Spatio-temporal changes in seismic velocity associated with the 2000 activity of Miyakejima volcano as inferred from cross-correlation analyses of ambient noise

2012 ◽  
Vol 247-248 ◽  
pp. 93-107 ◽  
Author(s):  
Titi Anggono ◽  
Takeshi Nishimura ◽  
Haruo Sato ◽  
Hideki Ueda ◽  
Motoo Ukawa
Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2427 ◽  
Author(s):  
Maria Valero ◽  
Fangyu Li ◽  
Jose Clemente ◽  
Wenzhan Song

A wireless seismic network can be effectively used as a tool for subsurface monitoring and imaging. By recording and analyzing ambient noise, a seismic network can image underground infrastructures and provide velocity variation information of the subsurface that can help to detect anomalies. By studying the variation in the noise cross-correlation function of the noise, it is possible to determine the subsurface seismic velocity and image underground infrastructures. Ambient noise imaging can be done in a decentralized fashion using Distributed Spatial Auto-Correlation (dSPAC). In dSPAC over sensor networks, the cross-correlation is the most intensive communication process since nodes need to communicate their data with neighbor nodes. In this paper, a new communication-reduced method for cross-correlation is presented to meet bandwidth and cost of communication constraints in networks while ambient noise imaging is performed using dSPAC method. By applying the proposed communication-reduced method, we show that energy and computational cost of the nodes is also preserved.


2014 ◽  
Vol 41 (17) ◽  
pp. 6131-6136 ◽  
Author(s):  
Tomoya Takano ◽  
Takeshi Nishimura ◽  
Hisashi Nakahara ◽  
Yusaku Ohta ◽  
Sachiko Tanaka

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