In this work we introduce a system pipeline for the analysis of earth’s electromagnetic field. Data gathered by the SWARM satellites are used to present the utility of our system. Our objective is to provide a streamlined method to analyze electromagnetic data over a region and investigate the relation of precursory signals caused by seismic events. The process follows three distinct stages: Data extraction, data pre-processing and anomaly detection. The first stage consists of the region selection and data extraction. The second stage consists of a number of different pre-processing methods that address the data sparsity problem and the cause of artificial anomalies. The end stage is the Anomaly Detection of the SWARM satellite data, over the investigated region. Four different methods are implemented that are known to perform well in the field of AD. Following the presentation of our system, a case study is shown. The seismic event under scrutiny is in China, Wenping that occurred on 03/08/2014 and is used to present the usefulness of our approach and pinpoint some critical problems regarding satellite data that were identified.
|Number of pages||17|
|Publication status||Accepted/In press - 25 Mar 2019|
- Anomaly Detection
- big data analytics
- Electromagnetic Data
- SWARM satellites
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Development and Application of Collective Anomaly Detection methods to Electromagnetic Satellite DataAuthor: Christodoulou, V., Sept 2020
Supervisor: Wilkie, G. (Supervisor) & Bi, Y. (Supervisor)
Student thesis: Doctoral ThesisFile