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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Multitemporal dimensionality of images of normalized difference vegetation index at continental scales

Two sets of multitemporal data derived from NOAA world data product are analyzed by means of principal components analysis in order to examine their underlying multitemporal dimensionality. Specifically, images of the normalized difference vegetation index (NDVI) were analyzed for eight 3-week periods for Africa and ten 3-week periods for North America sampled from throughout the year extending from April 1982 to March 1983. The two multitemporal sets of images displayed remarkable similarities in terms of their first two components, the first corresponding very closely to the annualized integrated NDVI and the second to the seasonality of the NDVI. In particular, for the African data set the feature space defined by the first two components allows separation of the main cover types.

Townshend, J. R. G.↗
NASA NTRS2000

Validation of CERES/TERRA Data

There are 2 CERES scanning radiometer instruments aboard the TERRA spacecraft, one for mapping the solar radiation reflected from the Earth and the outgoing longwave radiation and the other for measuring the anisotropy of the radiation. Each CERES instrument has on-board calibration devices, which have demonstrated that from ground to orbit the broadband total and shortwave sensor responses maintained their ties to the International Temperature Scale of 1990 at precisions approaching radiances have been validated in orbit to +/- 0.3 % (0.3 W/sq m sr). Top of atmosphere fluxes are produced by use of the CERES data alone. By including data from other instruments, surface radiation fluxes and radiant fluxes within the atmosphere and at its top, shortwave and longwave, for both up and down components, are derived. Validation of these data products requires ground and aircraft measurements of fluxes and of cloud properties.

Barkstrom, Bruce R.↗
NASA NTRS2003

Intelligent Systems Technologies to Assist in Utilization of Earth Observation Data

With the launch of several Earth observing satellites over the last decade, we are now in a data rich environment. From NASA's Earth Observing System (EOS) satellites alone, we are accumulating more than 3 TB per day of raw data and derived geophysical parameters. The data products are being distributed to a large user community comprising scientific researchers, educators and operational government agencies. Notable progress has been made in the last decade in facilitating access to data. However, to realize the full potential of the growing archives of valuable scientific data, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system. Potential Intelligent Archive concepts include: 1) Mining archived data holdings using Intelligent Data Understanding algorithms to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services involved in a scientific enterprise; 3) Recognizing the value of results, indexing and formatting them for easy access, and delivering them to concerned individuals; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building (i.e., the transformations from data to information to knowledge) instead of just data pipelining; and 5) Being aware of other nodes in the knowledge building system, participating in open systems interfaces and protocols for virtualization, and collaborative interoperability. This paper presents some of these concepts and identifies issues to be addressed by research in future intelligent systems technology.

Ramapriyan, Hampapuram K.↗
NASA NTRS1990

A comparison of ISCCP and FIRE satellite cloud parameters

One of the goals of the First ISCCP Regional Experiment (FIRE) is the quantification of the uncertainties in the cloud parameter products derived by the International Satellite Cloud Climatology Project (ISCCP). This validation effort has many facets including sensitivity analyses and comparisons to similar data or theoretical results with known accuracies. The FIRE provides cloud-truth data at particular points or along particular lines from surface and aircraft measurement systems. Relating these data to the larger, area-averaged ISCCP results requires intermediate steps using higher resolution satellite data analyses. Errors in the cloud products derived with a particular method can be determined by performing analyses of high resolution satellite data over the area surrounding the point or line measurement. This same analysis technique may then be used to derive cloud parameters over a larger area containing similar cloud fields. It is assumed that the uncertainties found for the small scale analyses are the same for the large scale so that the method has been calibrated for the particular cloud type; i.e., its accuracy is known. Differences between the large scale results using the ISCCP technique and the calibrated method can be computed and used to determine if any significant biases or rms errors occur in the ISCCP results. Selected ISCCP results are compared to cloud parameters derived using the hybrid bispectral threshold method over the FIRE IFO and extended observation areas.

Gibson, Gary G.↗
NASA NTRSDate not supplied

UASs in the VOG/Edge/FOG Sensor Web Environment

This paper will describe the evolution of information collection, derivation and delivery mechanisms in sensor webs utilizing Uninhabited Aerial Systems (UAS).We will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, UASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary UASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. The Author will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing UASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to other UAS development This paper will focus on applications, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

UAS↗
NASA NTRS1992

TOVS Pathfinder product validation and intercomparison

Validation and intercomparison is an essential part of the Pathfinder program. Since its organization within the International TOVS Working Group, the TOVS community has continuously emphasized this aspect of the product retrieval problem. In the previous sections of this report, the TOVS Pathfinder SWG has recommended a careful and coherent reorganization and archiving of TOVS radiance data, and three distinct pathways for deriving product variables from this TOVS radiance archive. The importance in taking this multiple path approach to creating climate datasets rests in our firm belief that there is now global 'absolute truth' data for any of the derived physical parameters. Each of the selected methods is based upon a different set of assumptions. The challenge in interpreting Pathfinder data is to determine what alterations in the physical attributes of the environment contribute to evidence of global change extracted from observed or derived Pathfinder datasets. The Pathfinder validation and intercomparison activity must include validation of the forward problem, by which one calculates an estimate of upwelling radiance information from given earth and atmospheric data, and validation of the inverse problem, by which one calculates estimates of earth and atmospheric information from given upwelling satellite spectral radiance data.

