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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Automated basin delineation from digital terrain data

While digital terrain grids are now in wide use, accurate delineation of drainage basins from these data is difficult to efficiently automate. A recursive order N solution to this problem is presented. The algorithm is fast because no point in the basin is checked more than once, and no points outside the basin are considered. Two applications for terrain analysis and one for remote sensing are given to illustrate the method, on a basin with high relief in the Sierra Nevada. This technique for automated basin delineation will enhance the utility of digital terrain analysis for hydrologic modeling and remote sensing.

Marks, D.↗
NASA NTRS1999

The Utility and Validity of Kinematic GPS Positioning for the Geosar Airborne Terrain Mapping Radar System

GeoSAR is an airborne, interferometric Synthetic Aperture Radar (IFSAR) system for terrain mapping, currently under development by a consortium including NASA's Jet Propulsion Laboratory (JPL), Calgis, Inc., a California mapping sciences company, and the California Department of Conservation (CaIDOC), with funding provided by the U.S. Army Corps of Engineers Topographic Engineering Center (TEC) and the U.S. Defense Advanced Research Projects Agency (DARPA). IFSAR data processing requires high-accuracy platform position and attitude knowledge. On 9 GeoSAR, these are provided by one or two Honeywell Embedded GPS Inertial Navigation Units (EGI) and an Ashtech Z12 GPS receiver. The EGIs provide real-time high-accuracy attitude and moderate-accuracy position data, while the Ashtech data, post-processed differentially with data from a nearby ground station using Ashtech PNAV software, provide high-accuracy differential GPS positions. These data are optimally combined using a Kalman filter within the GeoSAR motion measurement software, and the resultant position and orientation information are used to process the dual frequency (X-band and P-band) radar data to generate high-accuracy, high -resolution terrain imagery and digital elevation models (DEMs). GeoSAR requirements specify sub-meter level planimetric and vertical accuracies for the resultant DEMS. To achieve this, platform positioning errors well below one meter are needed. The goal of GeoSAR is to obtain 25 cm or better 3-D positions from the GPS systems on board the aircraft. By imaging a set of known point target corner-cube reflectors, the GeoSAR system can be calibrated. This calibration process yields the true position of the aircraft with an uncertainty of 20- 50 cm. This process thus allows an independent assessment of the accuracy of our GPS-based positioning systems. We will present an overview of the GeoSAR motion measurement system, focusing on the use of GPS and the blending of position data from the various systems. We will present the results of our calibration studies that relate to the accuracy the GPS positioning. We will discuss the effects these positioning, errors have on the resultant DEM products and imagery.

Freedman, Adam↗
NASA NTRS2004

High Resolution Digital Elevation Models of Pristine Explosion Craters

In order to effectively capture a realistic terrain applicable to studies of cratering processes and landing hazards on Mars, we have obtained high resolution digital elevation models of several pristine explosion craters at the Nevada Test Site. We used the Airborne Terrain Mapper (ATM), operated by NASA's Wallops Flight Facility to obtain DEMs with 1 m spacing and 10 cm vertical errors of 4 main craters and many other craters and collapse pits. The main craters that were mapped are Sedan, Scooter, Schooner, and Danny Boy. The 370 m diameter Sedan crater, located on Yucca Flat, is the largest and freshest explosion crater on Earth that was formed under conditions similar to hypervelocity impact cratering. As such, it is effectively pristine, having been formed in 1962 as a result of a controlled detonation of a 100 kiloton thermonuclear device, buried at the appropriate equivalent depth of burst required to make a simple crater. Sedan was formed in alluvium of mixed lithology and subsequently studied using a variety of field-based methods. Nearby secondary craters were also formed at the time and were also mapped by ATM. Adjacent to Sedan and also in alluvium is Scooter, about 90 m in diameter and formed by a high-explosive event. Schooner (240 m) and Danny Boy (80 m) craters were also important targets for ATM as they were excavated in hard basalt and therefore have much rougher ejecta. This will allow study of ejecta patterns in hard rock as well as engineering tests of crater and rock avoidance and rover trafficability. In addition to the high resolution DEMs, crater geometric characteristics, RMS roughness maps, and other higher-order derived data products will be generated using these data. These will provide constraints for models of landing hazards on Mars and for rover trafficability. Other planned studies will include ejecta size-frequency distribution at the resolution of the DEM and at finer resolution through air photography and field measurements, correlation of ejecta size and composition with radar and visible-thermal IR remote sensing signatures, and comparison of these results with similar measurements of Mars. The final DEMs, ancillary data sets, and derived data products will be made available to the community.

