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At least 721 records · Page 40

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

Self-Directed Cooperative Planetary Rovers

The project is concerned with the development of decision-theoretic techniques to optimize the scientific return of planetary rovers. Planetary rovers are small unmanned vehicles equipped with cameras and a variety of sensors used for scientific experiments. They must operate under tight constraints over such resources as operation time, power, storage capacity, and communication bandwidth. Moreover, the limited computational resources of the rover limit the complexity of on-line planning and scheduling. We have developed a comprehensive solution to this problem that involves high-level tools to describe a mission; a compiler that maps a mission description and additional probabilistic models of the components of the rover into a Markov decision problem; and algorithms for solving the rover control problem that are sensitive to the limited computational resources and high-level of uncertainty in this domain.

Zilberstein, Shlomo↗

Analysis of ERTS-1 imagery of Wyoming and its application to evaluation of Wyoming's natural resources

The author has identified the following significant results. The Wyoming investigation has progressed according to schedule during the Jan. - Feb., 1973 report period. A map of the maximum extent of Pleistocene glaciation was compiled for northwest Wyoming from interpretations of glacial features seen on ERTS-1 imagery. Using isodensitometry as a tool for image enhancement, techniques were developed which allowed accurate delineation of small urban areas and provided distinction of broad classifications within these small urban centers.

Marrs, R. W.↗

EOS mapping accuracy study

Studies were performed to evaluate various image positioning methods for possible use in the earth observatory satellite (EOS) program and other earth resource imaging satellite programs. The primary goal is the generation of geometrically corrected and registered images, positioned with respect to the earth's surface. The EOS sensors which were considered were the thematic mapper, the return beam vidicon camera, and the high resolution pointable imager. The image positioning methods evaluated consisted of various combinations of satellite data and ground control points. It was concluded that EOS attitude control system design must be considered as a part of the image positioning problem for EOS, along with image sensor design and ground image processing system design. Study results show that, with suitable efficiency for ground control point selection and matching activities during data processing, extensive reliance should be placed on use of ground control points for positioning the images obtained from EOS and similar programs.

Forrest, R. B.↗

Mapping the Moon in Soft x Rays: Promises and Challenges

Recent ROSAT images reported by Schmitt et el. show that the sunlit part of the Moon is a significant source of very soft x rays. Stimulated by these observations, Edwards et al. have made an analysis of the response of the Moon to the solar soft x ray and EUV spectrum. They argue that much of the observed emission is in the form of discrete fluorescence lines in the energy range 25 to 100 eV, and that these lines are generally much stronger than the adjacent directly scattered solar background. On this basis they suggest that soft x ray fluorescence can be used to remotely obtain high-precision elemental maps of the lunar surface. Edwards et al. have continued to develop this idea and have suggested a system using soft x ray telescopes in lunar orbit, which could also obtain very good spatial resolution. This combination could be extremely valuable in furthering our understanding of lunar chemistry and potential resource distributions. High spatial resolution combined with the thin surface layer from which these soft x rays arise suggests the exciting possibility that x ray telescopes could map lunar volcanic volatiles from orbit.

Housley, R. M.↗

Resource management implications of ERTS-1 data to Ohio

Initial experimental analysis of ERTS-1 imagery has demonstrated that remote sensing from space is a means of delineating and inventorying Ohio's strip-mined areas, detecting power plant smoke plumes, and proving the data necessary for periodically compiling land use maps for the entire state. The nature and extent of these problems throughout Ohio, how ERTS data can contribute to their solution, and estimates of the long term significance of these initial findings to overall resource management interests in Ohio are summarized.

Sweet, D. C.↗

Interdisciplinary research on the application of ERTS-1 data to the regional land use planning process

The author has identified the following significant results. Although the degree to which ERTS-1 imagery can satisfy regional land use planning data needs is not yet known, it appears to offer means by which the data acquisition process can be immeasurably improved. The initial experiences of an interdisciplinary group attempting to formulate ways of analyzing the effectiveness of ERTS-1 imagery as a base for environmental monitoring and the resolution of regional land allocation problems are documented. Application of imagery to the regional planning process consists of utilizing representative geographical regions within the state of Wisconsin. Because of the need to describe and depict regional resource complexity in an interrelatable state, certain resources within the geographical regions have been inventoried and stored in a two-dimensional computer-based map form. Computer oriented processes were developed to provide for the economical storage, analysis, and spatial display of natural and cultural data for regional land use planning purposes. The authors are optimistic that the imagery will provide revelant data for land use decision making at regional levels.

