Volcano SRI: 4D Volcano Tomography in a Large-Scale Sensor Network

Funded by NSF CDI Program (NSF-1125165, $1,833,608, 9/2011-8/2016)


This project will create a new paradigm, VolcanoSRI (Volcano Seismic Realtime Imaging), for imaging 4D (four-dimensional) tomography of an active volcano in real-time. VolcanoSRI is a large-scale sensor network of low-cost geophysical stations that analyzes seismic signals and computes real-time, full-scale, three-dimensional fluid dynamics of the volcano conduit system within the active network. The computed 4D tomography model will illuminate complex, time-varying dynamics of an erupting volcano, providing a deeper scientific understanding of volcanic processes, as well as a basis for rapid detection of volcanic hazards. VolcanoSRI will potentially make the fictional holographic projector known as Virgil in the film “Supervolcano”  a reality.

Passive Subsurface Camera
Realizing the VolcanoSRI system requires a trans-formative study on the science of complex volcano systems and the design of large-scale sensor networks. Our approach integrates innovations on distributed tomographic algorithms, collaborative signal processing and situation-aware networking technology for large-scale real-time sensor systems. The distributed tomography algorithm disperses the computational burden to the sensor nodes and performs real-time tomographic inversion within the network. Such an approach has never been attempted before and represents a major achievement for both earth and computer science. The team is composed of computer and earth scientists including early pioneers of wireless sensor networks as applied to volcano monitoring.

The educational activities of this project include enhancing undergraduate and graduate curriculum and research program at the three collaborative universities. Through this project, we plan to broaden access to these course materials by providing the course lectures, all readings, and assignments online to the public. This project provides many opportunities for collaborations of students across earth and computer science, increasing involvement of women and minorities, at the three collaborative universities.

VolcanoSRI holds vast potential for real-time risk monitoring and development of early warning systems for volcanoes and other earth hazards. The new approach developed in this project is general, and can be implemented as a new field network paradigm for real-time imaging of highly dynamic and complex environments. We envision the system can be applied to a wide range of seismic exploration topics such as hydrothermal, oil exploration, mining safety, mining resource monitoring. The scientific and social impact is broad and significant.


Sensor Devices

Event Location


Volcano Tomography (MtStHelen)



  • Goutham Kamath
  • Liang Zhao
  • Lei Shi


[18] Liang Zhao, WenZhan Song, Descentralized Consensus in Distributed Networks, International Journal of Parallel, Emergent and Distributed Systems, 2016.

[17] Goutham Kamath, Lei Shi, Wen-Zhan Song, Jonathan M. Lees, Distributed Travel-time Seismic Tomography in Large-Scale Sensor Networks, Journal of Parallel and Distributed Computing, 89 , 2016.

[16] Goutham Kamath, Lei Shi, Edmond Chow, Wen-Zhan Song, Junjie Yang, Decentralized Multigrid for In-situ Big Data Computing, Tsinghua Science and Technology, SI Big Data Computing and Communications, 2015.

[15] Liang Zhao, Wen-Zhan Song, Lei Shi, Xiaojing Ye, Decentralized Seismic Tomography Computing In Cyber-Physical Sensor Systems, Cyber-Physical Systems, Taylor & Francis, 2015.

[14] Goutham Kamath, Lei Shi, Edmund Chow, WenZhan Song, Distributed Tomography with Adaptive Mesh Refinement in Sensor Networks, International Journal of Sensor Network, 2015.

[13] Paritosh Ramanan, Goutham Kamath, Wen-Zhan Song, INDIGO: An In-Situ Distributed Gossip Framework for Sensor NetworksInternational Journal of Distributed Sensor Network (IJDSN), 2015.

[12] Xuefeng Liu, Jiannong Cao, Wen-Zhan Song, Peng Guo, Zongjian He, Distributed Sensing for High-Quality Structural Health Monitoring using WSNs, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2014.

[11] Yujie Gu, Chengwei Zhou, Nathan Goodman, Wen-Zhan Song, Zhiguo Shi, Coprime Array Adaptive Beamforming Based On Compressive Sensing Virtual Array SignalThe 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016.

[10] Chengwei Zhou, Yujie Gu, Wen-Zhan Song, Yao Xie, Zhiguo Shi, Robust Adaptive Beamforming Based On DoA Support Using Decomposed Coprime Subarrays, The 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), 2016.

[9] Goutham Kamath, Wen-Zhan Song, Paritosh Ramanan, Lei Shi, Junjie Yang, DRISTI: Distributed Real-Time In-Situ Seismic Tomographic Imaging, 14th International Conference on Ubiquitous Computing and Communications (IUCC), Liverpool, UK, 2015.

[8] Goutham Kamath, Lei Shi, Edmund Chow, WenZhan Song, Distributed Multigrid Technique for Seismic Tomography in Sensor Networks, The 1st International Conference on Big Data Computing and Communication (BigCom), Shanxi, China., 2015.

[7] Goutham Kamath, Paritosh Ramanan, Wen-Zhan Song, Distributed Randomized Kaczmarz and Applications to Seismic Imaging in Sensor Network, The 11th International Conference on Distributed Computing in Sensor Systems (DCOSS), Fortaleza, Brazil, 2015.

[6] Liang Zhao, Wen-Zhan Song, Xiaojing Ye, Fast Decentralized Gradient Descent Method and Applications to In-situ Seismic Tomography, IEEE International Conference on Big Data (IEEE BigData 2015), 2015.

[5] Paritosh Ramanan, Goutham Kamath, Wen-Zhan Song NetTomo: A Tomographic approach towards Network Diagnosis, IEEE International Symposium on a World of Wireless Mobile and Multimedia Networks (WoWMoM), 2015.

[4] Jonathan Lees, Song, WenZhan, Xing, Guoliang, Steve Vick, Dennis Phillips Large-N in Volcano Settings: VolcanoSRI, AGU, San Francisco, Calif., 2014.

[3] Goutham Kamath, Shi, Lei, Wen-Zhan Song, Component-Average based Distributed Seismic Tomography in Sensor Networks, The 9th IEEE International Conference on Distributed Computing in Sensor Systems (IEEE DCOSS), 2013.

[2] Shi, Lei, Wen-Zhan Song, Mingsen Xu, Qingjun Xiao, Jonathan M. Lees, Xing, Guoliang Imaging, Volcano Seismic Tomography in Sensor Networks, The 10th Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (IEEE SECON), 2013.

[1] Xuefeng Liu, Jiannong Cao, Wen-Zhan Song, Tang, Shaojie, Distributed Sensing for High Quality Structural Health Monitoring using Wireless Sensor Networks, The 33rd IEEE Real-Time Systems Symposium, 2012.

Book Chapter

Goutham Kamath, Song, WenZhan Tomographic Imaging in Sensor Networks (Book Chapter) Industrial Tomography, Chapter 17, Woodhead Publication, 2014.