The RSNI-Picker2 (Regional Seismic network of Northwestern Italy, University of Genova) automatic phase detector, picker, and locator is presented, as well as the analysis of its performance in real-time monitoring of earthquakes and nontectonic events. The major improvements of this algorithm with respect to previous ones are the iterative coupling between picking and probabilistic nonlinear locations and a dynamic selection of time windows for close phase onsets or contemporary events. Calculation of strong-motion parameters and discrimination of outof- network events can also be achieved. Automatic results from RSNI-Picker2, its original version (RSNI-Picker), and other automatic picking codes are compared with a reference manual dataset of 1445 local earthquakes of northwestern Italy. RSNI-Picker2 shows significantly higher precision (91%) and accuracy (98.3% within 0:1 s) in P-phase picking, with a recall of 75% for the selected setup. A similar robust picking of S phases (94% precision, 71% recall), with 89.2% of residuals within 0:2 s, ensures accurate and reliable automatic earthquake locations, especially for local-suited setup with well-constrained crustal velocity models. We find RSNIPicker2 also applicable for real-time automatic environmental monitoring, as for quarry shots and large rockfalls.

Robust Picking and Accurate Location with RSNI‐Picker2: Real‐Time Automatic Monitoring of Earthquakes and Nontectonic Events

Scafidi, Davide;Ferretti, Gabriele;Spallarossa, Daniele
2018

Abstract

The RSNI-Picker2 (Regional Seismic network of Northwestern Italy, University of Genova) automatic phase detector, picker, and locator is presented, as well as the analysis of its performance in real-time monitoring of earthquakes and nontectonic events. The major improvements of this algorithm with respect to previous ones are the iterative coupling between picking and probabilistic nonlinear locations and a dynamic selection of time windows for close phase onsets or contemporary events. Calculation of strong-motion parameters and discrimination of outof- network events can also be achieved. Automatic results from RSNI-Picker2, its original version (RSNI-Picker), and other automatic picking codes are compared with a reference manual dataset of 1445 local earthquakes of northwestern Italy. RSNI-Picker2 shows significantly higher precision (91%) and accuracy (98.3% within 0:1 s) in P-phase picking, with a recall of 75% for the selected setup. A similar robust picking of S phases (94% precision, 71% recall), with 89.2% of residuals within 0:2 s, ensures accurate and reliable automatic earthquake locations, especially for local-suited setup with well-constrained crustal velocity models. We find RSNIPicker2 also applicable for real-time automatic environmental monitoring, as for quarry shots and large rockfalls.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/920990
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