cluster diffuseness. It was also proven that a cell size of 17 x 17 pixels when used with the clustering algorithm results in high recognition rates for major terrain classes. ERTS-1 data from five diverse geographic regions of the United States were processed through the clustering algorithm with 17 x 17 pixel cells. Simple land use maps were produced and the average terrain recognition accuracy was 82 percent.

Gramenopoulos, N.↗

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.↗

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗

Higher-order topological corner and bond-localized modes in magnonic insulators

We theoretically investigate a two-dimensional decorated honeycomb lattice framework to realize a second-order topological magnon insulator (SOTMI) phase featuring distinct corner-localized modes. Here, our study emphasizes the pivotal role of spin-magnon mapping in characterizing bosonic topological properties, which exhibit differences from their fermionic counterparts. We employ a symmetry indicator topological invariant to identify and characterize this SOTMI phase, particularly for systems respecting time-reversal and rotational symmetry. Using a spin model defined on a honeycomb lattice geometry, we demonstrate that introducing “kekulé” type distortions yields a topological phase. In contrast, “antikekulé” distortions result in a nontopological magnonic phase. The presence of kekulé distortions manifests in two distinct topologically protected bosonic corner modes—an intrinsic and a pseudo, based on the specific edge terminations. On the other hand, antikekulé distortions give rise to Tamm/Shockley type bond-localized boundary modes, which are nontopological and reliant on particular edge termination. We further investigate the effects of random out-of-plane exchange anisotropy disorder on the robustness of these bosonic corner modes. The distinction between SOTMIs and their fermionic counterparts arises due to the system-specific magnonic onsite energies, a crucial feature often overlooked in prior literature. Our study unveils exciting prospects for engineering higher-order topological phases in magnon systems and enhances our understanding of their unique behavior within decorated honeycomb lattices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Registration of heat capacity mapping mission day and night images

Registration of thermal images is complicated by distinctive differences in the appearance of day and night features needed as control in the registration process. These changes are unlike those that occur between Landsat scenes and pose unique constraints. Experimentation with several potentially promising techniques has led to selection of a fairly simple scheme for registration of data from the experimental thermal satellite HCMM using an affine transformation. Two registration examples are provided.

Watson, K.↗

A search for ultraviolet circumstellar gas absorption features in alpha Piscis Austrinus (Fomalhaut), a possible Beta Pictoris-like system

Archival high-dispersion International Ultraviolet Explorer (IUE) spectra have been used to search for circumstellar gas absorption features in alpha PsA (A3 V), a nearby (6.7 pc) proto-planetary system candidate. Recent sub-millimeter mapping observations around the region of alpha PsA indicate a spatially resolved dust disk like the one seen around Beta Pic. To determine how closely this putative disk resembles that of Beta Pic, we have searched for signatures of circumstellar gaseous absorption in all the available IUE high-dispersion data of alpha PsA. Examination of co-added IUE spectra shows weak circumstellar absorptions from excited levels in the resonance multiplet of Fe II near 2600 A. We also conclude that the sharp C I feature near 1657 A, previously identified as interstellar absorption toward alpha PsA, likely has a circumstellar origin. However, because the weakness of these absorption features, we will consider the presence of circumstellar gas as tentative and should be verified by using the Goddard High-Resolution Spectrograph aboard the Hubble Space Telescope. No corresponding circumstellar absorption is detected in higher ionization Fe III and Al III. Since the collisionally ionized nonphotospheric Al III resonance absorption seen in Beta Pic is likely formed close to the stellar surface, its absence in the UV spectra of alpha PsA could imply that, in contrast with Beta Pic, there is no active gaseous disk infall onto the central star. In the alpha PsA gaseous disk, if we assume a solar abundance for iron and all the iron is in the form of Fe II, plus a disk temperature of 5000 K, the Fe II UV1 absorption at 2611.8743 A infers a total hydrogen column density along the line of sight through the circumstellar disk of N(H) approximately equals 3.8 x 10(exp 17)/cm.

