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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

LiDAR-Inertial Based Navigation and Mapping for Precision Landing

Future lander missions will travel to ambitious, scientifically interesting locations near rough and dangerous terrain. They will need to operate with limited prior information about the terrain, and under varying lighting conditions. Landing safely and precisely in the face of these challenges is difficult for existing vision-based landing systems, which require detailed orbital reconnaissance, a priori hazard maps, and impose time-of-day restrictions on landing to ensure similar lighting conditions in orbital and descent imagery. Advanced 3D imaging LiDAR systems currently under development, and originally intended for single-scan hazard detection, have the potential to be operated continuously from altitudes of up to 5 km. Used together with existing inertial measurement units (IMUs), these sensors open a path-to-flight for a full navigation and mapping system, which could replace or augment a traditional landing sensor suite. A landing system based around these sensors can perform accurate altimetry, map-relative localization (MRL), LiDAR-inertial odometry, and map refinement in an illumination-insensitive manner, over unknown or partially known terrain. This paper outlines preliminary work on a LiDAR-inertial landing system that: estimates the spacecraft trajectory during entry, descent, and landing (EDL); and maps the topography of the terrain below, for future use in hazard detection and avoidance. An incremental, factor graph based, smoothing approach is used to solve for the maximum a posteriori trajectory of spacecraft states. Integrated IMU measurements and features tracked in adjacent range and intensity images are used to estimate motion (LiDAR-inertial odometry). LiDAR scans are binned into motion-corrected digital elevation models (DEMs), which are matched to an existing orbital topographic map to provide absolute position information (MRL). The estimated trajectory is then used to project the LiDAR scans into the map frame, creating a variable-resolution quadtree topographic map suitable for hazard detection and avoidance. Existing topographic maps from throughout the solar system (i.e., Earth, the Moon, Mars, Ceres, Vesta, Europa, Enceladus, and Eros) are upsampled for use in EDL simulations. The Mars 2020 Lander Vision System Simulator (LVSS) is extended to simulate LiDAR-inertial data for realistic EDL trajectories. Results of the algorithm operating on the simulated data are presented. Estimated spacecraft trajectory and refined map are compared to ground truth to assess estimation accuracy.

Katake, Anup↗
NASA NTRSDate not supplied

Interoperable Map Services with Performance Tuning for Earth Science Data through API-Tiles and Dynamic API-Styles

NASA’s Goddard Earth Sciences Data and Information Services Center (GES DISC) provides access to a wide range of global climate data from various satellite missions and models. However, the visualization and analysis of these data can be challenging due to their large volume, complex structure, and diverse formats. This study presents the implementation of interoperable map services (API-Maps) with performance tuning using API-Tiles and dynamic API-Styles. API-Maps is a standard for defining and exposing map services through RESTful (representational state transfer) APIs (application programming interfaces). API-Tiles is a technique for generating and delivering map tiles on demand from any data source. API-Styles is a method for dynamically applying styles to map tiles based on user preferences or data attributes. The use of API-Tiles and dynamic API-Styles enhances the performance and scalability of the map services, allowing for smooth and interactive visualization of large datasets. Two types of Earth Science data sources from the NASA GES DISC are used in the experiment: regularly gridded data, such as Global Precipitation Measurement (GPM) precipitation data, and low processing level data, such as low-level data of atmospheric composite measurements from the TROPOspheric Monitoring Instrument (TROPOMI) mission. Re-gridding of swath data (low level data - e.g. Level 2) of atmospheric composites (e.g. TROPOMI products, such as nitrogen dioxide, ozone and aerosol optical depth) is applied to enable the Web-based, interoperable, tiled, and styled mapping (rendering) services of such data. The results demonstrate the effectiveness of the proposed approach in providing fast and efficient access to Earth science data through interoperable map services.

Geographic Information System↗
NASA NTRSDate not supplied

Terrestrial Demonstration of Orbital Mapping and Validation Capabilities Over a Lunar Surface Analog

The Lunar Navigation Maps (LuNaMaps) project has improved existing tools and processes and developed new tools and processes to support the generation and validation of navigation maps of the lunar surface from orbital imagery. To demonstrate the advancements made through the LuNaMaps project, we conducted a terrestrial demonstration obtaining “orbital” imagery of the Lunar Surface Proving Ground (LSPG) at Astrobotic’s test facility in Mojave California. The LSPG is a 100 m by 100 m pad built to mimic the features and appearance of the lunar surface. In this paper we describe the planning and results of the test, including the capture of imagery for building the maps, the map building processes, building of a “truth map” using traditional surveying tools, and the map validation processes. We demonstrate how the built map compares to the “truth map” and how the validation processes provided insight to this comparison. Additionally, we describe an upcoming partner test in which the navigation maps will be used in a terrain relative navigation (TRN) technology demonstration over the same LSPG surface.

