GNGTS 2013 - Atti del 32° Convegno Nazionale

(see for example Geller, 1997). The extension of our present observational capabilities and the refinement of data analysis methods could improve our present knowledge of preparatory phases of earthquakes and of their possible precursors. Under these consideration the project “S3 - Short term earthquake prediction and preparation”, the first supported Italian project on short term earthquake prediction, was developed in the frame of the agreement between the National Department of Civil Protection (DPC) and the National Institute for Geophysics and Volcanology (INGV) and aimed to identify and evaluate effective procedures for short term (from hours up to some months) forecasting of destructive earthquakes. In particular, the project aimed at overcoming the main limitation of researches so far carried on in the field of short term earthquake forecasting, that is the lack of observational data having sufficiently extended coverage both in time and space to allow a correct evaluation of the proposed precursory patterns. This goal has been considered as the basis of research project that focused on two Italian areas: the Po Plain and Southern Apennines. In this context the Research Unit coordinated by University of Basilicata, worked in order to make available to the project team a further contribution for a dynamic assessment of seismic risk. On this base a generation of thermal anomaly maps, based on historical TIR observations of MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager) from 2004 to 2012. Since the start of the project an automatic chain of satellite data acquisition and processing has been activated providing TIR anomaly maps (following the method described in Tramutoli et al. , 2005) for the whole Italian territory and made available every day using a suitable geographical projections in order to make them directly comparable with products coming from other research units. Moreover, the provided maps with RETIRA index values have been accompanied by information about the significance of the reported anomalies (if any) with regard to their space-time persistence and known spurious effects as the ones related to the presence and distribution of cloud coverage, navigation errors etc.. The rst methodology. The Earth’s thermally emitted radiation as measured from space is very high variable due to different natural/observational causes. By applying the Robust Satellite Technique (RST; Tramutoli, 1998, 2005, 2007) to multi-year satellite TIR records it is possible to identifies signal anomalies in the space-time domain as deviations from a normal state that has been preliminarily identified on the basis of satellite observations collected during several years, under similar observational conditions for each image pixel and period of the year. For earthquake (EQ) prone area monitoring, anomalous TIR patterns are identified by using a specific index, RETIRA (Robust Estimator of TIR Anomalies: Filizzola et al. , 2004) index ( r , t’ ), which is computed as follows: where: • ≡ (x,y) represents the ground geographic coordinates of the image pixel center; • t’ is the time of acquisition of the satellite image at hand with t ∊ τ, where τ defines the homogeneous domain of satellite images selected during the same time-slot (hour of the day) and period of the year (month) of the image at hand; these restrictions on the time series are useful in order to reduce the signal variability connected to both seasonal and daily cycle; • Δ T ( r , t ’) is the difference between the current ( t = t’ ) TIR signal value T ( r , t’ ) at location r and its spatial average T ( t’ ) at the moment of satellite acquisition, computed in place on the image at hand (within the RETIRA computation area ) considering only cloud-free pixels, and considering only sea pixels if r is located on the sea, only land pixels if r is located over the land; note that the choice of such a differential variable Δ T ( r , t ’), instead 147 GNGTS 2013 S essione 2.1