Source record↗
NASA NTRS2019

"Sensor Web Evolution - Webs of Webs for NASA Science - Focus on small Uninhabited Aerial Systems (sUAS)"

This paper will describe the evolution of information collection, derivation and delivery mechanisms in webs of NASA sensor webs, with a focus on recent advancements in small Uninhabited Aerial Systems (sUAS). I will discuss the movement to "Fog Computing", also known as Edge Computing. Fog Computing facilitates the distribution of common operations and networking between edge devices and cloud computing facilities, optimizing the production of actionable intelligence. Initially, sUASs utilized onboard data collection as standard, with minimal data downloaded directly. Information products were derived in conventional computational environments, generally desk top computers, and information products made available to the Science Community in weeks or months. With the increased availability, and increasingly lower costs, of beyond line of sight (BLOS) satellite based communication, transmission rates and data volumes increased, and processing migrated to Cloud based services. Contemporary sUASs are moving some of that information product derivation to on vehicle services, and are creating a distributed Cloud/Fog environment. I will describe the technological advances that have made this possible, including low power multi-core Central Processing Units (CPU), and, more recently, the availability of high end Graphical Processing Units (GPU) that consume only a few watts. Intelligent system software, leveraging these hardware advances, finally allows for information product generation on-board, rather than simple data collection. Additionally, intelligent flight control systems now support mutual vehicle to vehicle collaboration, allowing sUASs to create ad-hoc sensor webs on demand, as required. Also discussed will be the lessons learned by the Authors' development of data systems for NASA's large High Altitude Long Endurance (HALE) UASs like Predator and Global Hawk, and how those lessons are being applied to sUAS development. This paper will focus on application, rather a deep dive into the technology, and will highlight improving data management through these new technologies.

Sensor Web↗
NASA NTRS2015

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Stackhouse, Paul W., Jr.↗
NASA NTRS2011

CEOS WGCV Land Product Validation (LPV) Sub-Group: Current and Potential Roles in Future Decadal Survey Missions

The goals and objectives of the sub group are: To foster and coordinate quantitative validation of higher level global land products derive d from remotely sensed data, in a traceable way, and to relay results so they are relevant to users. and to increase the quality and effi ciency of global satellite product validation by developing and promo ting international standards and protocols for: (1) Field sampling (2) Scaling techniques (3) Accuracy reporting (4) Data / information exchange also to provide feedback to international structures (GEOSS ) for: (1) Requirements on product accuracy and quality assurance (QA 4EO) (2) Terrestrial ECV measurement standards (3) Definitions for f uture missions

Roman, Miguel O.↗
NASA NTRS1992

Ultraviolet and visible variability of the coma of Comet Levy (1990c)

A visible lightcurve of Comet Levy obtained with the IUE Fine Error Sensor has revealed short-term coma variability. A production-rate source function is derivable from these data which implies a nucleus exhibiting hemispherically asymmetric activity. The ratio of gas-to-dust-production rates is also noted to exhibit asymmetry. The low dust-outflow velocity derived from observations, at about 200 m/sec, indicates a distribution that is rich in large, 3-10 micron particles.

Feldman, P. D.↗
NASA NTRS2012

The NASA Soil Moisture Active Passive (SMAP) Mission - Science and Data Product Development Status

The Soil Moisture Active Passive (SMAP) mission, planned for launch in late 2014, has the objective of frequent, global mapping of near-surface soil moisture and its freeze-thaw state. The SMAP measurement system utilizes an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna. The instruments will operate on a spacecraft in a 685 km polar orbit with 6am/6pm nodal crossings, viewing the surface at a constant 40-degree incidence angle with a 1000-km swath width, providing 3-day global coverage. Data from the instruments will yield global maps of soil moisture and freeze/thaw state at 10 km and 3 km resolutions, respectively, every two to three days. The 10-km soil moisture product will be generated using a combined radar and radiometer retrieval algorithm. SMAP will also provide a radiometer-only soil moisture product at 40-km spatial resolution and a radar-only soil moisture product at 3-km resolution. The relative accuracies of these products will vary regionally and will depend on surface characteristics such as vegetation water content, vegetation type, surface roughness, and landscape heterogeneity. The SMAP soil moisture and freeze/thaw measurements will enable significantly improved estimates of the fluxes of water, energy and carbon between the land and atmosphere. Soil moisture and freeze/thaw controls of these fluxes are key factors in the performance of models used for weather and climate predictions and for quantifYing the global carbon balance. Soil moisture measurements are also of importance in modeling and predicting extreme events such as floods and droughts. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. In the Testbed algorithms are developed and evaluated using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including data from the SMOS and Aquarius missions. We report here on the development status of the SMAP data products. The Testbed simulations are designed to capture various sources of errors in the products including environment effects, instrument effects (nonideal aspects of the measurement system), and retrieval algorithm errors. The SMAP project has developed a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level l) and derived geophysical products (Level 2 and higher).