mapping↗
DOE OSTI2025

Q -score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps

Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

B factors↗
NASA NTRS2000

BOREAS Hardcopy Maps

Boreal Ecosystem-Atmospheric Study (BOREAS) hardcopy maps are a collection of approximately 1,000 hardcopy maps representing the physical, climatological, and historical attributes of areas covering primarily the Manitoba and Saskatchewan provinces of Canada. These maps were collected by BOREAS Information System (BORIS) and Canada for Remote Sensing (CCRS) staff to provide basic information about site positions, manmade features, topography, geology, hydrology, land cover types, fire history, climate, and soils of the BOREAS study region. These maps are not available for distribution through the BOREAS project but may be used as an on-site resource. Information is provided within this document for individuals who want to order copies of these maps from the original map source. Note that the maps are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of the maps that are available. This inventory listing is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). For hardcopies of the individual maps, contact the sources provided.

Hall, Forrest G.↗
NASA NTRS2001

Assessment of the Relative Accuracy of Hemispheric-Scale Snow-Cover Maps

There are several hemispheric-scale satellite-derived snow-cover maps available, but none has been fully validated. For the period October 23 - December 25, 2000, we compare snow maps of North America derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) National Operational Hydrologic Remote Sensing Center (NOHRSC), which both rely on satellite data from the visible and near-infrared parts of the spectrum; we also compare MODIS and Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) passive-microwave snow maps. The maps derived from visible and near-infrared data are more accurate for mapping snow cover than are the passive-microwave-derived maps, however discrepancies exist as to the location and extent of the snow cover among those maps. The large (approx. 30 km) footprint of the SSM/I data and the difficulty in distinguishing wet and shallow snow from wet or snow-free ground, reveal differences up to 5.32 million sq km in the amount of snow mapped using MODIS versus SSM/I data. Algorithms that utilize both visible and passive-microwave data, which would take advantage of the all-weather mapping ability of the passive-microwave data, will be refined following the launch of the Advanced Microwave Scanning Radiometer (AMSR) in the fall of 2001.

Hall, Dorothy K.↗
NASA NTRS2002

An Overview of Trajectory Design Operations for the Microwave Anisotropy Probe (MAP) Mission

The main science objective of the Microwave Anisotropy Probe (MAP) mission is to produce an accurate full-sky map of the cosmic microwave background temperature fluctuations - anisotropy. MAP will collect these measurements from a lissajous orbit about the Sun-Earth/Moon L2 Lagrange Point. The NASA Goddard Space Flight Center (GSFC) Flight Dynamics Analysis Branch provided mission analysis, maneuver planning and maneuver calibration for the MAP spacecraft. This paper will provide an overview of the MAP trajectory design, a summary of the maneuvers executed. Differences from the pre-launch nominal plan will also be discussed. During the MAP phasing loops, MAP performed three calibration maneuvers in order to characterize the performance of the primary sets of thrusters - +X, +Z, and -Z. The calibration maneuvers were designed to minimize their impact on the trajectory. Four maneuvers were performed to set up the gravity assist of the Moon - required to propel MAP out to its orbit about L2. These maneuvers were performed at the three phasing loop perigees and at 18 hours after the final perigee. It became necessary to alter some of the perigee maneuvers in order to shape the gravity assist. This shaping was done to help meet some mission goals. In particular, the gravity assist was changed slightly in order to remove lunar shadows in both the cruise out to L2 and in the first revolution about L2. This amounted to a change in the phasing loop AV of less than 1 m/s. After the gravity assist, two mid-course correction (MCC) maneuvers were performed in order to fine-tune the trajectory. MCC1 was used to clean up and errors which resulted from the gravity assist. MCC2 was performed in order to mitigate a large stationkeeping maneuver following a crucial instrument calibration period during the cruise phase. MAP executed it's first stationkeeping maneuver in January 16th and is ready for a second calibration period during late Winter / early Spring. Further information concerning subsequent stationkeeping maneuver will be added as they become available.