Clapp, J. L.↗

Interdisciplinary research on the application of ERTS-1 data to the regional land use planning process.

Although the degree to which ERTS-1 imagery can satisfy regional land use planning data needs is not yet known, it appears to offer means by which the data acquisition process can be immeasurably improved. This paper documents the initial experiences of an interdisciplinary group attempting to formulate ways of analyzing the effectiveness of ERTS-1 imagery as a base for environmental monitoring and the resolution of regional land allocation problems. Because of the need to describe and depict regional resource complexity in an interrelatable state, certain resources within the geographical regions have been inventoried and stored in a two-dimensional computer-based map form. Computer oriented processes were developed to provide for the economical storage, analysis and spatial display of natural and cultural data for regional land use planning purposes. Statistical programs have been developed that correlate interpreted data with stored data, both spatially and numerically.

Clapp, J. L.↗

Interfacing geographic information systems and remote sensing for rural land-use analysis

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

Nellis, M. Duane↗

Farmland Survey

A 1981 U.S. Department of Agriculture (USDA) study estimated that the nation is converting farmland to non-agricultural uses at the rate of 3 million acres a year. Seeking information on farmland loss in Florida, the state legislature, in 1984, directed establishment of a program for development of accurate data to enable intelligent legislation of state growth management. Thus was born Florida's massive Mapping and Monitoring of Agricultural Lands Project (MMALP). It employs data from the NASA-developed Landsat Earth resources survey satellite system as a quicker, less expensive alternative to ground surveying. The 3 year project involved inventory of Florida's 36 million acres classifying such as cropland, pastureland, citrus, woodlands, wetland, water and populated areas. Direction was assigned to Florida Department of Community Affairs (DCA) with assistance from the DOT. With the cooperation of the USDA, Soil Conservation Service, DCA decided that combining soil data with the Landsat land cover data would make available to land use planners a more comprehensive view of a county's land potential.

Source record↗

Global Infrared Observations of Roughness Induced Transition on the Space Shuttle Orbiter

High resolution infrared observations made from a mobile ground based optical system captured the laminar-to-turbulent boundary layer transition process as it occurred during Space Shuttle Endeavour's return to earth following its final mission in 2011. The STS-134 imagery was part of a larger effort to demonstrate an emerging and reliable non-intrusive global thermal measurement capability and to complement a series of boundary layer transition flight experiments that were flown on the Shuttle. The STS-134 observations are believed to be the first time that the development and movement of a hypersonic boundary layer transition front has been witnessed in flight over the entire vehicle surface and in particular, at unprecedented spatial resolution. Additionally, benchmark surface temperature maps of the Orbiter lower surface collected over multiple flights and spanning a Mach range of 18 to 6 are now available and represent an opportunity for collaborative comparison with computational techniques focused on hypersonic transition and turbulence modeling. The synergy of the global temperature maps with the companion in-situ thermocouple measurements serve as an example of the effective leveraging of resources to achieve a common goal of advancing our understanding of the complex nature of high Mach number transition. It is shown that quantitative imaging can open the door to a multitude of national and international opportunities for partnership associated with flight-testing and subsequent validation of numerical simulation techniques. The quantitative imaging applications highlighted in this paper offer unique and complementary flight measurement alternatives and suggest collaborative instrumentation opportunities to advance the state of the art in transition prediction and maximize the return on investment in terms of developmental flight tests for future vehicle designs.

Horvath, Thomas J.↗

Lunar Flashlight: Illuminating the Lunar South Pole

Lunar Flashlight is an innovative, small NASA mission to be launched as a secondary payload on the Space Launch System Exploration Mission 1 (EM-1). This highly mass- and volume-constrained satellite will demonstrate several technologies for NASA, including the use of "green" propellant, the ability for a CubeSat-sized satellite to perform science measurements beyond low Earth orbit, and the first planetary mission to use multi-band active reflectometry from orbit. Lunar Flashlight will detect and map water ice in permanently shadowed regions of the lunar south pole by measuring surface reflectance at multiple wavelengths. Mapping and quantifying lunar water ice addresses one of NASA's Strategic Knowledge Gaps to understand the lunar resource potential for future human exploration of the Moon.

