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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3

Observations of the giant radio lobes region of Centaurus A with SAS 3

Observations of the X-ray flux from the extended radio lobes of the galaxy Centaurus A obtained with the SAS 3 observatory are reported. The 15 x 15 deg region that includes the lobes was mapped by superposing data from raster scans with the horizontal tubular collimator detectors, which have a 1.7 deg FWHM circular field of view. Data obtained is consistent with the presence of superposed emission from the point sources NGC 5128 and MX 1312-42, a previously unreported source detected by the Einstein Observatory IPC. Fluxes of 4.63 + or - 0.14 x 10 to the -10th and 4.6 + or - 0.6 x 10 to the -11th ergs/sq cm per sec were measured for NGC 5128 and MX 1312-42, respectively, with best fit power law spectra of indices 0.83 + or - 0.04 and 0.62 + or - 0.10 and hydrogen column densities of 1.23 + or - 0.10 x 10 to the 23rd and 9.7 + or - 15.0 x 10 to the 21st atoms/sq cm. Results imply an upper limit of 2.9 x 10 to the 11th for the X-ray emission from the extended radio lobes of Cen A between 2 and 10 keV, which indicates a lower limit to the magnetic field in the lobes of 1.6 x 10 to the -6th gauss.

Marshall, F. J.↗

NASA’s Global Imagery Browse Services and Worldview Migrate to Mapbox Vector Tiles: The Drawbacks and Advantages

NASA’s Global Imagery Browse Services (GIBS) is in the process of migrating their vector data from raster tiles to Mapbox Vector Tiles (MVTs). MVTs are becoming ubiquitous in the world of web mapping. Serving data in place of pixels for each feature presents numerous new visualization opportunities as well as various new challenges to overcome. This presentation will cover some of the hardships these teams encountered, the techniques used to overcome those barriers, and it will give you a glimpse at how the user experience was enhanced.

Benjamin King↗

BOREAS TGB-12 Soil Carbon and Flux Data of NSA-MSA in Raster Format

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites. This data set provides: (1) estimates of soil carbon stocks by horizon based on soil survey data and analyses of data from individual soil profiles; (2) estimates of soil carbon fluxes based on stocks, fire history, drain-age, and soil carbon inputs and decomposition constants based on field work using radiocarbon analyses; (3) fire history data estimating age ranges of time since last fire; and (4) a raster image and an associated soils table file from which area-weighted maps of soil carbon and fluxes and fire history may be generated. This data set was created from raster files, soil polygon data files, and detailed lab analysis of soils data that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. Also used were soils data from Susan Trumbore and Jennifer Harden (BOREAS TGB-12). The binary raster file covers a 733-km 2 area within the NSA-MSA.

Hall, Forrest G.↗

BOREAS TE-1 Soils Data Over The SSA Tower Sites in Raster Format

The BOREAS TE-1 team collected various data to characterize the soil-plant systems in the BOREAS SSA. This data set was gridded from vector layers of soil maps that were received from Dr. Darwin Anderson (TE-1), who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the tower sites in the SSA. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

Harmonized geospatial data to support infrastructure siting feasibility planning for energy system transitions

Climate change, energy system transitions, and socioeconomic change are compounding influences affecting the growth of electricity demand. While energy efficiency initiatives and distributed resources can address a significant amount of this demand, the United States will likely still need new utility-scale generation resources. The energy sector uses capacity expansion planning models to determine the aggregate need for new generation, but these models are typically at the state or regional scale and are not equipped to address the wide range of location- and technology-specific issues that are increasingly a factor in power plant siting. To help address these challenges, we have developed the Geospatial Raster Input Data for Capacity Expansion Regional Feasibility (GRIDCERF) data package, a high-resolution product to evaluate siting suitability for renewable and non-renewable power plants in the conterminous United States. GRIDCERF offers 264 suitability layers for use with 56 power plant technologies in a harmonized format that can be easily ingested by geospatially-enabled modeling software allowing for customization to robustly address science objectives when evaluating varying future conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Physics Mining of Multi-Source Data Sets

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

Helly, John↗

Utah FORGE: InSAR Data Best Pairs

This submission provides Interferometric Synthetic Aperture Radar (InSAR) data covering the Utah FORGE site via the TerraSAR-X and TanDEM-X satellite missions operated by the German Space Agency (DLR). Data was collected between 2019/01/01 and 2023/06/30. Interferometric pairs (interferograms) were created using generic mapping tool GMT-SAR processing software. The best 112 pairs were selected based on having short orbital separations (perpendicular baseline less than 5 meters in absolute value).

15 GEOTHERMAL ENERGY↗

Interactive Digital Image Manipulation System (IDIMS)

The implementation of an interactive digital image manipulation system (IDIMS) is described. The system is run on an HP-3000 Series 3 minicomputer. The IDIMS system provides a complete image geoprocessing capability for raster formatted data in a self-contained system. It is easily installed, documentation is provided, and vendor support is available.

Fleming, M. D.↗

Survey of currently available high-resolution raster graphics systems

Presented are data obtained on high-resolution raster graphics engines currently available on the market. The data were obtained through survey responses received from various vendors and also from product literature. The questionnaire developed for this survey was basically a list of characteristics desired in a high performance color raster graphics system which could perform real-time aircraft simulations. Several vendors responded to the survey, with most reporting on their most advanced high-performance, high-resolution raster graphics engine.