Cheng, K.-P.↗

A comparison of infrared, radar, and geologic mapping of lunar craters

Between 1000 and 2000 infrared (eclipse) and radar anomalies have been mapped on the nearside hemisphere of the moon. A study of 52 of these anomalies indicates that most are related to impact craters and that the nature of the infrared and radar responses is compatible with a previously developed geologic model of crater aging processes. The youngest craters are pronounced thermal and radar anomalies; that is, they have enhanced eclipse temperatures and are strong radar scatterers. With increasing crater age, the associated thermal and radar responses become progressively less noticeable until they assume values for the average lunar surface. The last type of anomaly to disappear is radar enhancement at longer wavelengths. A few craters, however, have infrared and radar behaviors not predicted by the aging model. One previously unknown feature - a field strewn with centimeter-sized rock fragments - has been identified by this technique of comparing maps at the infrared, radar, and visual wavelengths.

Thompson, T. W.↗

The Diviner Lunar Radiometer Compositional Data Products: Description and Examples

The Diviner lunar radiometer has made the first direct global measurements of silicate mineralogy of the lunar surface using multispectral thermal emission mapping. By mid-March, 2011, the first derived compositional data products (level 3) will be released into the Planetary Data System (PDS) Geosciences Node. These products describe the Diviner Science Team's best efforts to determine the position of the Christiansen feature (CF), which is directly related to silicate mineralogy of lunar soils. The initial release of these products include data from the mission's primary mapping phase between 9/17/09 and 9/16/10. This work describes at a high level the creation of Diviner's compositional data products.

Diviner Lunar Radiometer↗

Imaging Flash Lidar for Safe Landing on Solar System Bodies and Spacecraft Rendezvous and Docking

NASA has been pursuing flash lidar technology for autonomous, safe landing on solar system bodies and for automated rendezvous and docking. During the final stages of the landing from about 1 kilometer to 500 meters above the ground, the flash lidar can generate 3-Dimensional images of the terrain to identify hazardous features such as craters, rocks, and steep slopes. The onboard flight computer can then use the 3-D map of terrain to guide the vehicle to a safe location. As an automated rendezvous and docking sensor, the flash lidar can provide relative range, velocity, and bearing from an approaching spacecraft to another spacecraft or a space station. NASA Langley Research Center has developed and demonstrated a flash lidar sensor system capable of generating 16,000 pixels range images with 7 centimeters precision, at 20 Hertz frame rate, from a maximum slant range of 1800 m from the target area. This paper describes the lidar instrument and presents the results of recent flight tests onboard a rocket-propelled free-flyer vehicle (Morpheus) built by NASA Johnson Space Center. The flights were conducted at a simulated lunar terrain site, consisting of realistic hazard features and designated landing areas, built at NASA Kennedy Space Center specifically for this demonstration test. This paper also provides an overview of the plan for continued advancement of the flash lidar technology aimed at enhancing its performance to meet both landing and automated rendezvous and docking applications.

Amzajerdian, Farzin↗

Stanford Thermal Earth Model for the Conterminous United States

Provided here are various forms of the Stanford Thermal Earth Model, as well as the data and methods used for its creation. The predictions produced by this model were visualized in two-dimensional spatial maps across the modeled depths (0-7 km) for the conterminous United States. The thermal earth model is made available as an application programming interface (API) and as feature layers on ArcGIS, which are both provided via links below. A data-driven spatial interpolation algorithm based on physics-informed graph neural networks was used to develop these national temperature-at-depth maps. The model satisfied the three-dimensional heat conduction law by predicting subsurface temperature, surface heat flow, and rock thermal conductivity. Many physical quantities, including bottomhole temperature, depth, geographic coordinates, elevation, sediment thickness, magnetic anomaly, gravity anomaly, gamma-ray flux of radioactive elements, seismicity, and electric conductivity were used as model inputs. Surface heat flow, temperature, and thermal conductivity predictions were constructed for depths of 0-7 km at an interval of 1 km with spatial resolution of 18 km2 per grid cell. The model showed superior temperature, surface heat flow and thermal conductivity mean absolute errors of 4.8C, 8.1 mW/m2 and 0.07 W/(C-m), respectively..

