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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Ground support for Space Shuttle earth observations by the NASA environment remote sensing analysis facility (ERSAF)

The functions and capabilities of the NASA Environment Remote Sensing Analysis Facility (ERSAF) located at the Johnson Space Center are described. ERSAF provides dedicated support to earth-observation activities and Earth-looking payloads conducted aboard the Space Shuttle. This support merges environmental satellite imagery with high-resolution film products and digital imagery acquired aboard the Space Shuttle. ERSAF utilizes several computer systems with specialized software to process and analyze environmental information as well as data acquired from the Space Shuttle. These computer systems and the image analysis capabilities are discussed.

Chambers, M. A.↗
NASA NTRS2011

NASA's Earth Observing System Data and Information System - EOSDIS

This slide presentation reviews the work of NASA's Earth Observing System Data and Information System (EOSDIS), a petabyte-scale archive of environmental data that supports global climate change research. The Earth Science Data Systems provide end-to-end capabilities to deliver data and information products to users in support of understanding the Earth system. The presentation contains photographs from space of recent events, (i.e., the effects of the tsunami in Japan, and the wildfires in Australia.) It also includes details of the Data Centers that provide the data to EOSDIS and Science Investigator-led Processing Systems. Information about the Land, Atmosphere Near-real-time Capability for EOS (LANCE) and some of the uses that the system has made possible are reviewed. Also included is information about how to access the data, and evolutionary plans for the future of the system.

Ramapriyan, Hampapuram K.↗
NASA NTRSDate not supplied

Building Capacity to Use Earth Observations for Wildfire Risk Reduction and Resilience Applications: A Summary of NASA’s DEVELOP 2022 Wildfire Projects

NASA’s DEVELOP Program engages individuals and organizations in 10-week feasibility studies to apply NASA Earth observations (EO) to decision makers’ needs. DEVELOP maintains a balance of projects across nine application areas, one of which is Wildfires. DEVELOP's Wildfires application area supports pre-fire (fuel loading, fire risk), during (active fire detection), and post-fire (fire extent, intensity) monitoring and modeling. In 2022 so far, DEVELOP has conducted six projects with Wildfires as a primary or secondary component across a diverse set of study areas. This presentation introduces DEVELOP, its approach to capacity building, key partnerships, and project results highlighting the capabilities of EO for enhanced decision-making regarding wildfires.

Wildfire↗
NASA NTRS1975

Annual review of earth observations from space

An overview is given of the present state of satellites making observations of the earth. Satellite systems discussed include the NOAA series of Synchronous Meteorological Satellites (SMS) and sun-synchronous satellites, the two LANDSATS (formerly called ERTS), and the NIMBUS series. Examples are presented of the types of observations being made as well as their purposes. These include observations of synoptic and mesoscale atmospheric processes for daily weather forecasting, global atmospheric processes for long-range weather forecasting, planetary radiation budget and ocean circulation for monitoring climatic trends, earth dynamics and tectonic structure for mineral exploration and assessing earthquake hazards, atmospheric composition and water quality for environment monitoring, and thematic mapping for monitoring land use, managing crops and water resources, and assessing environmental impacts.

Nordberg, W.↗
NASA NTRS1988

Earth Observing System (EOS) advanced altimetry

In the post-TOPEX era, satellite radar altimeters will be developed with the capability of measuring the earth's surface topography over a wide swath of coverage, rather than just at the satellite's nadir. The identification of potential spacecraft flight missions in the future was studied. The best opportunity was found to be the Earth Observing System (EOS). It is felt that an instrument system that has a broad appeal to the earth sciences community stands a much better chance of being selected as an EOS instrument. Consequently, the Topography and Rain Radar Imager (TARRI) will be proposed as a system that has the capability to profile the Earth's topography regardless of the surface type. The horizontal and height resolutions of interest are obviously significantly different over land, ice, and water; but, the use of radar to provide an all-weather observation capability is applicable to the whole earth. The scientific guidance for the design and development of this instrument and the eventual scientific utilization of the data produced by the TARRI will be provided by seven science teams. The teams are formed around scientific disciplines and are titled: Geology/Geophysics, Hydrology/Rain, Oceanography, Ice/Snow, Geodesy/Orbit/Attitude, Cartography, and Surface Properties/Techniques.

Parsons, C. L.↗
NASA NTRS1992

The Earth Observing System (EOS) nickel-hydrogen battery

Information is given in viewgraph form on the Earth Observing System (EOS) nickel hydrogen battery. Information is given on the life evaluation test, cell characteristics, acceptance and characterization tests, and the battery system description.

Bennett, Charles W.↗
NASA NTRS1994

Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activiy

This paper describes the Earth Observing System (EOS) Communication (Ecom) Modeling, Analysis, and Testbed (EMAT) activity performed by Code 540 in support of the Ecom project. Ecom is the ground-to-ground data transport system for operational EOS traffic. The National Aeronautic and Space Administration (NASA) Communications (Nascom) Division, Code 540, is responsible for implementing Ecom. Ecom interfaces with various systems to transport EOS forward link commands, return link telemetry, and science payload data. To understand the complexities surrounding the design and implementation of Ecom, it is necessary that sufficient testbedding, modeling, and analysis be conducted prior to the design phase. These activities, when grouped, are referred to as the EMAT activity. This paper describes work accomplished to date in each of the three major EMAT activities: modeling, analysis, and testbedding.

