A study of Minnesota forests and lakes using data from Earth Resources Technology Satellites
Utilization of ERTS data to study air pollution, insect infestation, and water transport in Minnesota
Source record↗
SEARCH · Search NASA
Results for “Earth Data”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Earth-Science Data Co-Locating Tool
This software is used to locate Earth-science satellite data and climate-model analysis outputs in space and time. This enables the direct comparison of any set of data with different spatial and temporal resolutions. It is written in three separate modules that are clearly separated for their functionality and interface with other modules. This enables a fast development of supporting any new data set. In this updated version of the tool, several new front ends are developed for new products. This software finds co-locatable data pairs for given sets of data products and creates new data products that share the same spatial and temporal coordinates. This facilitates the direct comparison between the two heterogeneous datasets and the comprehensive and synergistic use of the datasets.
Lee, Seungwon↗
Archive Management of NASA Earth Observation Data to Support Cloud Analysis
NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly.
Lynnes, Christopher↗
Archive Management of NASA Earth Observation Data to Support Cloud Analysis
NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly. Reviewed by Mark McInerney ESDIS Deputy Project Manager.
Lynnes, Christopher↗
LAADS DAAC Migrates to the Cloud: Lessons Learned from Communicating About Earth Science Data on the Cloud
The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) is migrating data to the cloud. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS is using moving away from on premise data storage facilities to migrating to Amazon Web Services, where the massive archive of data from the Moderate Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) will be available for download and post-processing transformations online. The migration is happening in three phases and LAADS is concluding its beta testing period. This poster shows the lessons learned from communicating with a select group of users about how to effectively educate data users on using data in the cloud.
Tassia Owen↗
Sleep and wake states in the Biosatellite III monkey - Visual and computer analysis of telemetered electroencephalographic data from earth orbital flight
Biosatellite 3 monkey sleep and wake states based on visual and computer analysis of telemetered EEG data from earth orbital flight
Adey, W. R.↗
Correction and Geological Analysis of Lunar 3.8 Cm Radar Data
Earth based radar observations of the Moon have been taken at many wavelengths during the last ten years -- at 3.8, 70 cm, and most recently, 7.5 cm. Radar returns have been collected in both polarized and depolarized form so that is possible to derive both topographic and local surface roughness from the data. Until recently, work with 3.8 cm radar data had consisted of qualitative correlation of photographic and thermal IR data with individual depolarized radar data frames (local surface roughness) at different wavelengths. These studies provided results which demonstrated that the relationships between surface roughness (measured by either thermal emission or radar reflectivity) at different wavelengths can be used as an index of a crater's state of degradation (age). However, systematic studies of craters, or other local terrain features, as well as regional or global studies of major terrains (involving a number of data frames), cannot be done until individual frames are calibrated, geometric distortion is removed, and corrected frames are mosaicked.
Clark, P. E.↗
An operational, multistate, earth observation data management system
The purpose of this paper is to investigate a group of potential users of satellite remotely sensed data - state, local, and regional agencies involved in natural resources management. We assess this group's needs in five states and outline alternative data management systems to serve some of those needs. We conclude that an operational Earth Observation Data Management System (EODMS) will be of most use to these user agencies if it provides a full range of information services - from raw data acquisition to interpretation and dissemination of final information products.
Eastwood, L. F., Jr.↗
The Earth Resources Data Project
The Council of State Planning Agencies, in consultation with the National Governor's Association and NASA, initiated the Earth Resources Data Project to encourage the appropriate application of cost-effective science and technology to state natural resources issues and problems. This project was established to provide a focal point for identifying those issues associated with state use of remote sensing and related technology. One project goal is to elevate to the consciousness of state policy and program officials new technologies, such as LANDSAT, by association with major issues to which policy officials are attuned. The project assists the coordination between the states and NASA and promotes communication on those issues. A related project objective is to encourage technical assistance opportunities for states that will promote better use of remote sensing and natural resources data in state programs.