15 GEOTHERMAL ENERGY↗

Detecting Change in Urban Areas at Continental Scales with MODIS Data

Urbanization is one of the most important components of global environmental change, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multitemporal data from multiple satellite data sources to classify c. 2010 urban extent; and (3) mapping newly built areas (2000-2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socioeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of the error in the change detection can be related to definitional issues or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as for providing a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

Urban areas↗

Satellite geological and geophysical remote sensing of Iceland

The author has identified the following significant results. Under a binational, multidisciplinary experiment ERTS-1 imagery is being used to measure and map dynamic natural phenomena in Iceland. A few of the initial results from the project are: (1) a large variety of geological and volcanic features can be studied, particularly on imagery acquired at low sun angle ( 10 deg), which have not been previously recognized; (2) under optimum snow cover conditions, geothermal areas can be discerned by their snowmelt pattern or by warm spring discharge into frozen lakes; (3) a variety of map types at scale of 1:1,000,000 and 1:500,000, can be compiled, made more accurate, or updated (changes in coastline, glaciers, lakes, etc.); (4) the persistence of snow in the highland areas, during the summer months, has important ramifications to rangeland management; (5) false color composites (MSS) permitted the mapping of four types of vegetation; forested, reclaimed, cultivated areas and grasslands, and the mapping of the seasonal change of the vegetation, all of high value to rangeland management when complete, repetitive coverage of Iceland becomes a reality with an operational satellite; and (6) the volcanic eruption on Heimaey was recorded.

Williams, R. S., Jr.↗

Mapping Vesta: First Results from Dawn's Survey Orbit

The geologic objectives of the Dawn Mission [1] are to derive Vesta s shape, map the surface geology, understand the geological context and contribute to the determination of the asteroids origin and evolution. Geomorphology and distribution of surface features will provide evidence for impact cratering, tectonic activity, volcanism, and regolith processes. Spectral measurements of the surface will provide evidence of the compositional characteristics of geological units. Age information, as derived from crater size-frequency distributions, provides the stratigraphic context for the structural and compositional mapping results, thus revealing the geologic history of Vesta. We present here the first results of the Dawn mission from data collected during the approach to Vesta, and its first discrete orbit phase - the Survey Orbit, which lasts 21 days after the spacecraft had established a circular polar orbit at a radius of approx.3000 km with a beta angle of 10deg-15deg.

Jaumann, R.↗

Geoscientific Mapping of Vesta by the Dawn Mission

The geologic objectives of the Dawn Mission are to derive Vesta's shape, map the surface geology, understand the geological context and contribute to the determination of the asteroids' origin and evolution. Geomorphology and distribution of surface features will provide evidence for impact cratering, tectonic activity, volcanism, and regolith processes. Spectral measurements of the surface will provide evidence of the compositional characteristics of geological units. Age information, as derived from crater size-frequency distributions, provides the stratigraphic context for the structural and compositional mapping results into the stratigraphic context and thusrevealing the geologic history of Vesta.

lunar mapping↗

Optimization of stochastic feature properties in laser powder bed fusion

Process parameter selection in laser powder bed fusion (LPBF) controls the as-printed dimensional tolerances, pore formation, surface quality and microstructure of printed metallic structures. Measuring the stochastic mechanical performance for a wide range of process parameters is cumbersome both in time and cost. As such, in this study, we overcome these hurdles by using high-throughput tensile (HTT) testing of over 250 dogbone samples to examine process-driven performance of strut-like small features, ~1 mm 2 in austenitic stainless steel (316 L). The output mechanical properties, porosity, surface roughness and dimensional accuracy were mapped across the printable range of laser powers and scan speeds using a continuous wave laser LPBF machine. Tradeoffs between ductility and strength are shown across the process space and their implications are discussed. While volumetric energy density deposited onto a substrate to create a melt-pool can be a useful metric for determining bulk properties, it was not found to directly correlate with output small feature performance.

316 L stainless steel↗