Barbara Cohen↗

Eastern Washington Disasters: Integrating NASA Earth Observations to Analyze Spatiotemporal Distributions of Lightning-Caused Wildfires in Eastern Washington

According to the Washington Department of Natural Resources, roughly 36% of large fires in the state since 2010 were caused by lightning. General trends also show a greater increase in the number of lightning-ignited fires over the last three decades. The NASA DEVELOP Eastern Washington Disasters team partnered with The Nature Conservancy’s Washington Chapter to analyze the relationship between lightning strikes and wildfire events in Eastern Washington, with an emphasis on Kittitas and Yakima Counties. Using the International Space Station Lightning Imaging Sensor, the Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager vegetation moisture index, and Washington Department of Natural Resources historical fire data, the team generated a lightning-caused fire vulnerability index for 2001-2019. Climatology maps of lightning, wildfire, and vegetation moisture of the study area, along with an Esri ArcGIS StoryMap, further communicated project findings. The project results demonstrated that spatiotemporal patterns of lightning-ignited wildfires in Eastern Washington can be useful to inform land management practices and better predict areas that may be more vulnerable to these events.

Disasters↗

Eastern Washington Disasters: Integrating NASA Earth Observations to Analyze Spatiotemporal Distributions of Lightning-Caused Wildfires in Eastern Washington

According to the Washington Department of Natural Resources, roughly 36% of large fires in the statesince 2010 were caused by lightning. General trends also show a greater increase in the number of lightning-ignited fires over the last three decades. The NASA DEVELOP Eastern Washington Disasters team partnered with The Nature Conservancy’s Washington Chapter to analyze the relationship between lightning strikes and wildfire events in Eastern Washington, with an emphasis on Kittitas and Yakima Counties. Using the International Space Station Lightning Imaging Sensor, the Landsat 5 Thematic Mapper and Landsat 8 Operational Land Imager vegetation moisture index, and Washington Department of Natural Resources historical fire data, the team generated a lightning-caused fire vulnerability index for 2001-2019. Climatology maps of lightning, wildfire, and vegetation moisture of the study area, along with an Esri ArcGIS StoryMap, further communicated project findings. The project results demonstrated that spatiotemporal patterns of lightning-ignited wildfires in Eastern Washington can be useful to inform land management practices and better predict areas that may be more vulnerable to these events.

Disasters↗

The Kinematic Navigation and Cartography Knapsack (KNaCK): Demonstrating SlLAM (Simultaneous Localization and Mapping) LiDAR as a Tool for Exploration and Mapping of Lunar Pits and Caves

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile LiDAR (Light Detection and Ranging) system. It can map its surroundings in 3 dimensions and localize itself in space. The project is exploring how LiDAR can advance terrain mapping and navigation at the lunar south pole. KNaCK is lead by Dr. Michael Zanetti of NASA MSFC’s Heliophysics and Planetary Science Branch. - KNaCK serves as - A test article for GPS denied mapping and navigation. - A test bed for SLAM (Simultaneous Localization and Mapping) algorithms. - A test bed for commercial LiDAR units. - A tool for terrestrial science.

LiDAR↗

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

LiDAR↗

Caves as Planetary Analogs for GPS Denied, Low-Light Mapping and Navigation in Rugged Environments

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

Relevant environment testing↗

Mobile LiDAR as a Tool for Terrestrial and Planetary Cave Exploration and Mapping

KNaCK (Kinematic Navigation and Cartography Knapsack) is a backpack-mounted mobile mapping system. It can map its surroundings in 3 dimensions and localize itself in space using a LiDAR (Light Detection and Ranging) sensor and SLAM (Simultaneous Localization and Mapping) algorithm. The KNaCK team is leveraging caves as a proving ground to refine technology for mapping and navigation on other worlds while simultaneously advancing the State of the Art for terrestrial cave exploration and study.

LiDAR↗