Automatic Detection of Slow Slip Events Using the PICCA: Application to Chilean GNSS Data
نویسندگان
چکیده
The detection of transient events related to slow earthquakes in GNSS positional time series is key understanding seismogenic processes subduction zones. Here, we present a novel Principal and Independent Components Correlation Analysis (PICCA) method that allows for the temporal spatial signals. PICCA based on an optimal combination principal (PCA) independent component analysis (ICA) network. We assume signal mostly contained one or components. To detect transient, applied where correlations between sliding windows each PCA/ICA are calculated, obtaining stations affected by slip event onset from resulting correlation peaks. first tested calibrated using synthetic signals different magnitudes durations modelled their effect network Chile. Then, analyzed three recorded Chile, areas Iquique, Copiapó, Valparaíso. For data, 150 days was detected PCA-based method, while 3 ICA-based method. real long-term PCA, 16 ICA. It concluded simultaneous use both separation methods more effective when searching events. PCA useful events, ICA better suited recognize short duration. promising tool transients characteristics series, which will be used next stage generate catalog SSEs
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ژورنال
عنوان ژورنال: Frontiers in Earth Science
سال: 2021
ISSN: ['2296-6463']
DOI: https://doi.org/10.3389/feart.2021.788054