Continuous monitoring of Hawaiian volcanoes with thermal cameras
© Patrick et al.; licensee Springer. 2014
Received: 2 August 2013
Accepted: 20 December 2013
Published: 21 January 2014
Continuously operating thermal cameras are becoming more common around the world for volcano monitoring, and offer distinct advantages over conventional visual webcams for observing volcanic activity. Thermal cameras can sometimes “see” through volcanic fume that obscures views to visual webcams and the naked eye, and often provide a much clearer view of the extent of high temperature areas and activity levels. We describe a thermal camera network recently installed by the Hawaiian Volcano Observatory to monitor Kīlauea’s summit and east rift zone eruptions (at Halema‘uma‘u and Pu‘u ‘Ō‘ō craters, respectively) and to keep watch on Mauna Loa’s summit caldera. The cameras are long-wave, temperature-calibrated models protected in custom enclosures, and often positioned on crater rims close to active vents. Images are transmitted back to the observatory in real-time, and numerous Matlab scripts manage the data and provide automated analyses and alarms. The cameras have greatly improved HVO’s observations of surface eruptive activity, which includes highly dynamic lava lake activity at Halema‘uma‘u, major disruptions to Pu‘u ‘Ō‘ō crater and several fissure eruptions.
Webcams are now a standard and essential component of effective volcano monitoring (Kirianov et al. 2002; Poland et al. 2008a; Hoblitt et al. 2008; Moran et al. 2008; Behncke et al. 2009; Ripepe et al. 2009; Patrick et al. 2010; Arason et al. 2011; Schaefer 2012; Orr et al. 2013a). Visible-wavelength (0.4-0.7 μm) webcams, however, have numerous limitations. In many cases, volcanic vents are obscured by thick volcanic fume (a term we use to refer to volcanic gas and particles, such as aerosols), severely impairing or blocking observations of activity. In other cases, it is difficult to identify the extent of hot volcanic material (such as lava or fumarolic surfaces), because these surfaces may not always be incandescent, or their incandescence may not be strong enough to stand out from sunlit surfaces. Low-light, or near-infrared (~1 μm), cameras offer an improvement upon visible-wavelength cameras in these regards (Sentman et al. 2010), but still suffer from these limitations to a large degree.
Thermal (i.e. long-wave infrared, 7.5-13 μm) cameras provide a valuable complement to visual cameras by mitigating the aforementioned problems. Often (but not always), thermal cameras can “see” through thick volcanic fume, providing a view of active vents that would not otherwise be possible. Perhaps most importantly, they offer an unambiguous depiction of the extent of hot, warm and cool areas, making discrimination between active, recently active, and inactive surfaces very straightforward. Unlike visible or near-infrared cameras, their capacity for observation is not significantly affected by diurnal changes in sunlight, enhancing the clarity of long-term observation.
Beyond tracking ongoing eruptions, thermal cameras can also monitor changes that may presage eruptive activity. Patrick and Witzke (2011) describe selected examples of thermal precursors that were observed at volcanoes including Tokachi (Japan; Yokoyama 1964), Mt. St. Helens (USA; Kieffer et al. 1981), Stromboli (Italy; Bonaccorso et al. 2003) and Santa Ana (El Salvador; Hernández et al. 2007). In Hawai‘i, hikers observed red glow and anomalous steaming coming from cracks in the summit caldera of Mauna Loa a few days before the 1984 eruption began (Lockwood et al. 1987). Some of these observations of thermal precursors may have been serendipitous, and continuously-operating thermal cameras offer a continuous tool for detection of such precursors.