Harwood, P.↗
Earth resources data systems design: S192 instrument measurements and characteristics
The design, development, and characteristics of the S192 instrument for use with the earth resources data systems are discussed. Subjects presented are: (1) multispectral scanner measurements, (2) measurement characteristics, (3) calibration and aligment, (4) operating modes, and (5) time tagging and references. The S192 will obtain high spatial resolution, quantitative line scan imagery data of the radiation reflected and emitted by selected test sites in up to 13 spectral bands of visible, near infrared, and thermal infrared regions of the electromagnetic spectrum.
Goldstein, A. S.↗
Study of on-board compression of earth resources data
The current literature on image bandwidth compression was surveyed and those methods relevant to compression of multispectral imagery were selected. Typical satellite multispectral data was then analyzed statistically and the results used to select a smaller set of candidate bandwidth compression techniques particularly relevant to earth resources data. These were compared using both theoretical analysis and simulation, under various criteria of optimality such as mean square error (MSE), signal-to-noise ratio, classification accuracy, and computational complexity. By concatenating some of the most promising techniques, three multispectral data compression systems were synthesized which appear well suited to current and future NASA earth resources applications. The performance of these three recommended systems was then examined in detail by all of the above criteria. Finally, merits and deficiencies were summarized and a number of recommendations for future NASA activities in data compression proposed.
Habibi, A.↗
GeoDash: Assisting Visual Image Interpretation in Collect Earth Online by Leveraging Big Data on Google Earth Engine
Collect Earth Online (CEO) is a free and open online implementation of the FAO Collect Earth system for collaboratively collecting environmental data through the visual interpretation of Earth observation imagery. The primary collection mechanism in CEO is human interpretation of land surface characteristics in imagery served via Web Map Services (WMS). However, interpreters may not have enough contextual information to classify samples by only viewing the imagery served via WMS, be they high resolution or otherwise. To assist in the interpretation and collection processes in CEO, SERVIR, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries, developed the GeoDash system, an embedded and critical component of CEO. GeoDash leverages Google Earth Engine (GEE) by allowing users to set up custom browser-based widgets that pull from GEE's massive public data catalog. These widgets can be quick looks of other satellite imagery, time series graphs of environmental variables, and statistics panels of the same. Users can customize widgets with any of GEE's image collections, such as the historical Landsat collection with data available since the 1970s, select date ranges, image stretch parameters, graph characteristics, and create custom layouts, all on-the-fly to support plot interpretation in CEO. This presentation focuses on the implementation and potential applications, including the back-end links to GEE and the user interface with custom widget building. GeoDash takes large data volumes and condenses them into meaningful, relevant information for interpreters. While designed initially with national and global forest resource assessments in mind, the system will complement disaster assessments, agriculture management, project monitoring and evaluation, and more.
SERVI↗
An operational, multistate, earth observation data management system
State, local, and regional agencies involved in natural resources management were investigated as potential users of satellite remotely sensed data. This group's needs are assessed and alternative data management systems serving some of those needs are outlined. It is concluded that an operational earth observation data management system will be of most use to these user agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.
Eastwood, L. F., Jr.↗
Public-Private Partnership: Joint Recommendations to Improve Downloads of Large Earth Observation Data
No abstract available
Data Systems↗
Animated computer graphics models of space and earth sciences data generated via the massively parallel processor
The capability was developed of rapidly producing visual representations of large, complex, multi-dimensional space and earth sciences data sets via the implementation of computer graphics modeling techniques on the Massively Parallel Processor (MPP) by employing techniques recently developed for typically non-scientific applications. Such capabilities can provide a new and valuable tool for the understanding of complex scientific data, and a new application of parallel computing via the MPP. A prototype system with such capabilities was developed and integrated into the National Space Science Data Center's (NSSDC) Pilot Climate Data System (PCDS) data-independent environment for computer graphics data display to provide easy access to users. While developing these capabilities, several problems had to be solved independently of the actual use of the MPP, all of which are outlined.
