John E. Bailey 1,2 , Jonathan Dehn 2 Arctic Region Supercomputing Center, 909 Koyukuk Drive, University of Alaska, Fair

1. Volcano Monitoring Using Google Earth • John E. Bailey1,2, Jonathan Dehn2 • Arctic Region Supercomputing Center, 909 Koyukuk Drive, University of Alaska, Fairbanks, AK 99775, USA • (2) Alaska Volcano Observatory, 903 Koyukuk Drive, University of Alaska, Fairbanks, AK 99775, USA

2. North Pacific Volcanic Threat Alaska Volcano Observatory monitors 72 historically or potentially active volcanoes across the Alaskan Interior, Peninsular and the Aleutian chain. Only 28 are currently by monitored seismic and other instruments. Although many of these volcanoes are located on remote and unpopulated islands, they also lie directly along the path of several major air traffic corridors that daily carry over 20,000 passengers and millions of dollars of freight (Miller and Casadevall, 2000). This high density of air traffic, along with several past instances of aircraft experiencing mechanical problems after encountering volcanic clouds (Casadevall, 1994), make real-time satellite monitoring of the North Pacific volcanoes a necessity. Indeed, eruptions can only be tracked through remote sensing, as occurred at Mt Cleveland in 2001 (Dean et al., 2004). Major air traffic corridors relative to eruptions of North Pacific volcanoes 1989-1996

3. Satellite Monitoring System The AVO remote sensing group at the University of Alaska Fairbanks has been acquiring AVHRR and GOES data since 1999, and MODIS since 2001. Located at the Geophysical Institute UAF operates its own AVHRR and MODIS receiving stations, and receives a GOES data feed from the Navy Research Labs, Monterey Bay. Redundancy is provided by an additional AVHRR feed from NOAA's Gilmore Creek Station. Approximately 70 GB of data is archived per day. Coverage and analyses Includes data for all the Alaskan volcanoes, as well as over 50 other volcanoes across Kamchatka, the Kurile Islands and the US mainland. Monitored regions are divided into Sectors

4. Satellite Monitoring Tools Analysis is performed by a combination of automated and manual methods. Ultimately all images are examined by an observer a minimum of twice daily. More frequent checks are made with elevated levels of activity, with 24h operations during times of eruption. Volcanoes are grouped by sectors and standardized procedures are used to check all these regions for thermal anomalies and plumes. The observations made from the satellite images and volcano webcams are entered into a database. This database generates reports that are emailed to AVO personnel and collaborating groups. Reports are also automatically posted on an internal operations webpage. Web-based tools that search the database can generate graphs/files that show information such as the frequency of thermal anomalies/plumes; acquisition time and coverage of recorded swaths; and the delay in processing time relative to acquisition. Aside from the manual checks, constant analysis of images is made 24 h/day through the use of automated algorithms.

5. Volcanoes in Google Earth A new KMZ file produced by the Smithsonian’s Global Volcanism Program demonstrates the possibilities of using Google Earth as a medium for volcano information

6. Google Earth and Augustine Volcano Google Earth’s 3D geobrowser allows integration of both images (ASTER infrared combination) and tabular data (instrument location, details and status)

7. Geologic Mapping GIS data-derived products can be imported or re-created within the Google Earth Browser

8. Geologic Mapping Google Earth can also be used as a visual link to further information on a volcano

9. Augustine Webcams “Live” data feeds are possible through the use of refreshing network links, e.g., on-island (Mound) webcam; Homer webcam and a low-light “night-cam”

10. Thermal Anomaly Detection A thermal anomaly, or "hotspot", is an area of an image coincident with a volcano where one or more pixels report elevated temperatures relative to the surrounding ground. During the 1996 Pavlof eruption an automated algorithm to detect thermal anomalies was created. This was later generalized for use on all Alaskan volcanoes and detected the start of the 1997 Okmok algorithm. Further refinements produced an automated alarm system. All anomalies that are assessed by the algorithm to be genuine hotspots generate email reports. If no hotspot has been seen at a given volcano in the last 5 days, a SMS message is also generated and sent to cell phones. The creation of an interactive GUI has allowed the Okmok algorithm to be used as an observational tool to view hotspots.