Handheld thermal cameras have been used in numerous field campaigns at many volcanoes around the world, but far fewer fixed, continuously operating, thermal camera installations exist. In the last ten years, however, more of these continuous systems have been installed on a handful of volcanoes. Thermal cameras at the summit of Stromboli volcano were vital in tracking the onset and progress of the 2007 effusive eruption, which began with the opening of hot fissures that drained the uppermost magma column (Ripepe et al. 2009; Calvari et al. 2010). Delle Donne et al. (2006) used data from a fixed thermal camera on Stromboli to analyze almost 20,000 explosions, and integrated the observed dynamics with infrasound to create one of the longest-term characterizations of strombolian explosive behavior to date. Thermal cameras are one component in an extensive network closely monitoring Mt. Etna, where explosive activity can rapidly threaten air traffic around the city of Catania (Alparone et al. 2007; Bonaccorso et al. 2011). Thermal cameras were installed in 2006 to monitor the fumarole field at Vulcano, Italy, and have detected a decreasing trend in fumarole temperatures (Lodato et al. 2009). Chiodini et al. (2007) describes a thermal camera installed in 2004 at Campei Flegrei, Italy, that detected subtle offsets in thermal output of the fumarole field associated with two seismic swarms, which may have impacted the hydrothermal system. A thermal camera was installed at Turrialba volcano in 2010 by University of Costa Rica geologists to monitor gas emission from fissures that opened in June 2007 (M. Mora, written communication). During the 2010 eruption of Eyjafjallajökull, Iceland, a telecommunications company installed a thermal camera about 10 km from the volcano to monitor activity. Yokoo (2009) used a continuously operating thermal camera, installed in 2007, to monitor the explosive eruptions at Sakurajima volcano, Japan, during 2008 and study the thermal evolution of the ash plumes. Thermal cameras have provided insightful results during field campaigns at Erebus lava lake (Oppenheimer et al. 2009), and plans are underway to install a permanent fixed camera there (N. Peters, written communication). Spampinato et al. (2011) and Harris (2013) provide comprehensive summaries of the theory of radiative transfer, technical limitations and recent applications of thermal cameras, both fixed and handheld, at volcanoes around the world.
In this paper, we detail the installation and image acquisition setup of several fixed thermal cameras on Kīlauea and Mauna Loa volcanoes in Hawai‘i. These cameras were installed during 2010–2012 in a variety of environments and monitored volcanic processes including lava lakes, intracrater vents, fissure eruptions, lava flows and fumarolic activity (Patrick et al. 2012a). In addition to details on the equipment and setup specifications, we provide detailed summaries and code for the numerous Matlab scripts that manage image acquisition, image processing, data management and alarming (see Additional files 1, 2, 3, 4, 5, 6, 7). Finally, we highlight recent results from our thermal camera network, mostly during highly dynamic activity on Kīlauea in 2011, to demonstrate the potential of this system for both monitoring and understanding volcanic processes.
Recent volcanic activity in Hawai‘i
In addition to Kīlauea’s summit eruption, the long-lived east rift zone eruption at Pu‘u ‘Ō‘ō, which began in 1983 (Heliker and Mattox 2003), continued with episodes 58–61 during 2010–2012 (Orr et al. 2013b). Episode 58 (Poland et al. 2008b; Patrick et al. 2011a; Patrick and Orr 2011), ended with the Kamoamoa intrusion and fissure eruption (episode 59) in early March 2011 (Orr et al. 2013b). Following the Kamoamoa eruption, lava refilled Pu‘u ‘Ō‘ō’s crater (episode 60) and eventually broke out from the lower west flank of Pu‘u ‘Ō‘ō cone in early August 2011. Lava refilled Pu‘u ‘Ō‘ō once again (episode 61), and burst through the upper east flank in late September 2011. These “Peace Day” lava flows reached the ocean in December 2011 and remained active until late 2013.
Mauna Loa’s most recent eruption was in 1984 (Lockwood et al. 1987), when flows stalled within 7 km of the outskirts of the city of Hilo (pop. 43,000). A period of pronounced summit inflation and deep long-period earthquakes in 2002–2004 suggested reawakening of the volcano but did not culminate in an eruption (Miklius and Cervelli 2003; Miklius et al. 2005; Amelung et al. 2007). During 2010–2012, deformation was minimal and earthquake activity was at background levels, giving no indication of imminent eruptive activity. Nevertheless, the time since Mauna Loa’s last eruption stands as its longest historic repose period, based on data in Decker et al. (1995). Also, Mauna Loa’s capacity for extremely high-effusion-rate flows (500 m3 s-1 or more, from Lipman and Banks (1987)) and high flow-advance rates requires close monitoring for potential signs of unrest. Fumarolic activity remains on the caldera floor (Casadevall and Hazlett 1983; Patrick and Witzke 2011).
