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

Pan, Xiong, Gu, Xinfa, Bi, Yaxin, Shen, Xuhui and Meng, Qingyan (2013) Detecting seismic IR anomalies in bi-angular Advanced Along-Track Scanning Radiometer data. Natural Hazards and Earth System Sciences, 13 (8). pp. 2065-2074. [Journal article]

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DOI: 10.5194/nhess-13-2065-2013, 2013

Abstract

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 Radiome- ter (AATSR) data based on spatial/temporal continuity anal- ysis. The distinguishing feature of our method is that we car- ried 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 grid- ded 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 val- idation purposes. Unperturbed periods (March–April 2008) have been considered for confutation analysis. Combining with the tectonic explanation of spatial and temporal continu- ity of the abnormal phenomena, along with the analysed re- sults, a number of anomalies could be associated with possi- ble 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.

Item Type:Journal article
Keywords:Seismic anomaly, satellite data analysis, bi-angular radiometer data
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:38949
Deposited By: Dr Yaxin Bi
Deposited On:01 Nov 2017 16:20
Last Modified:01 Nov 2017 16:20

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