Automatic Anomaly Detection for Swarm Observations

The Swarm satellite mission was launched on 22 November 2013ꎬ it is the first European Space Agency’s constellation of three satellitesꎬ dedicated to monitoring geomagnetic field changes. The measurements delivered by the three satellites are very valuable for a range of applicationsꎬ including the earthquake prediction study. Howeverꎬ for more than 5 yearsꎬ relatively little advancement has been achieved in establishing a systematic approach for detecting anomalies from the satellite measurements for predicting earthquakes. This paper presents the challenges of developing a pragmatic framework for automatic anomaly detection and highlights innovative features of functional components developed. Through a case study we demonstrate a functionality pipeline of the system in detecting anomaliesꎬ and present our solutions to coping with data sparsity and parameter tuning as well as insights into the differences between discovering seismic anomalies from periodic and non¯periodic data observed by the Swarm satellites.