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CL 05-2182

Volcano Sensorweb

image of erupting volcano


Volcano Sensors

The Sensor Web Project uses a network of sensors linked by software and the internet to an autonomous satellite observation response capability. This system of systems is designed with a flexible, modular, architecture to facilitate expansion in sensors, customization of trigger conditions, and customization of responses.

This system has been used to implement a global surveillance program to study volcanos. We have also run sensorweb tests to study flooding, cryosphere events, and atmospheric phenomena.

AI Technology


Coordinating the activities of multiple sensors including space, terrestrial, and airborne to monitor science and hazard events.


Cinder Cone

In a remote area of the South Atlantic Ocean near Antarctica a volcano begins rumbling. It begins with a few minor tremors, and suddenly fresh lava breaks to the surface out of an existing vent. While there are no inhabitants of the South Sandwich Islands, four times per day the Terra & Aqua satellites fly overhead at 7.5 kilometers per second and an altitude of 705 kilometers. Each of these spacecraft carries a Moderate Resolution Imaging Spectrometer (MODIS) instrument, acquiring (250m-1000m/pixel) resolution data of the South Sandwich Islands as part of a 2700 kilometer wide swath of imagery.

These data are streamed to and processed at the Distributed Active Archive Center (DAAC) at the Goddard Space Flight Center where the University of Hawaii developed MODVOLC algorithms automatically detect the "hot spot" signature of the volcanic activity within hours of data acquisition. Software monitoring the MODVOLC web site matches this new alert with a previously specified science team interest in volcanoes in this region and generates an observation request to the Earth Observing One (EO-1) Ground System. Based on the priority of the request, the ground system uplinks the observation request to the EO-1 Spacecraft. Onboard Artificial Intelligence software evaluates the request, orients the spacecraft, and operates the science instruments to acquire high resolution (pan-band up to 10m/pixel) images with hyperspectral (220+ bands) data for science analysis. Onboard this data is processed to extract the signature of the volcanic eruption, downlinking this vital information within hours.


Project is currently running, with the goal of monitoring the Earth's 50 most active volcanos.

Mission Last Week Yesterday Upcoming
Images Taken By Sensorweb 5951 9 1 1


MODVOLC webpage
The MODVOLC webpage: realtime volcanism

A wide range of operational satellite/platforms make their data freely available (e.g. broadcast or internet) in a rapid fashion (tens of minutes to several hours from acquisition). For example, data from the Moderate Resolution Imaging Spectrometer (MODIS) flying on Terra and Aqua are available via Direct Broadcast in near real-time for regional coverage and 3-6 hours from acquisition from the GSFC Distributed Active Archive Center (DAAC) (for global coverage). These data provide regional or global coverage with a wide range of sensing capabilities. For example, MODIS covers the globe roughly 4 times daily (two day and two night overflights). QuickSCAT covers the majority of the globe daily.

Unfortunately, these global coverage instruments do not provide the high resolution data desirable for many science applications. The above instruments range in resolution from MODIS with 250m-1km resolution to 1km and above for the other instruments. While ideally, high resolution data would be available continuously with global coverage, typically high resolution assets can image only limited swathes of the Earth -- thus making them highly constrained and high-demand assets.

In our project, we have networked sensors and science event recognizers/trackers with an automated response system to form a sensorweb, defined as follows.

A networked set of instruments in which information from one or more sensors is automatically used to reconfigure the remainder of the sensors
Dust Storm in Persian Gulf
A dust storm over the persian gulf

Specifically, in our application, we use low resolution, high coverage sensors to trigger observations by high resolution instruments. Note that there are many other rationales to network sensors into a sensorweb. For example automated response might enable observation using complementary instruments such as imaging radar, infra-red, visible, etc. Or automated response might be used to apply more assets to increase the frequency of observation to improve the temporal resolution of available data.

Our sensorweb project is being used to monitor the Earth's 50 most active volcanos. We have also run sensorweb experiments to monitor flooding, wildfires, and cryospheric events (snowfall and melt, lake freezing and thawing, sea ice formation and breakup.)