Although the cameras are intrinsically temperature-calibrated, numerous extrinsic field conditions can result in the measured, or apparent, temperature being different than the actual surface temperature (Ball and Pinkerton 2006 Harris 2013, Additional file 2). The apparent temperature measured by the cameras will usually be lower than the actual surface temperature for several reasons. First, volcanic fume between the target surface and the camera will attenuate the radiant signal of the surface significantly (Sawyer and Burton 2006). In some cases, particularly if there is much condensed water in the plume, the target surface may be entirely blocked by fume. Second, an individual pixel temperature will be a composite of all the temperatures within the pixel footprint. If the hot target is small and the majority of the pixel area is cooler, this “mixed pixel” issue results in the pixel-integrated temperature being significantly lower than that of the hot target. The pixel footprint size therefore plays a part in the temperature accuracy—and effective sensitivity—of the cameras (Ball and Pinkerton 2006). This relates to another limitation of the cameras: thermal camera images tend to be very low resolution (Spampinato et al. 2011). The cameras used in this study have image sizes of 320 × 240 pixels (0.08 megapixels), which was the standard resolution available for this type of camera in 2010. At a distance of 200 m, the pixel footprint for the 53° lens would be about 62 cm wide.
In some cases, the view of the target can be entirely blocked by volcanic fume. In Hawai‘i, we have only seen this happen during phases when the plume is particle-laden—for instance, immediately after a rockfall into the vent. These episodes are infrequent and last only seconds; the remainder of the time, the plume is always transparent in the infrared and observation is therefore essentially continuous. In other cases, such as in Alaska, volcanic fume often completely blocks the view of thermal cameras (Wessels et al. 2012). This may be due to the lower ambient temperatures, and higher abundance of condensed water droplets in those plumes.
Notwithstanding the above limitations in temperature accuracy, temperature-calibrated thermal cameras still provide more information than simple “relative” values, which could be provided by less expensive, uncalibrated, cameras. First, the temperature values are more intuitively useful for characterizing activity than the digital numbers output by uncalibrated cameras. Even with the above limitations in accuracy, they often still provide a good “ball park” temperature that is useful for basic hazard assessment, particularly for the casual user. Second, in most cases, the apparent temperature values will be an underestimate of the true surface temperature, and thus they can be taken as a minimum value that often has use. For instance, when observing an apparent temperature of 300°C, we can assume the true temperature is higher than this, which in Hawai‘i is normally indicative of active, flowing lava. For the equivalent scenario with an uncalibrated camera, we might observe a digital number of 3420, which we take as a minimum value, but this has little use without much more context that may not be available to the casual user.
Camera, enclosure and power
Mikron M7500L camera specifications
Uncooled focal plane array (microbolometer)
320 × 240 pixels
Image update rate:
+/− 2% or 2°C of reading*
0.06°C at 30°C
Range 1: -40 to 120°C
Range 2: 0 to 500°C
100 Base T Ethernet
−15 to 50°C
12 V DC
Dimensions (with root lens)
8.2 × 8.3 × 17.9 cm
Weight (with root lens)
Root: 21.7° × 16.4°
Spyglass: 53° × 40° (lens is 16.3 cm long)
Extreme wide angle: 75° × 56° (lens is about 8 cm long)
2× telephoto: 10.9° × 8.2° (lens is 18.9 cm long)
Equipment list and costs
Total cost $USD
Mikron M7500L camera
Germanium IR window (3” diam., 8 mm thick)
PVC window frame (custom made)
AcTron Machine Co.
Aluminum mounting plates (custom made set)
AcTron Machine Co.
Long ethernet cable
Miscellaneous electrical components
12 volt car batteries (group 27 105 Ah)
80 W solar panels
Charge controllers (10 amp)
Wifi radio (CM9 radio card)
Antenna (24 dB parabolic magnesium)
Network switch (model NS 205)
12 volt car batteries (group 27 105 Ah)
80 W solar panels
Charge controllers (10 amp)
Mikrospec RT-Multi and SDK
Matlab with image processing toolbox:
Total cost for one camera setup (excluding software):
In a lone configuration, the camera is powered by four 12-volt batteries which are recharged by two 80-Watt solar panels. Later upgrades to our instrument sites included large battery banks shared by multiple instruments. An IP-capable power relay unit was installed in order to remotely cycle the power (i.e., turn the camera off, then on) from the office. We found that the power relay unit was essential for reliable operation, as some camera problems could only be solved by cycling the camera power. Without the power relay unit, we would need to wait days or weeks until the next helicopter overflight to service the camera. Power consumption is described in Additional file 1.
Telemetry and acquisition
The camera outputs data through an Ethernet cable, which exits out the back of the enclosure and is run to a telemetry station that is generally a few tens of meters from the camera site. A WiFi radio at the telemetry station transmits the images back to the observatory in real-time. The telemetry station, which is powered by its own batteries and solar panels or connected to a shared battery bank, may be used by several other instruments (e.g. GPS or other webcams) at the site.