T G Farr↗
NASA NTRS2013

Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

Moore, Angelyn W.↗
NASA NTRS1983

Wildland inventory and resource modeling for Douglas and Carson City Counties, Nevada, using LANDSAT and digital terrain data

The potential of using LANDSAT satellite imagery to map and inventory pinyon-juniper desert forest types in Douglas and Carson City Counties, Nevada was demonstrated. Specific map and statistical products produced include land cover, mechanical operations capability, big game winter range habitat, fire hazard, and forest harvestability. The Nevada Division of Forestry determined that LANDSAT can produce a reliable and low-cost resource data. Added benefits become apparent when the data are linked to a geographical information system (GIS) containing existing ownership, planning, elevation, slope, and aspect information.

Brass, J. A.↗
NASA NTRS1981

Using radar image simulation to assess relative geometric distortions inherent in radar imagery

A unique method for observing the relative contributions of backscatter and propagation effects is afforded by radar image simulation. Digital terrain data are used in modeling radar image formation. Backscatter and propagation effects are modeled separately. These are incorporated serially and the image expression of each is noted. Sequences of images are presented illustrating these effects over a range of slopes and angles of incidence. The conclusions reached are that at angles of incidence that are smaller than the average slope of the terrain in a region, propagation phenomena predominate. As the angle of incidence increases beyond this, the radar image portrays an increasingly faithful representation of the backscatter from the ground. It is also demonstrated that digital simulation affords an important tool for evaluating complex interactions between the ground and radar, for training users in radar image interpretation, and for selecting optimum sensor parameters for particular applications.

Kaupp, V. H.↗
DOE OSTI2020

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling. Analogous “depressions” also arise in image processing and morphological segmentation, where they may represent noise, features of interest, or both. Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region. We treat depressions as networks in a way that is analogous to surface-water flow paths, in which individual sub-depressions merge together to form meta-depressions in a process that continues until they begin to drain externally. This hierarchy can be used to selectively fill or breach depressions or to accelerate dynamic models of hydrological flow. Complete, well-commented, open-source code and correctness tests are available on GitHub and Zenodo.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities

Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.

Quattrochi, Dale A.↗
DOE OSTI2023

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Surface Modeling to Support Small-Body Spacecraft Exploration and Proximity Operations

In order to simulate physically plausible surfaces that represent geologically evolved surfaces, demonstrating demanding surface-relative guidance navigation and control (GN&C) actions, such surfaces must be made to mimic the geological processes themselves. A report describes how, using software and algorithms to model body surfaces as a series of digital terrain maps, a series of processes was put in place that evolve the surface from some assumed nominal starting condition. The physical processes modeled in this algorithmic technique include fractal regolith substrate texturing, fractally textured rocks (of empirically derived size and distribution power laws), cratering, and regolith migration under potential energy gradient. Starting with a global model that may be determined observationally or created ad hoc, the surface evolution is begun. First, material of some assumed strength is layered on the global model in a fractally random pattern. Then, rocks are distributed according to power laws measured on the Moon. Cratering then takes place in a temporal fashion, including modeling of ejecta blankets and taking into account the gravity of the object (which determines how much of the ejecta blanket falls back to the surface), and causing the observed phenomena of older craters being progressively buried by the ejecta of earlier impacts. Finally, regolith migration occurs which stratifies finer materials from coarser, as the fine material progressively migrates to regions of lower potential energy.