Nloku, E.↗
NASA NTRS2013

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗
NASA NTRS1979

Swath width study. A simulation assessment of costs and benefits of a sensor system for agricultural application

Satellites provide an excellent platform from which to observe crops on the scale and frequency required to provide accurate crop production estimates on a worldwide basis. Multispectral imaging sensors aboard these platforms are capable of providing data from which to derive acreage and production estimates. The issue of sensor swath width was examined. The quantitative trade trade necessary to resolve the combined issue of sensor swath width, number of platforms, and their orbits was generated and are included. Problems with different swath width sensors were analyzed and an assessment of system trade-offs of swath width versus number of satellites was made for achieving Global Crop Production Forecasting.

Source record↗
NASA NTRS1981

Computer-implemented remote sensing techniques for measuring coastal productivity and nutrient transport systems

An automatic technique has been developed to measure marsh plant production by inference from a species classification derived from Landsat MSS data. A separate computer technique has been developed to calculate the transport path length of detritus and nutrients from their point of origin in the marsh to the shoreline from Landsat data. A nutrient availability indicator, the ratio of production to transport path length, was derived for each marsh-identified Landsat cell. The use of a data base compatible with the Landsat format facilitated data handling and computations.

Butera, M. K.↗
NASA NTRS2021

Highland Lakes Water Resources: Using NASA Earth Observations to Improve Detection Systems for Harmful Algal Events in the Highland Lakes in Central Texas

Beginning in 2019, harmful algal events in Austin, Texas, caused canine deaths in the Lady Bird Lake and Lake Travis reservoirs. These reservoirs are part of the larger Highland Lakes chain, managed by the Lower Colorado River Authority (LCRA) and the City of Austin Department of Watershed Protection (CoA DWP), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable algal event conditions in central Texas, the LCRA and CoA DWP partnered with NASA DEVELOP to improve algal event early-warning systems through the application of remote sensing and machine learning. An Earth observation-based algal monitoring system will assist the responsible agencies in predicting algal conditions and communicating hazards to the public. The NASA DEVELOP team utilized Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data to produce products including chlorophyll-a concentrations, cyanobacteria detections, turbidity, and water surface temperature. Chlorophyll-a concentrations were retrieved with a pre-trained machine learning model (mixture density network) and spectral indices, while the other products were derived from spectral indices. In situ field data were used to validate and quantify uncertainties for each product. The validations show strong correlations for chlorophyll-a and water surface temperature. Time series analyses of chlorophyll-a concentrations show peaks in the severe drought years (2015 and 2016). This project's resulting products enable monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain and will ultimately support water management, decision making, and risk communication.

Kaitlynn Hietpas↗
NASA NTRSDate not supplied

Making Better Use of Satellite Data: The Satellite Needs Working Group

The U.S. Group on Earth Observations (USGEO) initiated in 2016 the Satellite Needs Working Group (SNWG) to identify and communicate the Earth observation needs of U.S. federal agencies. The SNWG identifies such needs through a biennial survey followed by interviews and follow-up discussions by the satellite Earth data providers of the U.S. Government: the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Geological Survey (USGS). Solutions and services are identified that leverage current or upcoming satellite missions to meet the identified needs; implementation of services that are estimated to significantly increase the level of satisfaction of multiple U.S. agencies are funded by NASA. The SNWG process has resulted in the implementation of numerous services that have impacted operations of not only U.S. agencies but of academic and international institutions as well. Notable examples include the Harmonized Landsat Sentinel-2 project that leverages European Space Agency (ESA) and NASA satellite assets to generate a global, analysis-ready, surface reflectance product with a temporal resolution of two days; the Airborne Data Management Group that curates and provides access to relevant resources, information and data from existing and past NASA field campaigns; and the Dynamic Surface Water Extent product which consists of harmonized but independent water extents derived from both from optical and radar data. These and other products are hosted at the NASA Distributed Active Archive Centers (DAACs) for free and open access. The SNWG Management Office at NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) manages the implementation of selected solutions and, importantly, NASA’s response to the needs of federal agencies through a Stakeholder Engagement Program. The impact of implemented services and solutions is hampered without efforts to build capacity around the use of the services. The Stakeholder Engagement Program ensures relevant training and outreach to SNWG agencies in collaboration with each solution implementation team.

remote sensing↗
NASA NTRS1979

Analysis of coastal upwelling and the production of a biomass

The coastal upwelling index derived from weather data is input to a set of coupled differential equations that describe the production of a biomass. The curl of the wind stress vector is discussed in the context of the physical extent of the upwelling structure. An analogy between temperature and biomass concentration in the upwelled coastal water is derived and the relationship is quantified. The use of remote satellite or airborne sensing to obtain biomass rate production coefficients is considered.

Howe, J. T.↗
NASA NTRS2011

Hurricane Data Analysis Tool

In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of interest and time, single imagery, overlay of two different products, animation,a time skip capability and different image size outputs. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. Since the tool can directly access the real data, more features and functionality can be added in the future.

Liu, Zhong↗