Cuevas, Osvaldo O.↗
NASA NTRS2004

EGRET Diffuse Gamma Ray Maps Between 30 MeV and 10 GeV

This paper presents all-sky maps of diffuse gamma radiation in various energy ranges between 30 MeV and 10 GeV, based on data collected by the EGRET instrument on the Compton Gamma Ray Observatory. Although the maps can be used for a variety of applications, the immediate goal is the generation of diffuse gamma-ray maps which can be used as a diffuse background/foreground for point source analysis of the data to be obtained from new high-energy gamma-ray missions like GLAST and AGILE. To generate the diffuse gamma maps from the raw EGRET maps, the point sources in the Third EGRET Catalog were subtracted out using the appropriate point spread function for each energy range. After that, smoothing was performed to minimize the effects of photon statistical noise. A smoothing length of 1deg was used for the Galactic plane maps. For the all-sky maps, a procedure was used which resulted in a smoothing length roughly equivalent to 4deg. The result of this work is 16 maps of different energy intervals for [b]less than or equal to 20deg, and 32 all-sky maps, 16 in equatorial coordinates (J2000) and 16 in Galactic coordinates.

Cillis, A. N.↗
NASA NTRS2004

EGRET Diffuse Gamma Ray Maps Between 30 MeV and 10 GeV

This paper presents all-sky maps of diffuse gamma radiation in various energy ranges between 30 MeV and 10 GeV, based on data collected by the EGRET instrument on the Compton Gamma Ray Observatory. Although the maps can be used for a variety of applications. the immediate goal is the generation of diffuse gamma-ray maps which can be used as a diffuse background/foreground for point source analysis of the data to be obtained from new high-energy gamma-ray missions like GLAST and AGILE. To generate the diffuse gamma maps from the raw EGRET maps, the point sources in the Third EGRET Catalog were subtracted out using the appropriate point spread function for each energy range. After that, smoothing was performed to minimize the effects of photon statistical noise. A smoothing length of 1 deg vas used for the Galactic plane maps. For the all-sky maps, a procedure was used which resulted in a smoothing length roughly equivalent to 4 deg. The result of this work is 16 maps of different energy intervals for absolute value of b < or equal to 20 deg, and 32 all-sky maps, 16 in equatorial coordinates (J2000) and 16 in Galactic coordinates.

Cillis, A, N.↗
DOE OSTI2026

SPT-3G D1: Maps of the millimeter-wave sky from 2019 and 2020 observations of the SPT-3G Main field

Maps of the sky in millimeter wavelengths contain rich information on cosmology through anisotropies of the cosmic microwave background (CMB). Creating multifrequency sky maps of anisotropies in the $I$, $Q$, and $U$ Stokes parameters is one of the first steps of CMB cosmology analyses. In this work, we describe the production and validation of a set of sky maps from the South Pole Telescope's third-generation camera, SPT-3G. The maps are from data taken in frequency bands centered at 95, 150, and 220 GHz and taken during the first two years, 2019 and 2020, of the SPT-3G Main survey, which covers $4\%$ of the sky. We applied high-pass filters to time series of individual detectors and binned the filtered time series samples into map pixels. After that, we calibrated and cleaned the maps to reduce known systematic errors. In addition, we searched for other systematic errors through null tests and mitigated a significant systematic error detected therein. The white noise levels of the full-depth maps of the $I$ Stokes parameter are $5.4$, $4.4$, and $16.2$$\mathrm{μK}$-$\mathrm{arcmin}$ in the 95, 150, and 220 GHz bands, respectively, and $8.4$, $6.6$, and $25.8$$\mathrm{μK}$-$\mathrm{arcmin}$ for $Q/U$. These maps are the deepest to date used for measurements of mid-to-high-$\ell$ primary temperature and $E$-mode polarization CMB anisotropies, and reconstructions of the CMB gravitational lensing potential. We make these maps and supporting data products publicly accessible.

Quan, W. [Argonne (main); Chicago U., EFI; Chicago↗
NASA NTRSDate not supplied

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗
NASA NTRS2018

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning

This paper discusses research methodology to develop Land Use Land Cover (LULC) mapsfor the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellitedata. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthlyNDVI maps with the Time Series Product Tool software package and then used to classify regionallycommon forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATAclustering was used to derive most LULC classifications. MODIS and Landsat classifications werecombined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB.The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared randomlocations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs,MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commissiondata (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%.The project enabled updated regional LULC maps that included more detailed agriculture LULCtypes. LULC maps were supplied to project partners to improve use of Soil andWater AssessmentTool for modeling hydrology and water use, plus enhance LMB water and disaster managementin a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planningand assessment.

land use land cover mapping; SWAT hydrologic model↗
NASA NTRSDate not supplied

Building Lunar Maps for Terrain Relative Navigation and Hazard Detection Applications

Terrain Relative Navigation (TRN) systems localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map. The spacecraft position estimates can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.