Riedel, Joseph E.↗
DOE OSTI2024

DEM, DSM, and Cleaned LiDAR Point Cloud Data from the NGEE Arctic UAS Campaigns at the Teller 27 Field Site from 2017 and 2018, Seward Peninsula, Alaska

A Digital Elevation Model (DEM) and Digital Surface Model (DSM) were derived from airborne Light Detection and Ranging (LiDAR) data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) quadcopter and hexacopter platforms operated by Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) scientists from the EES-14 group at LANL. These data were collected in August 2017 and July 2018 at the NGEE Arctic field site near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway between Nome, Alaska and Teller, Alaska. A Vulcan Raven X8 Airframe (Mitcheldean, Gloucestershire, UK), DJI Matrice 600 Pro Airframe (Shenzhen, China), and Routescene UAV LiDARSystem (Edinburgh, Scotland, UK) were used to collect LiDAR data. Following pre-processing in Routescene LidarViewer Pro software, the LiDAR point clouds were cleaned and processed using CloudCompare software to separate ground and off-ground points. A high resolution DEM and DSM were then created using ArcGIS Pro software. This data package contains fully cleaned point clouds of ground and off-ground points (.las), a 25 cm DEM (.tif), and a 25 cm DSM (.tif) for the Teller 27 field site. Ancillary aircraft data, flight mission parameters, weather conditions, and raw lidar data and imagery can be found in the L0 datasets for these campaigns: NGA299 (2017) and NGA297 (2018). Minimally processed point clouds and auxiliary files can be found in the L1 dataset: NGA304 (2017 and 2018).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

A clear-sky spectral solar radiation model for snow-covered mountainous terrain

A clear-sky spectral solar radiation model for direct and diffuse fluxes, combined with topographic calculations from digital terrain data, computes either incident, net, or reflected solar radiation at any point on a snow surface in mountainous terrain. The radiation may be integrated over any wavelength range from 250 to 5000 nm, or over any time step. Atmospheric attenuation parameters are ozone, water vapor, the Angstrom turbidity coefficient and exponent, and the absorptance to reflectance ratio of the atmospheric aerosols. The model derives these, from measurements which may contain both systematic and random errors, by finding the least squares solution to an overdetermined set of nonlinear equations. For calculations over a specified area, it employs table look-up procedures, so that computation speed for the spectral model approaches that for a lumped model. Thus it may be useful as part of a snow surface energy budget calculation over a drainage basin.

Dozier, J.↗
NASA NTRS1991

Topography estimation with interferometric synthetic aperture radar using fringe detection

Methods are presented for using Synthetic Aperture Radar (SAR) interferometry data to estimate surface topography. An expression is given to relate the elevation of a ground point to the phase difference of SAR images received from two spatially separated antennas. An iterative algorithm which solves for the position and elevation of each point in the image simultaneously is developed. One of the critical issues that determines the accuracy of the terrain mapping is the phase unwrapping. An approach to the problem by fringe line detection is proposed. The algorithms are tested with two Seasat SAR images of terrain near Yellowstone National Park. The resultant elevation map is compared with a USGS terrain elevation model. The error of the SAR elevation with respect to the digital terrain map is about 8.2 percent of the total terrain variation.

Lin, Qian↗
DOE OSTI2023

Data, scripts, and figures associated with a manuscript studying impact of climate and topography on post-fire vegetation recovery.