We used two blade servers at the observatory to run the acquisition and processing. Details on the computer equipment are in Additional file 1.
Deployment sites and acquisition schemes
The first camera (HTcam) was installed at Halema‘uma‘u, viewing the lava lake, in October 2010 (Figures 1 and 2). Next, a thermal camera (PTcam) was installed at the rim of Pu‘u ‘Ō‘ō crater in March 2011 (Figures 1 and 2), just after the Kamoamoa eruption. This camera followed the repeated filling and draining of lava within the crater through the remainder of that year. In July 2011, anticipating possible breakouts on the flank of Pu‘u ‘Ō‘ō cone, two cameras were installed on the upper flanks of the cone looking east (ETcam) and west (WTcam). A fifth camera (MTcam) was deployed at the summit of Mauna Loa (Figures 1 and 2), overlooking the summit caldera, in October 2012.
We operated two types of acquisition: a high-rate version and low-rate version. The high-rate acquisition, which acquired an image every five seconds, was used only at Halema‘uma‘u (HTcam), where the highly dynamic and continuously circulating lava lake requires a high observation rate. The low-rate acquisition, in which images are acquired every few minutes, was used for all other cameras. This lower rate is adequate for most situations, given the typically slow rates of lava movement. These two acquisition schemes are detailed in the sections below.
List of scripts
High frequency acquisition (image every few seconds) for Mikron 7500 camera
Check to make sure Mikrospec RT Multi is running
Every 5 min.
Run scripts H2a-d
Move image files from local to temporary directory for analysis
Measure lava level
Measure crust velocity
Archive images in date folders
Make composite image
Write data to VALVE
Check hard drive space
Once a day
Low frequency acquisition (image every few minutes) for Mikron 7500 camera
Acquire single image, make html image, and archive
Every 2–5 minutes
Connect to camera and acquire single binary image
Visual BASIC .NET
Every 2–5 minutes
Track temperature trends
Alarm if anomalous temperatures detected
Every 10 minutes
Kill Matlab sessions that are hung
Once a day
Make composite image
Cycle power on thermal camera power relay
Matlab and HTML
Send email if acquisition is failing
Low frequency acquisition (image every few minutes) for FLIR A320 camera
Acquire single image, make html image, and archive
Every few minutes
Mikrospec RT-Multi (Version 2.10 build 209) is a program developed by Lumasense-Mikron to interface with their M7500 cameras and acquire and analyze images. We use it simply to acquire images and do not perform any analyses. The acquired images are written by the program to an acquisition directory, and Script H2 (Additional files 3 and 6) performs subsequent data management. Mikrospec maintains an open connection with the camera, even when not saving images, and consumes significant bandwidth. The software also sets the camera’s non-uniformity correction (a periodic internal camera calibration) frequency, which we set to 15 minutes.
The low-frame-rate scheme is meant to acquire an image every few minutes. Unlike the high-rate acquisition Mikrospec program that maintains a continuous connection with the camera, this low rate approach only initiates a connection when an image is acquired, and immediately closes the connection, which minimizes bandwidth usage. For the image rates we use (an image every 2–5 minutes), the data rates are about 150 Mb per day for each camera. This low-rate approach is largely contained within Script L1 (Additional files 3 and 7), and the other scripts perform accessory tasks, such as alarming and recording temperature trends. Table 3 and Additional files 3 and 7 contain more details on the acquisition scripts.
Web display of images and data
In addition, our internal website has the web application VALVE (a time-series viewing interface, Cervelli et al. 2002), and some products from the thermal cameras are shown using VALVE. For instance, the Halema‘uma‘u lava level (Script H2b, Table 3, Additional files 3 and 6) and the temperature trends in and around Pu‘u ‘Ō‘ō (Script L2, Table 3, Additional files 3 and 7) are shown in VALVE.
The first months of setting up the cameras were challenging, with several computer issues that seemed to be related to operating system compatibility. Since these bugs were worked out and acquisition began, performance has been very good, with only brief interruptions. Details on performance issues and bugs are described in Additional file 5.
Results and discussion
Another benefit is that thermal cameras provide a clearer and more consistent view of active lava flows than visible-wavelength webcams. Normal webcams may only show active lava flows clearly at night when incandescence stands out; during the day, lava may or may not exhibit obvious incandescence or color contrast with the surroundings, depending on activity levels and the nature of the surroundings. Thermal cameras, on the other hand, provide an unambiguous image of flow activity, day or night (Figure 5). In addition, information on relative age of flow lobes can be roughly estimated by eye using the temperature information, in many instances.