11. Thermal Anomaly Detection Other web-tools are used to generate graphical illustrations of thermal change, to look for patterns of change that help define the type of activity. A hotspot may indicate that a volcano is actively exploding or producing pyroclastic flows, erupting lava flows or a lava dome, or even generating hot lahars (Dehn et al., 2000; Dean et al., 2002; Ramsey and Dehn, 2004). It may also be sensitive to increases in Strombolian activity and/or degassing (Harris and Stevenson, 1997). Hotspots also occur as precursors to eruptions. Between 1994 and 1999, thermal anomalies preceded in six of seven major explosive eruptions in the North Pacific (Dehn et al. 2000). The ability to connect to externally located KML files and refresh the locally generated content creates opportunity for Google Earth to be used an interface for eruption detection and analysis tools, e.g. hotspot alarms generated by the Okmok algorithm.

12. Ash Plume Detection and Tracking Ash detection primarily uses the "split window" technique (Prata, 1989), which finds the brightness temperature difference (BTD) between 2 satellite channels centered at 11 and 12 micron wavelength. Translucent volcanic clouds generally have negative BTDs while meteorological clouds generally have positive BTDs. Currently a beta-version automated ash detection algorithm is in operation over the Alaskan Peninsula and Aleutian island. The eruption of Augustine Volcano has added to momentum to development of this algorithm, along with an interface similar to that used for thermal anomalies.

13. Ash Plume Detection and Tracking Dynamic Overlay that allows different image bands/products to be viewed

15. Ash Dispersion Modeling Analysis of ash plumes is assisted by the use of an ash dispersal model: PUFF (Searcy et al., 1998). This model uses gridded wind fields that are updated daily, positions hypothetical particles above a volcano and releases the particles in the wind field. PUFF then tracks the movement of these particles. Predictions proved highly accurate during the ash-plume producing explosive events at Augustine (Webley et al., 2006). The example figure (left) shows dispersion modeling for 6 plumes that were simultaneously airborne on 14th Jan. This is a record for observations in Alaska.

16. Ash Dispersion Modeling 3D visualization of PUFF model for small ash plume over Cleveland Volcano. Multiple iterations of the isosurfaces at several time iterations are combined into one KML file. A combination of a network link refresh and running scripts produce a “moving” plume

17. References Casadevall TJ (1994), Volcanic ash and aviation safety: Proceedings of the First International Symposium on Volcanic Ash and Aviation Safety, U.S. Geol. Surv. Bull. 2047, 450 p. Dehn J, Dean KG, Engle K (2000) Thermal monitoring of North Pacific volcanoes from space, Geology, 28:755-758 Dehn J, Dean KG, Engle K, Izbekov P (2002), Thermal precursors in satellite images of the 1999 eruption of Shishaldin Volcano, Bull. Volcanol., 64:525-534 Dean KG, Dehn J, Engle K, Izbekov P., Papp K., Patrick M. (2002), Operational satellite monitoring of volcanoes at the Alaska Volcano Observatory, Adv. Environ. Monthly Mod., 1:70-97 Dean KG, Dehn J, Papp KR, Smith, Izbekov, P, Peterson R, Kearney C, Steffke A (2004), Integrated satellite observations of the 2001 eruption of Mt. Cleveland, Alaska, J. Volcanol. Geotherm. Res. 135:52-74. Harris AJL, Stevenson DS (1997), Thermal observations of degassing open conduits and fumaroles at Stromboli and Vulcano using remotely sensed data, J. Volcanol. Geotherm. Res., 76:175-198 Miller TP and Casadevall TJ (2000), Volcanic Ash Hazards to Aviation, Encyclopedia of Volcanoes, Academic Press, pp. 915-930. Prata AJ (1989), Observations of volcanic ash clouds in 10-12 µm window using AVHRR/2 data, Int. J. Rem. Sens., 10:751-761. Ramsey M., Dehn J. (2004), Spaceborne observations of the 2000 Bezymianny, Kamchatka eruption: the integration of high-resolution ASTER data into near real-time monitoring using AVHRR, J. Volcanol. Geotherm. Res., 135:127-146 Searcy C, Dean K, Stringer W. (1998), PUFF: A high-resolution volcanic ash tracking model, J. Volcanol. Geotherm. Res., 80:1-16 Webley P, Dean K, Dehn J, Bailey J, Schneider D, Wessels R, Lovick J, Rinkleff P, Izbekov P (2006), The Role of Remote Sensing in Monitoring of Augustine Volcano, GSA Cordilleran Section meeting - May 2006.