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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

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗

NASA Earth Resources Survey Symposium. Volume 2-A: Special session presentations. Plenary summaries

Practical application of earth resources survey data is considered. The utilization and results of data from NASA programs involving LANDSAT, the Skylab Earth Resources Experiment Package, and aircraft, as well as other data acquisition programs are included. User services and requirements and applications in land use, agriculture, coastal zone management, and geology are among the topics covered. For Vol. 1A, see N76-17469.

Source record↗

Estimating Lunar Pyroclastic Deposit Depth from Imaging Radar Data: Applications to Lunar Resource Assessment

Lunar pyroclastic deposits represent one of the primary anticipated sources of raw materials for future human settlements. These deposits are fine-grained volcanic debris layers produced by explosive volcanism contemporaneous with the early stage of mare infilling. There are several large regional pyroclastic units on the Moon (for example, the Aristarchus Plateau, Rima Bode, and Sulpicius Gallus formations), and numerous localized examples, which often occur as dark-halo deposits around endogenic craters (such as in the floor of Alphonsus Crater). Several regional pyroclastic deposits were studied with spectral reflectance techniques: the Aristarchus Plateau materials were found to be a relatively homogeneous blanket of iron-rich glasses. One such deposit was sampled at the Apollo 17 landing site, and was found to have ferrous oxide and titanium dioxide contents of 12 percent and 5 percent, respectively. While the areal extent of these deposits is relatively well defined from orbital photographs, their depths have been constrained only by a few studies of partially filled impact craters and by imaging radar data. A model for radar backscatter from mantled units applicable to both 70-cm and 12.6-cm wavelength radar data is presented. Depth estimates from such radar observations may be useful in planning future utilization of lunar pyroclastic deposits.

Campbell, B. A.↗

Use of MAGSAT anomaly data for crustal structure and mineral resources in the US midcontinent

Magnetic field data acquired by NASA's MAGSAT satellite is used to construct a long-wavelength magnetic anomaly map for the U.S. midcontinent. This aids in interpretation of gross crustal geology (structure, lithologic composition, resource potential) of the region. Magnetic properties of minerals and rocks are investigated and assessed, to help in evaluation and modelling of crustal magnetization sources and depth to the Curie-temperature isotherm.

Carmichael, R. S.↗

Generation of color imagery from earth resources technology satellite /ERTS/ data return

The ERTS-1 satellite returns to the NASA-Goddard Ground Data Handling System four bands of Multispectral Scanner (MSS) imagery and three bands of Return Beam Vidicon (RBV) imagery. The system by which this data is used to generate multispectral color composite prints is described. The discussion includes an explanation of the ERTS photography tone reproduction system.

Polger, J. E.↗

Lithium-Ion Verification Test Program

Need for technology verification for aerospace applications. Structure flexible program that will allow assessment of current technology capabilities. Provide information about various vendors. Provide for assessment of technology developments. Developed statistical DOE to interpret relationships in data and to address program test goals and resource limitations. Data will be used to develop a model to predict life of cells as a function of DOD, temperature, and EOCV.

McKissock, Barbara↗

Data processing requirements for the Earth Resources Technology Satellite (ERTS)

Some of the data handling considerations that led to the formulation of the data processing requirements for the ERTS system are discussed. The significant parameters that influence these requirements are: (1) payload characteristics, (2) spacecraft characteristics such as orbit, attitude and attitude rates, (3) payload coverage, and (4) product types and quantities. Items 3 and 4 have had the most significant influence on the generation of the requirements.

Sos, J. Y.↗

Geographic analysis of multiple sensor data from the NASA/USGS earth resources program

Qualitative and quantitative analyses were made of multi-sensor data acquired during aircraft missions. While the principal analysis effort was concentrated on imagery taken over test sites in Southern California, data were also studied from records acquired on missions over test sites at Phoenix, Chicago, Asheville, and New Orleans. The objectives of the analyses were: (1) to determine the capabilities of ten remote sensors in identifying the elements of information necessary in conducting geographic investigations in land use analysis, urban problems, surface energy budget, and soil moisture; (2) to determine the feasibility of using these sensors for these purposes at orbital altitudes; and (3) to collate and analyze ground and air data previously collected and assemble it in a format useful in the accomplishment of cost effectiveness studies.

Pascucci, R. F.↗

Low Latency DESDynI Data Products for Disaster Response, Resource Management and Other Applications

We are developing onboard processor technology targeted at the L-band SAR instrument onboard the planned DESDynI mission to enable formation of SAR images onboard opening possibilities for near-real-time data products to augment full data streams. Several image processing and/or interpretation techniques are being explored as possible direct-broadcast products for use by agencies in need of low-latency data, responsible for disaster mitigation and assessment, resource management, agricultural development, shipping, etc. Data collected through UAVSAR (L-band) serves as surrogate to the future DESDynI instrument. We have explored surface water extent as a tool for flooding response, and disturbance images on polarimetric backscatter of repeat pass imagery potentially useful for structural collapse (earthquake), mud/land/debris-slides etc. We have also explored building vegetation and snow/ice classifiers, via support vector machines utilizing quad-pol backscatter, cross-pol phase, and a number of derivatives (radar vegetation index, dielectric estimates, etc.). We share our qualitative and quantitative results thus far.

applications↗

ELAS - A geobased information system that is transferable to several computers

In the early years of remote sensing, emphasis was placed on the processing and analysis of data from a single multispectral sensor, such as the Landsat Multispectral Scanner System (MSS). However, in connection with attempts to use the data for resource management, it was realized that many deficiencies existed in single data sets. A need was established to geographically reference the MSS data and to register with it data from disparate sources. Technological transfer activities have required systems concepts that can be easily transferred to computers of different types in other organizations. ELAS (Earth Resources Laboratory Applications Software), a geographically based information system, was developed to meet the considered needs. ELAS accepts data from a variety of sources. It contains programs to geographically reference the data to the Universal Transverse Mercator grid. One of the primary functions of ELAS is to produce a surface cover map.

Whitley, S. L.↗

GPU Lossless Hyperspectral Data Compression System

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

Aranki, Nazeeh I.↗

Improved LANDSAT to give better view of earth resources

The launch data of LANDSAT 3 is announced. The improved capability of the spacecrafts' remote sensors (the return beam vidicon and the multispectral scanner) and application of LANDSAT data to the study of energy supplies, food production, and global large-scale environmental monitoring are discussed along with the piggyback amateur radio communication satellite-OSCAR-D, the plasma Interaction Experiment, and the data collection system onboard LANDSAT 3. An assessment of the utility of LANDSAT multispectral data is given based on the research results to data from studies of LANDSAT 1 and 2 data. Areas studied include agriculture, rangelands, forestry, water resources, environmental and marine resources, environmental and marine resources, cartography, land use, demography, and geological surveys and mineral/petroleum exploration.

Source record↗

Performability modeling based on real data: A casestudy

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

Hsueh, M. C.↗