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Time series analysis of remotely sensed TIR emissions: linking anomalies to physical processes
This thesis describes the application of time series analysis to satellite derived thermal infrared imagery, in order to determine if spatiotemporally limited anomalies can be linked to earthquake occurrence as has been suggested by literature. For this pupose, a methodology is applied that can sppress large scale patterns and highligt subbtle localized fluctuations in hypertemporal satellite data. The methodology is tested on at sensor longwave and midwave Thermal Infrared (TIR) Brightness Temperature daata on TIRderived land surface temperature ((LST) data. Experiments are fist carried out to retrieve synthetic anomalies which are imposed in reallife datasets. The methodology is found to facilitate utilization of longwave IR input for long term volcanic monitoring, to complement existing hotspot detection techniques and to aid monitoring of lower temperature targets even in areas of constant activy.Finally, the methodology is applied to examine the presence of detectable localized 9 spatial extent up to 18225 km2) increases in LST prior to twenty large, shallow, land based earquakes worldwide. The findings show that there is no statiscally significant difference between the anomaly density detected at different distance from the earhquake, at different periods 9before, during and after the earhquake), and in years with and without earthquake occurence. It is not clear if the earthquakes have no influence on the LST registered by the satellite if the influence or if influences are linked to stress accumulaion rather than stress release and therefore do not coincide with the earthquake. To clarify, more research is required on the physcal background behind the links between earthquakes and TIR anomalies wihch are suggested by literature.
B20190319290 | DS 621.3678 EFT t | Perpustakaan BIG (600) | Tersedia |
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