Because thermal camera images are less sensitive to day-night fluctuations (the effects of solar heating are relatively minor for hot, active volcanic surfaces; see Additional file 2) and less susceptible to interference from fume, they provide a superior long-term view of activity compared to visible-wavelength webcams. Normal webcams will have daily changes in sunlight and illumination angle and variable visibility due to shifting fume, often making their long-term time-lapse sequences appear distractingly “busy” and therefore less informative. Long-term time-lapse sequences from the thermal cameras, in many cases, provide a substantially clearer view of evolving volcanic processes than time-lapse sequences from conventional webcams (see Additional files 8, 9, 10, 11, 12, 13).
Kīlauea summit: Automated lava-level tracking at Halema‘uma‘u
Kīlauea summit: Halema‘uma‘u long-term lava levels
In February 2011, the lava lake was at a relatively high level, following continued inflation of the summit. At its peak, the lava was about 62 m below the rim of the Overlook crater—the highest level for the eruption to that time. On March 5, increasing pressurization of the east rift zone conduit reached the failure point, and magma intruded from the conduit to the surface, triggering the Kamoamoa fissure eruption (Orr et al. 2013b). This depressurized the system and presumably diverted large amounts of magma from the east rift zone conduit, resulting in major lava level drops at both Halema‘uma‘u and Pu‘u ‘Ō‘ō. Over the course of about 24 hours, the lava in Halema‘uma‘u dropped by about 140 m. The lava largely disappeared from the vent for over a week, reappearing briefly as transient rises in lava level occurred due to summit deflation-inflation cycles. From March to August, the lava level rose at an unsteady rate during repressurization of the magmatic system. By early August it had nearly achieved its pre-Kamoamoa level, and was about 70 m below the vent rim. On August 3, fissures opened on the lower flank of Pu‘u ‘Ō‘ō, again depressurizing the east rift zone conduit and leading to a rapid drop (of about 85 m) in the Halema‘uma‘u lava lake. The level again recovered, and returned to relatively high levels by early September. On September 21, fissures again opened on Pu‘u ‘Ō‘ō, and lava abruptly dropped a minor amount at Halema‘uma‘u.
Similar to Figure 6, Figure 7 shows a remarkable correlation between the lava-lake level in Halema‘uma‘u and the summit ground tilt. While Figure 6 demonstrates that the lava level acts as a reliable pressure gauge of the summit reservoir over a time-span of days, Figure 7 shows that this relation also applies over the course of weeks to months.
Kīlauea summit: Halema‘uma‘u gas pistoning and lava lake circulation
Kīlauea east rift zone: Pu‘u ‘Ō‘ō refilling and perched lava lake growth
Kīlauea east rift zone: Onset of August 3 and September 21, 2011, fissure eruptions
The rapid draining of lava through the west flank of Pu‘u ‘Ō‘ō was captured by a thermal camera on the north flank of Pu‘u ‘Ō‘ō (Figure 10a-d; Additional file 12). The thermal camera image was one of the first indications that a new fissure eruption had begun. It also documented the extremely high advance rate of the flows due to their unusually high effusion rate, which was presumably driven by the high magmatic head in the cone (akin to draining water from a bucket by punching a hole in its base). A preliminary estimate of the effusion rate from this fissure during the first 2.75 hours is 110–330 m3 s-1 DRE (dense rock equivalent), based on lava-flow-volume measurements. The draining mechanism and unusually high-effusion-rate flows are reminiscent of the 1977 flank eruption of Nyiragongo, DRC (Tazieff 1977).
The westward-viewing thermal camera also captured another intriguing process. The surface of the western flank of Pu‘u ‘Ō‘ō cone was observed to be briefly lifted immediately before the onset of the fissure eruption (Figure 10b; Additional file 12), presumably due to magma injection through this part of the cone. The WTcam thermal camera (Figure 2b) captured a portion of this deformation, which consisted of about 3 m of uplift of the surface. Another webcam on Pu‘u ‘Ō‘ō showed that the portion of the cone that experienced the greatest deformation was uplifted 10 m.