This data package is associated with the publication “Impact of Topography and Climate on Post-fire Vegetation Recovery Across Different Burn Severity and Land Cover Types through Machine Learning” submitted to Remote Sensing of Environment (Zahura et al. 2023). In this research, a machine learning algorithm, random forest (RF), was utilized to examine the impact of climate and topography on post-fire vegetation recovery. We used enhanced vegetation index (EVI) to examine varying burn severity and land cover types. The data package includes the input files for RF model training, outputs from model predictions and analysis, and python scripts to run the model, analyze the results to understand model performance and interpretability, and plot manuscript figures. This data package contains three folders (Data, Scripts, and Figures), a file-level metadata (FLMD) csv, and a data dictionary (dd) csv. Please see Postfire_recovery_flmd.csv for a list of all files contained in this data package and descriptions for each. The data dictionary (Postfire_recovery_dd.csv) describes the csv column headers. The “Data” folder provides all the inputs and outputs to train the RF model, evaluate performance, and interpret predictions. The “Scripts” folder contains python scripts and jupyter notebooks for model training and result analysis. The “Figures” folder includes the figures used in the manuscript in “.png” and “.jpg” format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Onslow Beach Washover Fan Morphology from 2012 to 2015

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of encroachment pressures in surrounding areas, impairments due to other anthropogenic disturbances, and changes in climate and sea level. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and also optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the second 5 years of the program (DCERP2) are presented in the DCERP2 Final Report.There were four overarching objectives of DCERP2. The first objective was to understand the effects of climate change impacts, including warming temperatures, variability in the hydrological cycle, storm events, and sea level rise on the coastal ecosystems at MCBCL from observations and measurements made over the 10-year program. The second objective was to understand the carbon cycle of the coastal and terrestrial ecosystems at MCBCL through a highly integrated sampling program. The third objective was to develop models, tools, and indicators to evaluate current and projected future ecosystem state changes and translate scientific findings into actionable information for installation managers. The last objective was to recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.These grid files were created from data collected using a Riegl 3-D laser scanner. Millions of x, y, and z points from the F2 Washover Fan on Onslow Beach were processed using the MARS software package to define a bare-earth model. Grid files were imported into Golden Software Surfer version 19 for editing and exported from that application as .grd files. Files can be opened in Surfer or ArcMap, but the coordinate system information will be lost if opened in ArcMap. These data were collected to quantify the morphological changes that occur on a washover fan through time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Vegetation classification map and covariates associated with NEON AOP survey, East River, CO 2018

This package includes geospatial data layers developed to investigate how environmental gradients—specifically topography and near-surface soil properties—drive the spatial arrangement of dominant plant communities in mountainous watersheds. The geospatial products, which support the analysis of these ecological relationships, are derived from airborne hyperspectral and LiDAR datasets acquired by the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP), in conjunction with an extensive ground field campaign conducted in summer 2018. This work is part of the DOE Watershed Function Science Focus Area (SFA) and features geospatial datasets developed based on observations and ground data collected at East River, Colorado, in collaboration with the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) survey in June 2018. Classification Map: - Classification Map (PNG, GeoTIFF): Derived from hyperspectral and LiDAR airborne data using a machine learning approach. - Class Code Mapper (CSV): Associates pixel values with corresponding vegetation/non-vegetation classes. - Classification Reference Data (CSV): Reference data used in the machine learning procedure. LiDAR-Derived Products: - Topographical Metrics (GeoTIFFs): Elevation, slope, curvature, TWI, TPI, solar insolation, and canopy height model (CHM), smoothed with a 5x5 pixel window. Vegetation Indices: - GeoTIFFs of NDVI, NDNI, NDWI: Vegetation indices derived from hyperspectral data. Urban Masks: - Urban Mask (GeoTIFF): Applied to the mapping to convert bare soil classes to urban classes. Software Compatibility: GeoTIFFs: Can be visualized with GIS software or libraries that support GeoTIFF images. CSV Files: Can be opened with any software that handles comma-separated values. The FLMD file provides details and links to the source datasets used to derive the products. The manuscript (in the Method session) provides details on how each product was derived. This work was 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. Update on 2026-03-25: Since the original dataset publication date of 02/28/2020, this package has a new classification map derived by an improved methodology. This update also includes additional ground data that improved the representation of some of the communities. See the methods for further details on what has changed between versions.

2018 NEON and 2025 CHESS Campaigns↗