Treinish, Lloyd A.↗
A Contrast in Use of Metrics in Earth Science Data Systems
In recent years there has been a surge in the number of systems for processing, archiving and distributing remotely sensed data. Such systems, working independently as well as in collaboration, have been contributing greatly to the advances in the scientific understanding of the Earth system, as well as utilization of the data for nationally and internationally important applications. Among such systems, we consider those that are developed by or under the sponsorship of NASA to fulfill one of its strategic objectives: "Study Earth from space to advance scientific understanding and meet societal needs." NASA's Earth science data systems are of varying size and complexity depending on the requirements they are intended to meet. Some data systems are regarded as NASA's "Core Capabilities" that provide the basic infrastructure for processing, archiving and distributing a set of data products to a large and diverse user community in a robust and reliable manner. Other data systems constitute "Community Capabilities". These provide specialized and innovative services to data users and/or research products offering new scientific insight. Such data systems are generally supported by NASA through peer reviewed competition. Examples of Core Capabilities are 1. Earth Observing Data and Information System (EOSDIS) with its Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems (SIPSs), and the EOS Clearing House (ECHO); 2. Tropical Rainfall Measurement Mission (TRMM) Science Data and Information System (TSDIS); 3. Ocean Data Processing System (ODPS); and 4. CloudSat Data Processing Center. Examples of Community Capabilities are projects under the Research, Education and Applications Solutions Network (REASON), and Advancing Collaborative Connections for Earth System Science (ACCESS) Programs. In managing these data system capabilities, it is necessary to have well-established goals and to measure progress relative to them. Progress is measured through "metrics", which can be a combination of quantitative as well as qualitative assessments. The specific metrics of interest depend on the user of the metrics as well as the type of data system. The users of metrics can be data system managers, program managers, funding agency or the public. Data system managers need metrics for assessing and improving the performance of the system and for future planning. Program managers need metrics to assess progress and the value of the data systems sponsored by them. Also, there is a difference in the metrics needed for core capabilities that tend to be more complex, larger and longer-term compared to community capabilities and the community capabilities that tend to be simpler, smaller and shorter-term. Even among community capabilities there are differences; hence the same set of metrics does not apply to all. Some provide data products to users, some provide services that enable better utilization of data or interoperability among other systems, and some are a part of a larger project where provision of data or services is only a minor activity. There is also a contrast between metrics used for internal and external purposes. Examples of internal purposes are: ensuring that the system meets its requirements, and planning for evolution and growth. Examples of external purposes are: providing to sponsors indicators of success of the systems, demonstrating the contributions of the system to overall program success, etc. This paper will consider EOSDIS, REASON and ACCESS programs to show the various types of metrics needed and how they need to be tailored to the types of data systems while maintaining the overall management goals of measuring progress and contributions made by the data systems.
Ramapriyan, Hampapuram↗
JSC earth resources data analysis capabilities available to EOD revision B
A list and summary description of all Johnson Space Center electronic laboratory and photographic laboratory capabilities available to earth resources division personnel for processing earth resources data are provided. The electronic capabilities pertain to those facilities and systems that use electronic and/or photographic products as output. The photographic capabilities pertain to equipment that uses photographic images as input and electronic and/or table summarizes processing steps. A general hardware description is presented for each of the data processing systems, and the titles of computer programs are used to identify the capabilities and data flow.
Source record↗
Study of cosmic ray motion in cosmic space near the earth
Data are presented on experimental installations developed in the cosmic ray variations laboratory in Kazgu (Alma-Ata). Various experiments on modelling the interaction of plasma with the geomagnetic field as well as the plasma distribution in quiet and disturbed fields are described. The characteristics of the meson supertelescope using scintillators (effective area, 10 sq m) for vertical alignments designed to study microvariations of the cosmic rays and their interrelation with magnetospheric fluctuations and the study of solar wind parameters are given.
Budilov, V. K.↗