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Detecting seismic IR anomalies in bi-angular Advanced Along-Track Scanning Radiometer data

This paper presents a validation and confutation analysis using the methods of the robust satellite data analysis technique (RST) to detect seismic anomalies within the bi-angular Advanced Along-Track Scanning Radiometer (AATSR) data based on spatial/temporal continuity analysis. The distinguishing...

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Bibliographic Details
Published in:Natural hazards and earth system sciences 2013-08, Vol.13 (8), p.2065-2074
Main Authors: Xiong, P, Gu, X. F, Bi, Y. X, Shen, X. H, Meng, Q. Y, Zhao, L. M, Kang, C. L, Chen, L. Z, Jing, F, Yao, N, Zhao, Y. H, Li, X. M, Li, Y, Dong, J. T
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Language:English
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Summary:This paper presents a validation and confutation analysis using the methods of the robust satellite data analysis technique (RST) to detect seismic anomalies within the bi-angular Advanced Along-Track Scanning Radiometer (AATSR) data based on spatial/temporal continuity analysis. The distinguishing feature of our method is that we carried out a comparative analysis of seismic anomalies from bi-directional observation, which could help understanding seismic thermal infrared (TIR) anomalies. The proposed method has been applied to analyse bi-angular AATSR gridded brightness temperature data with longitude from 5 to 25° E and latitude from 35 to 50° N associated with the earthquake that occurred in Abruzzo, Italy, on 6 April 2009, and a full data set of 7 yr data from 2003 to 2009 during the months of March and April has been analysed for validation purposes. Unperturbed periods (March-April 2008) have been considered for confutation analysis. Combining with the tectonic explanation of spatial and temporal continuity of the abnormal phenomena, along with the analysed results, a number of anomalies could be associated with possible seismic activities, which follow the same time and space. Therefore, we conclude that the anomalies observed from 29 March 2009 to 5 April 2009, about eight days before the Abruzzo earthquake, could be earthquake anomalies.
ISSN:1684-9981
1561-8633
1684-9981
DOI:10.5194/nhess-13-2065-2013