Following the August 3 draining, effusion was focused on the west flank of Pu‘u ‘Ō‘ō for almost two weeks, but returned to Pu‘u ‘Ō‘ō crater in late August. The crater once again began to fill with lava, and lava reached the rim again in mid-September. On September 13 at 17:50, the script that was running for the ETcam and WTcam detected the spillout of flows over the east rim, sending a text message alarm to cell phones belonging to HVO staff geologists T. Orr and M. Patrick. In the early morning of September 21, lava broke through a fissure just below the east rim of Pu‘u ‘Ō‘ō crater, sending flows towards the southeast. The fissure was just out of view of the ETcam, but elevated temperatures in the clouds and fog around the fissure indicated an increase in activity in that area (Figure 10e,f).
Kīlauea east rift zone: Automated temperature tracking
Mauna Loa monitoring
Future work and improvement
The cameras described in this setup have an image size of 320 × 240 pixels, which was the standard resolution for fixed thermal cameras during requisition in 2009. At that time, however, new cameras were appearing on the market with higher resolution. The FLIR SC655 camera has an image size of 640 × 480 pixels, which is four times the amount of data. At HVO, we have used handheld thermal cameras with both 320 × 240 and 640 × 480 image sizes and, while the 320 × 240 images provide a reasonably good image, the 640 × 480 images are remarkably sharper. As the price of these 640 × 480 cameras will hopefully decline in coming years, the next generation of the thermal camera setup described in this paper should incorporate one or more of the 640 × 480 cameras, or even higher-resolution cameras when they become available.
In our discussion of performance in Additional file 5, we describe how interfacing with the cameras was often tricky and fraught with difficulties, and troubleshooting problems related to operating system compatibility and other computer-related issues was one of the most time-consuming parts of this project. New fixed thermal cameras appearing on the market may potentially reduce this problem by using a common, shared and open-source interface like GigE Vision and GenICam. The GenICam standard will essentially replace the proprietary software development kits (SDK) currently used, and hopefully make interfacing with the cameras less problematic.
A primary justification for purchasing the thermal cameras was their capability to automatically detect activity—that is, alarm—based on temperature changes. The alarming tool that we currently use (Script L3; Additional file 7) is very basic and uses a simple temperature threshold, but more sensitive techniques for detecting subtle changes are possible. For instance, the technique used by Pergola et al. (2004) and Koeppen et al. (2011) looks at long-term trends in thermal satellite images to build a picture of the normal variations in surface temperature at each pixel. This normal variation is constrained by a selected number of standard deviations around the long-term mean temperature for each pixel. The same approach could easily be applied to thermal camera images. When pixels start to deviate outside of their normal temperature envelope, the pixel is flagged and an alert is issued.
For thermal cameras looking out over broad areas, the precise location of alerted pixels is potentially useful for determining the geographical coordinates of, say, a new fissure. Currently at HVO, we use incandescence in nighttime images from our visual webcams to automatically locate active breakouts (Patrick et al. 2012b). By knowing the camera viewing geometry, the location of bright pixels in the images can be translated to azimuths from the camera. Mapping these azimuths as rays on a flow-field map then helps constrain the location of active breakouts. In some cases, we have mapped these pixel locations onto a DEM surface, providing absolute mapping of active breakouts. This same approach could easily be applied to the thermal camera images for automated mapping of anomalous thermal activity, and more sophisticated photogrammetric approaches might also have promise.
Thermal cameras have dramatically improved HVO’s observational capabilities. The cameras have provided views of volcanic activity that would simply not have been possible with visible-wavelength cameras, enabling uninterrupted surface observations. They allow us to visually monitor the summit lava lake continuously, and identify and locate active lava flows day or night. Although costly, we deem thermal cameras a highly worthwhile investment.
Italian researchers were some of the earliest adopters of fixed thermal cameras on volcanoes, and this project was spurred in part by the demonstrated success of their systems. Specifically, Maurizio Ripepe (University of Florence) and Luigi Lodato (INGV-Catania) provided much helpful information on their fixed thermal camera setups on Stromboli and Vulcano, Italy. Andrew Harris provided additional helpful information, and Rick Wessels (AVO) provided advice and loaned us the FLIR A320 to test. Adolph Teves of AcTron Machine Co. worked closely with us to design the enclosure parts. Matt Ducharme and Kreg Kelley of Lumasense provided considerable assistance and answered many questions during initial camera setup. Bill Million and Cyril Moniz, both of HVO, have helped maintain the thermal cameras in the field. Comments from two anonymous reviewers were greatly appreciated. The use of manufacturer’s names is provided for information only and does not constitute an endorsement by the US Geological Survey, the US Department of Interior or the US Government.
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