Jones, Denise R.↗

Algorithm for Compressing Time-Series Data

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Hawkins, S. Edward, III↗

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

BOREAS TE-20 Soils Data Over the NSA-MSA and Tower Sites in Raster Format

The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set was gridded from vector layers of soil maps that were received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994. The vector layers were gridded into raster files that cover the NSA-MSA and tower sites. The data are stored in binary, image format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).

Hall, Forrest G.↗

CanSIS Regional Soils Data in Vector Format

This data set is the original vector data set received from Canada Soil Information System (CanSIS). The data include the provinces of Saskatchewan and Manitoba. Attribute tables provide the various soil data for the polygons; there is one attribute table for Saskatchewan and one for Manitoba. The data are stored in ARC/INFO export format files. Based on agreements made with Agriculture Canada, these data are available only to individuals and groups that have an official relationship with the BOREAS project. These data are not included on the BOReal Ecosystem-Atmosphere Study (BOREAS) CD-ROM set. A raster version of this data set titled 'BOREAS Regional Soils Data in Raster Format and AEAC Projection' is publicly available and is included on the BOREAS CD-ROM set.

Monette, Bryan↗

The Use of Interactive Raster Graphics in the Display and Manipulation of Multidimensional Data

Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.

Anderson, D. C.↗

User alternatives in post-processing for raster-to-vector conversion

A number of Landsat-based coniferous forest stratum maps have been created of the Eldorado National Forest in California. These maps were produced in raster image format which is not directly usable by the U.S. Forest Service's vector-based Wildland Resource Information System (WRIS). As a solution, raster-to-vector conversion software has been developed for processing classified images into polygonal data structures. Before conversion, however, the digital classification images must be simplified to remove high spatial variance ('noise', 'speckle') and meet a USFS ten acre minimum requirement. A post-processing (simplification) strategy different from those commonly used in raster image processing may be desired for preparing maps for conversion to vector format, because simplification routines typically permit diagonal connections in the process of reclassifying pixels and forming new polygons. Diagonal connections are often undesirable when converting to vector format because they permit polygons to effectively cross over each other and occupy a common location. Three alternative methodologies are discussed for simplifying raster data for conversion to vector format.

Logan, T. L.↗

CD-ROM publication of the Mars digital cartographic data base

The recently completed Mars mosaicked digital image model (MDIM) and the soon-to-be-completed Mars digital terrain model (DTM) are being transcribed to optical disks to simplify distribution to planetary investigators. These models, completed in FY 1991, provide a cartographic base to which all existing Mars data can be registered. The digital image map of Mars is a cartographic extension of a set of compact disk read-only memory (CD-ROM) volumes containing individual Viking Orbiter images now being released. The data in these volumes are pristine in the sense that they were processed only to the extent required to view them as images. They contain the artifacts and the radiometric, geometric, and photometric characteristics of the raw data transmitted by the spacecraft. This new set of volumes, on the other hand, contains cartographic compilations made by processing the raw images to reduce radiometric and geometric distortions and to form geodetically controlled MDIM's. It also contains digitized versions of an airbrushed map of Mars as well as a listing of all feature names approved by the International Astronomical Union. In addition, special geodetic and photogrammetric processing has been performed to derive rasters of topographic data, or DTM's. The latter have a format similar to that of MDIM, except that elevation values are used in the array instead of image brightness values. The set consists of seven volumes: (1) Vastitas Borealis Region of Mars; (2) Xanthe Terra of Mars; (3) Amazonis Planitia Region of Mars; (4) Elysium Planitia Region of Mars; (5) Arabia Terra of Mars; (6) Planum Australe Region of Mars; and (7) a digital topographic map of Mars.

Batson, R. M.↗

Surrogate Distributed Radiological Sources—Part III: Quantitative Distributed Source Reconstructions

In this third part of a multi-paper series, we present quantitative image reconstruction results from aerial measurements of eight different surrogate distributed gamma-ray sources on flat terrain. Here, we show that our quantitative imaging methods can accurately reconstruct the expected shapes, and, after appropriate calibration, the absolute activity of the distributed sources. We conduct several studies of imaging performance versus various measurement and reconstruction parameters, including detector altitude and raster pass spacing, data and modeling fidelity, and regularization type and strength. The imaging quality performance is quantified using various quantitative image quality metrics. Our results confirm the utility of point source arrays as surrogates for truly distributed radiological sources, and advance the quantitative capabilities of Scene Data Fusion gamma-ray imaging methods.

Airborne survey↗

Towards Automated/Semiautomated Extraction of Faults from Lidar Data

The Pajarito fault system is a complex zone of deformation and a seismically active region nestled within the Rio Grande rift in north-central New Mexico. Numerous laterally discontinuous faults and associated folds and fractures interact in a manner that has important implications for seismic hazards and risk mitigation. Previous efforts have established a foundation for the location of lineaments and structures in the Pajarito fault system; however, ensuring the completeness of the current lineament mapping is required for identifying areas for field validation, evaluating the potential for future seismic activity, and better understanding fault interaction. Assistance with this fault-mapping task via automated or semiautomated techniques as applied to lidar data over a large area of interest is highly desirable. A proof-of-concept processing flow which transforms lidar point-cloud data into a raster of surficial fault candidates is described and illustrated herein. We report these initial results hold great promise toward achieving our ultimate goal.

58 GEOSCIENCES↗