Publication | Closed Access
NOANET: A Continuously Operating GNSS Network for Solid-Earth Sciences in Greece
23
Citations
52
References
2021
Year
Observational NetworksNoanet ReceiversEngineeringGlobal Navigation Satellite SystemNetwork AnalysisEarth System ScienceEarth ScienceGeophysicsNoanet StationsSatellite MeasurementNoanet NetworkGeodesySatellite NetworkSatellite Signal ProcessingGeographyGeodetic NetworkSatellite Navigation SystemsNetwork ScienceSeismologyEarth SciencesGeoinformaticsNon-terrestrial NetworkSpace GeodesySolid-earth Sciences
Abstract The NOANET network is a continuously operating high-rate Global Navigation Satellite System (GNSS) network in Greece whose primary role is to enhance and support geophysical research employing GNSS data. This network is operated by the Institute of Geodynamics of the National Observatory of Athens and currently (September 2020) consists of 26 stations, most of which are located close to major seismogenic structures of Greece to optimally measure tectonic and seismically induced motions. All NOANET receivers are configured to record and collect data with a sampling rate of 1 Hz, although some of them also collect data every 5 Hz on their ring buffer. The network is committed to free and open data sharing within the scientific community, and the collected data are made available via the NOANET data repository and distribution point for all interested parties with no limitations. Integrity, validity, and quality checks of the acquired data are performed using a variety of software tools along with in-house developed programs to supervise the network performance and detect ill-formed data and/or awkward station behavior. In addition, the conventional low-rate GNSS observation data of all NOANET stations are routinely processed on a daily basis to supervise their performance through their position time series. Since the beginning of its establishment, the NOANET network has recorded a variety of deformation signals, and a large number of published papers have used GNSS data from stations that are part of NOANET to constrain, model, and interpret the nature of the associated geophysical phenomena.
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