Analysis of streaming GPS measurements of surface displacement through a web services environment

We present a method for performing mode classification of real-time streams of GPS surface position data. Our approach has two parts: an algorithm for robust, unconstrained fitting of hidden Markov models (HMMs) to continuous-valued time series, and SensorGrid technology that manages data streams through a series of filters coupled with a publish/subscribe messaging system. The SensorGrid framework enables strong connections between data sources, the HMM time series analysis software, and users. We demonstrate our approach through a Web portal environment through which users can easily access data from the SCIGN and SOPAC GPS networks in Southern California, apply the analysis method, and view results. Ongoing real-time mode classifications of streaming GPS data are displayed in a map-based visualization interface