Desai, Vishal↗
NASA NTRS2020

Amazonia Disasters: Assessing Methods for Gold Mining-related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Project Summary↗
NASA NTRS2020

Amazonia Disasters: Assessing Methods for Gold Mining-Related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Tech Paper↗
NASA NTRS2000

The Earth Observing System Terra Mission

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Kaufman, Yoram J.↗
NASA NTRS2000

The Earth Observing System Terra Mission

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Kaufman, Yoram J.↗
NASA NTRS2003

Scheduling Earth Observing Satellites with Evolutionary Algorithms

We hypothesize that evolutionary algorithms can effectively schedule coordinated fleets of Earth observing satellites. The constraints are complex and the bottlenecks are not well understood, a condition where evolutionary algorithms are often effective. This is, in part, because evolutionary algorithms require only that one can represent solutions, modify solutions, and evaluate solution fitness. To test the hypothesis we have developed a representative set of problems, produced optimization software (in Java) to solve them, and run experiments comparing techniques. This paper presents initial results of a comparison of several evolutionary and other optimization techniques; namely the genetic algorithm, simulated annealing, squeaky wheel optimization, and stochastic hill climbing. We also compare separate satellite vs. integrated scheduling of a two satellite constellation. While the results are not definitive, tests to date suggest that simulated annealing is the best search technique and integrated scheduling is superior.

Globus, Al↗
NASA NTRS2018

Preliminary Evaluation of the Simplified Higher Order Closure (SHOC) in the NASA Goddard Earth Observing System (GEOS)

Here we evaluate alternative planetary boundary layer (PBL) schemes in the NASA Goddard Earth Observing System (GEOS) model. The model currently calculates turbulent diffusivities with a local Richardson number-based scheme for stable layers, and a K-profile scheme with surface- and cloud-driven plumes based on Lock et al. (2000) for unstable layers. In this study, these are replaced with the TKE-based Simplified Higher Order Closure (SHOC). SHOC combines a 1.5-order turbulence closure with a double-Gaussian PDF serving as a subgrid condensation scheme. The new diffusivity calculations are paired with two new shallow mass flux schemes. First, the University of Washington shallow cumulus scheme of Park and Bretherton (2009), a buoyancy-sorting entraining-detraining bulk plume with overshooting entrainment and a TKE/CIN-based closure. Second, an Eddy Diffusivity Mass Flux (EDMF) scheme based on the multiple plume model of Suselj et al. (2013) with stochastic lateral entrainment. Global climatologies of low level temperature, humidity, and wind are evaluated against MERRA-2 and ERA-Interim reanalyses, and significant reductions in bias are seen with both mass flux schemes. The diurnal cycle over the continental United States is evaluated using MERRA-2 and an in situ network of surface Lidar profilers.

Arnold, Nathan↗
NASA NTRSDate not supplied

Quantum Leap: Evaluating the Feasibility of Quantum Machine Learning Using NASA Earth Observational Data

This study explores the feasibility of leveraging quantum machine learning (QML) to analyze NASA Earth Observational (EO) data for climate change research, with a particular focus on the phenomenon of ”crop frosting” which has become more prevalent due to climate change. We implemented and evaluated two QML models, the Variational Quantum Classifier (VQC) and Quantum Support Vector Classifier (QSVC), in both simulated and real quantum computing environments using a 127 qubit IBM quantum processor. Our study emphasizes the scientific rigor in comparing these quantum models with a classical Support Vector Machine (SVM) classifier, highlighting their performance in processing climate data. The results offer valuable insights into the potential scientific advantages, limitations, and scalability of QML for analyzing EO datasets, thus paving the way for more advanced climate modeling and predictive analytics using quantum computing. We showcased how Environmental Interaction Knowledge Graphs (EIKGs) and Digital Twins (DTs) can be integrated into this study. This research underscores the transformative potential of Classical and QML leveraging KGs and DT to address the multifaceted challenges posed by climate change.

Quantum Computing↗
NASA NTRS2006

Coordinating an Autonomous Earth-Observing Sensorweb

A system of software has been developed to coordinate the operation of an autonomous Earth-observing sensorweb. Sensorwebs are collections of sensor units scattered over large regions to gather data on spatial and temporal patterns of physical, chemical, or biological phenomena in those regions. Each sensor unit is a node in a data-gathering/ data-communication network that spans a region of interest. In this case, the region is the entire Earth, and the sensorweb includes multiple terrestrial and spaceborne sensor units. In addition to acquiring data for scientific study, the sensorweb is required to give timely notice of volcanic eruptions, floods, and other hazardous natural events. In keeping with the inherently modular nature of the sensory, communication, and data-processing hardware, the software features a flexible, modular architecture that facilitates expansion of the network, customization of conditions that trigger alarms of hazardous natural events, and customization of responses to alarms. The soft8 NASA Tech Briefs, July 2006 ware facilitates access to multiple sources of data on an event of scientific interest, enables coordinated use of multiple sensors in rapid reaction to detection of an event, and facilitates the tracking of spacecraft operations, including tracking of the acquisition, processing, and downlinking of requested data.

Sherwood, Robert↗