Lunar Maps↗
DOE OSTI2025

Stellar reddening map from DESI imaging and spectroscopy

We present new Galactic reddening maps of the high Galactic latitude sky using DESI imaging and spectroscopy. We directly measure the reddening of 2.6 million stars by comparing the observed stellar colors in $g-r$ and $r-z$ from DESI imaging with the synthetic colors derived from DESI spectra from the first two years of the survey. The reddening in the two colors is on average consistent with the Fitzpatrick (1999) extinction curve with $R_\mathrm{V}=3.1$ . We find that our reddening maps differ significantly from the commonly used Schlegel et al. (1998) (SFD) reddening map (by up to 80 mmag in $E(B-V)$ ), and we attribute most of this difference to systematic errors in the SFD map. To validate the reddening map, we select a galaxy sample with extinction correction based on our reddening map, and this yields significantly better uniformity than the SFD extinction correction. Finally, we discuss the potential systematic errors in the DESI reddening measurements, including the photometric calibration errors that are the limiting factor on our accuracy. The $E(g-r)$ and $E(r-z)$ maps presented in this work, and for convenience their corresponding $E(B-V)$ maps with SFD calibration, are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. The vegetation map in preparation at the time of the last report was refined and labeled. This map is presented as an indication of the spatial and classificatory detail possible from interpretations of enlarged ERTS-1 color photographs. Using this map, areas covered by the several vegetation types characterized by white spruce were determined by planimetry. A 1:63,360 scale land use map of the Juneau area was drawn. This map incorporates the land use classification system now under development by the U.S. Geological Survey. The ERTS-1 images used in making the Juneau map were used to determine changes in surface area of the terminal zones of advancing and receding glaciers, the Taku, Norris, and Mendenhall. A new 1:63,360 scale land use map of the Bonanza Creek Experimental Forest and vicinity was drawn. Several excellent new sciences of test areas were received from NASA in color-infrared transparency format. These are being used for making photographic prints for analysis and mapping according to procedures outlined in this report.

Anderson, J. H.↗
NASA NTRS1978

Proposal for a study of computer mapping of terrain using multispectral data from ERTS-A for the Yellowstone National Park test site

The author has identified the following significant results. A terrain map of Yellowstone National Park showed plant community types and other classes of ground cover in what is basically a wild land. The map comprised 12 classes, six of which were mapped with accuracies of 70 to 95%. The remaining six classes had spectral reflectances that overlapped appreciably, and hence, those were mapped less accurately. Techniques were devised for quantitatively comparing the recognition map of the park with control data acquired from ground inspection and from analysis of sidelooking radar images, a thermal IR mosaic, and IR aerial photos of several scales. Quantitative analyses were made in ten 40 sq km test areas. Comparison mechanics were performed by computer with the final results displayed on line printer output. Forested areas were mapped by computer using ERTS data for less than 1/4 the cost of the conventional forest mapping technique for topographic base maps.

Smedes, H. W.↗
NASA NTRS1979

Impact of cell size on inventory and mapping errors in a cellular geographic information system

The author has identified the following significant results. The effect of grid position was found insignificant for maps but highly significant for isolated mapping units. A modelable relationship between mapping error and cell size was observed for the map segment analyzed. Map data structure was also analyzed with an interboundary distance distribution approach. Map data structure and the impact of cell size on that structure were observed. The existence of a model allowing prediction of mapping error based on map structure was hypothesized and two generations of models were tested under simplifying assumptions.

Wehde, M. E.↗
NASA NTRS1982

Mapping of wildlife habitat in Farmington Bay, Utah

Mapping was accomplished through the interpretation of high-altitude color infrared photography. The feasibility of utilizing LANDSAT digital data to augment the analysis was explored; complex patterns of wildlife habitat and confusion of spectral classes resulted in the decision to make limited use of LANDSAT data in the analysis. The final product is a map which delineates wildlife habitat at a scale of 1:24,000. The map is registered to and printed on a screened U.S.G.S. quadrangle base map. Screened delineations of shoreline contours, mapped from a previous study, are also shown on the map. Intensive field checking of the map was accomplished for the Farmington Bay Waterfowl Management Area in August 1981; other areas on the map received only spot field checking.

Jaynes, R. A.↗