The Development of a Low-Cost, Near Infrared, High-Temperature Thermal Imaging System and Its Application to the Retrieval of Accurate Lava Lake Temperatures at Masaya Volcano, Nicaragua
"> Figure 1
<p>(<b>A</b>) Lens design in OpticStudio (Zemax Ltd.) showing the position of each lens in the triplet, the aperture, filter and sensor from the PiCam. Colours represent light rays terminating at different field heights on the focal plane array; red displays the rays at the edge of the camera field of view (5° from the optical axis), whilst blue represents rays parallel to the optical axis. (<b>B</b>) Image of the 3D printed lens holder and camera mount. The filter holder slides into the camera mount during operation. The triplet lens holder is threaded and thus can be focused (at infinity) in the field.</p> "> Figure 2
<p>Main image: Photograph of the PiCam capturing images of the lava lake at Masaya volcano on 12 June 2017. The plume aerosols are quite clearly visible, as are bubble bursts in the lake itself. Inset: A schematic of the estimated viewing geometry provided by Instituto Nicaragüense de Estudios Territoriales (INETER; Personal Communication, 2017); figure not to scale.</p> "> Figure 3
<p>(<b>A</b>) A plot showing how retrieved temperature varies with emissivity of the object. Displayed at 3 different Digital Numbers (DNs), for a shutter speed of 1 ms and with a path transmission coefficient of 0.8789. (<b>B</b>) As (<b>A</b>) but displaying the effect of a water vapour correction on the retrieved temperature, i.e., larger estimated water vapour loadings in the path cause higher temperatures to be retrieved since there is more absorption of radiation across the path. For each data point the transmission coefficient was calculated as the mean between 800–1200 °C (see <a href="#sec2dot3-remotesensing-10-00450" class="html-sec">Section 2.3</a> for further explanation). