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111 results for “Satellite Observations”
Ground-Based Global Navigation Satellite System (GNSS) GLONASS (GLObal NAvigation Satellite System) Observation Data (30-second sampling, daily files) from NASA CDDIS
This dataset consists of ground-based Global Navigation Satellite System GLONASS Observation Data (30-second sampling, daily files) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. The GLONASS data sets from ground receivers at the CDDIS consist of observations from the Russian GLObal NAvigation Satellite System (GLONASS); Russia's GLONASS is similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The daily GLONASS GNSS observation files (un-compacted) contain one day of GLONASS observation (30-second sampling) data in RINEX format from a global permanent network of ground-based receivers, one file per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/daily_30second_data.html.
Ground-Based Satellite Laser Ranging (SLR) Observation Data (full-rate, daily, 24 hour files) from NASA CDDIS
This dataset consists of ground-based Satellite Laser Ranging observation data (full-rate, daily 24 hour files) from the NASA Crustal Dynamics Data Information System (CDDIS). SLR provides unambiguous range measurements to mm precision that can be aggregated over the global network to provide very accurate satellite orbits, time histories of station position and motion, and many other geophysical parameters. SLR operates in the optical region and is the only space geodetic technique that measures unambiguous range directly. Analysis of SLR data contributes to the terrestrial reference frame, modeling of the spatial and temporal variations of the Earth's gravitational field, and monitoring of millimeter-level variations in the location of the center of mass of the total Earth system (solid Earth-atmosphere-oceans). In addition, SLR provides precise orbit determination for spaceborne radar altimeter missions. It provides a means for sub-nanosecond global time transfer, and a basis for special tests of the Theory of General Relativity. Analysis Centers (ACs) of the International Laser Ranging Service (ILRS) retrieve SLR data on regular schedules to produce precise station positions and velocities for stations in the ILRS network. The daily SLR full-rate observation files contain data received in the previous 24-hour period from a global network of stations ranging to satellites equipped with retroreflectors. Data are available in ILRS data format (older data sets) and/or the Consolidated Ranging Data (CRD) format. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/SLR/Full-rate_data.html.
GEOSatDB: global civil earth observation satellite semantic database
<p>The new version at <a href="https://doi.org/10.57760/sciencedb.11805">https://doi.org/10.57760/sciencedb.11805</a></p> <p>GEOSatDB is a semantic representation of Earth observation satellites and sensors that can be used to easily discover available Earth observation resources for specific research objectives.</p> <p><strong>Relevant Papers</strong></p> <p>Ming Lin, Meng Jin, Juanzi Li & Yuqi Bai (2024) GEOSatDB: global civil earth observation satellite semantic database, Big Earth Data, DOI: <a href="https://doi.org/10.1080/20964471.2024.2331992">10.1080/20964471.2024.2331992</a></p> <p><strong>Background</strong></p> <p>The widespread availability of coordinated and publicly accessible Earth observation (EO) data empowers decision-makers worldwide to comprehend global challenges and develop more effective policies. Space-based satellite remote sensing, which serves as the primary tool for EO, provides essential information about the Earth and its environment by measuring various geophysical variables. This contributes significantly to our understanding of the fundamental Earth system and the impact of human activities.</p> <p>Over the past few decades, many countries and organizations have markedly improved their regional and global EO capabilities by deploying a variety of advanced remote sensing satellites. The rapid growth of EO satellites and advances in on-board sensors have significantly enhanced remote sensing data quality by expanding spectral bands and increasing spatio-temporal resolutions. However, users face challenges in accessing available EO resources, which are often maintained independently by various nations, organizations, or companies. As a result, a substantial portion of archived EO satellite resources remains underutilized. Enhancing the discoverability of EO satellites and sensors can effectively utilize the vast amount of EO resources that continue to accumulate at a rapid pace, thereby better supporting data for global change research.</p> <p><strong>Methodology</strong></p> <p>This study introduces GEOSatDB, a comprehensive semantic database specifically tailored for civil Earth observation satellites. The foundation of the database is an ontology model conforming to standards set by the International Organization for Standardization (ISO) and the World Wide Web Consortium (W3C). This conformity enables data integration and promotes the reuse of accumulated knowledge. Our approach advocates a novel method for integrating Earth observation satellite information from diverse sources. It notably incorporates a structured prompt strategy utilizing a large language model to derive detailed sensor information from vast volumes of unstructured text.</p> <p><strong>Dataset Information</strong></p> <p>The downloadable files in RDF Turtle format are located in the data directory and contain a total of 130,134 statements:</p> <p>- GEOSatDB_ontology.ttl: Ontology modeling of concepts, relations, and properties.</p> <p>- satellite.ttl: 2,365 Earth observation satellites and their associated entities.</p> <p>- sensor.ttl: 1,021 Earth observation sensors and their associated entities.</p> <p>- sensor2satellite.ttl: relations between Earth observation satellites and sensors.</p> <p>In addition, a user-friendly portal is under development to facilitate easy access to GEOSatDB. The portal currently offers preliminary SPARQL query functionality, enabling the execution of SPARQL query examples.</p> <p>GEOSatDB undergoes quarterly updates, involving the addition of new satellites and sensors, revisions based on expert feedback, and the implementation of additional enhancements.</p>
Ground-Based Global Navigation Satellite System (GNSS) Observation Data (1-second sampling, sub-hourly files) from NASA CDDIS
This dataset consists of ground-based Global Navigation Satellite System (GNSS) Observation Data (1-second sampling, sub-hourly files) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The sub-hourly GNSS observation files (un-compacted) contain 15 minutes of GPS or multi-GNSS observation (1-second sampling) data in RINEX format from a global permanent network of ground-based receivers, one file per 15 minutes per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/high-rate_data.html.
Ground-Based Global Navigation Satellite System Observation Summary Data (30-second sampling, daily files) from NASA CDDIS
This dataset consists of ground-based Global Navigation Satellite System (GNSS) Observation Summary Data (30-second sampling, daily files of all distinct navigation messages received in one day) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. The daily files contain summary information of one day of GPS or multi-GNSS observations (30-second sampling) data in RINEX format from a global permanent network of ground-based receivers, one file per site. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/GNSS/daily_30second_data.html.
Ground-Based Satellite Laser Ranging (SLR) Observation Data (full-rate, daily, 24 hour files) from NASA CDDIS
This dataset consists of ground-based Satellite Laser Ranging observation data (full-rate, daily 24 hour files) from the NASA Crustal Dynamics Data Information System (CDDIS). SLR provides unambiguous range measurements to mm precision that can be aggregated over the global network to provide very accurate satellite orbits, time histories of station position and motion, and many other geophysical parameters. SLR operates in the optical region and is the only space geodetic technique that measures unambiguous range directly. Analysis of SLR data contributes to the terrestrial reference frame, modeling of the spatial and temporal variations of the Earth's gravitational field, and monitoring of millimeter-level variations in the location of the center of mass of the total Earth system (solid Earth-atmosphere-oceans). In addition, SLR provides precise orbit determination for spaceborne radar altimeter missions. It provides a means for sub-nanosecond global time transfer, and a basis for special tests of the Theory of General Relativity. Analysis Centers (ACs) of the International Laser Ranging Service (ILRS) retrieve SLR data on regular schedules to produce precise station positions and velocities for stations in the ILRS network. The daily SLR full-rate observation files contain data received in the previous 24-hour period from a global network of stations ranging to satellites equipped with retroreflectors. Data are available in ILRS data format (older data sets) and/or the Consolidated Ranging Data (CRD) format. More information about these data is available on the CDDIS website at https://cddis.nasa.gov/Data_and_Derived_Products/SLR/Full-rate_data.html.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) was launched on April 28, 2006 to study the impact of clouds and aerosols on the Earth’s radiation budget and climate. It flies in formation with five other satellites in the international 'A-Train' (PDF) constellation for coincident Earth observations. The CALIPSO satellite comprises three instruments, the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP), the Imaging Infrared Radiometer (IIR), and the Wide Field Camera (WFC). CALIPSO is a joint satellite mission between NASA and the French Agency, CNES.
PDS Lunar Crater Observation and Sensing Satellite Data Release 1
Agile, CCD47, Clio, MIR, NIR, NSP, PHOTDOC, PHOTGJON, TLP, VIS, VSP
Satellite Observations of Arctic Change, Version 1
The purpose of this site is to expose NASA satellite data and research on Arctic change in the form of maps that illustrate the changes taking place in the Arctic over time. A high-speed internet connection is recommended for map viewing. This site is presented with support from NASA Earth Sciences.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.