Lights Out Autonomous Operation of an Earth Observing Sensorweb S. Chien, D. Tran, A. Davies, M. Johnston, J. Doubleday, R. Castano, L. Scharenbroich, G. Rabideau, B. Cichy, S. Kedar, D. Mandl, S. Frye, W. Song, P. Kyle, R. LaHusen, P. Cappaelare International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2007). Moscow, Russia. June 2007 + PDF CL#07-1702
Sensor Web Technologies: A New Paradigm for Operations R. Sherwood, S. Chien International Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO 2007). Moscow, Russia. June 2007 + PDF CL#07-1639
Sensor Webs for Science: New Directions for the Future R. Sherwood, S. Chien IEEE Infotech@Aerospace Conference. Rohnert Park, CA. May 2007 + PDF CL#07-1387
Sensor Web Enables Rapid Response to Volcanic Activity A. Davies, S. Chien, R. Wright, A. Miklius, P. Kyle, M. Welsh, J. Johnson, D. Tran, S. Schaffer, R. Sherwood EOS . v87 #1 January 2006 .
Autonomous Science Agents and Sensor Webs: EO-1 and Beyond R. Sherwood, S. Chien, D. Tran, B. Cichy, R. Castano, A. Davies, G. Rabideau IEEE Aerospace Conference (IAC 2006). Big Sky, MT. March 2006 + PDF CL#05-3565
Space-Based Measurement of River Runoff G. Brakenridge, S. Nghiem, E. Anderson, S. Chien EOS . v86 #19 May 2005 .
An Autonomous Earth-Observing Sensorweb S. Chien, B. Cichy, A. Davies, D. Tran, G. Rabideau, R. Castano, R. Sherwood, R. Greeley, T. Doggett, V. Baker, J. Dohm, F. Ip, D. Mandl, S. Frye, S. Shulman, S. Ungar, T. Brakke, J. Descloitres, J. Jones, S. Grosvenor, R. Wright, L. Flynn, A. Harris, R. Brakenridge, S. Cacquard, S. Nghiem IEEE Conference on Systems Man and Cybernetics (IEEE-CSMC 2005). Big Island, HI. October 2005
An Autonomous Earth-Observing Sensorweb S. Chien, B. Cichy, A. Davies, D. Tran, G. Rabideau, R. Castano, R. Sherwood, D. Mandl, S. Frye, S. Shulman, J. Jones, S. Grosvenor IEEE Intelligent Systems . May/June 2005 . + PDF CL#05-1291
Using Automated Planning for Sensorweb Response Steve Chien, Ashley Davies, Daniel Tran, Benjamin Cichy, Gregg Rabideau, Rebecca Castano, Rob Sherwood, Jeremy Jones, Sandy Grosvenor, Dan Mandl, Stuart Frye, Seth Shulman, Stephen Ungar, Thomas Brakke, Jacques Descloitres, Chris Justice, Rob Sohlberg, Rob Wright, Luke Flynn, Andy Harris, Robert Brakenridge, Sebastien Cacquard, Son Nghiem, Ronald Greeley, Thomas Doggett, Victor Baker, James Dohm, Felipe Ip International Workshop on Planning and Scheduling for Space (IWPSS 2004). Darmstadt, Germany. June 2004 CL#04-1535
Flood warnings, flood disaster assessments, and flood hazard reduction: the roles of orbital remote sensing G. Brakenridge, E. Anderson, S. Nghiem, S. Caquard, T. Shabaneh Symposium on Remote Sensing of the Environment. Honolulu, HI. November 2003
Using Timely Satellite Data to Autonomously Trigger Science Observations S. Chien , et. al Direct Broadcast Meeting. Kohala Coast, HI. November 2003


Technology Provider (PI): Dr. Steve Chien
Steve.Chien at

Project Team

JPL: Steve Chien
Rob Sherwood
Becky Castano
Ashley Davies
Gregg Rabideau
Daniel Tran
Ben Cichy
Steve Schaffer
Arizona State University: Thomas Doggett
University of Arizona: James Dohm
Felipe Ip


+ New Millennium Program


WSU Sensorweb Research Lab
[external + Link]