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23 October 2014 Time series satellite and ground-based data for detecting earthquake anomalies
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Earthquake science has entered a new era with the development of space-based technologies to measure surface geophysical parameters and deformation at the boundaries of tectonic plates and large faults. Satellite time-series data, coupled with ground based observations where available, can enable scientists to survey pre-earthquake signals in the areas of strong tectonic activity. Cumulative stress energy in seismic active regions under operating tectonic force manifests various earthquakes’ precursors. Space-time anomalies of Earth’s emitted radiation (thermal infrared in spectral range measured from satellite months to weeks before the occurrence of earthquakes, radon in underground water and soil, etc.), and electromagnetic anomalies are considered as pre-seismic signals. Vrancea tectonic active zone in Romania is characterized by a high seismic hazard in European- Mediterranean region, being responsible of intermediate depth and normal earthquakes generation on a confined epicentral area.Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. This paper presents observations made using in-situ data and time series MODIS and NOAA-AVHRR satellite data for derived multi geophysical parameters (land surface temperature -LST, outgoing long-wave radiation- OLR, net surface latent heat flux (LHF) and mean air temperature- AT for some seismic events recorded in Vrancea region in Romania, which is one of the most active intracontinental seismic areas in Europe. Starting with almost one week prior to a moderate or strong earthquake a transient thermal infrared rise in LST of several Celsius degrees (°C) and the increased OLR values higher than the normal have been recorded around epicentral areas, function of the magnitude and focal depth, which disappeared after the main shock.
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M. A. Zoran, R. S. Savastru, and D. M. Savastru "Time series satellite and ground-based data for detecting earthquake anomalies", Proc. SPIE 9245, Earth Resources and Environmental Remote Sensing/GIS Applications V, 92450C (23 October 2014);

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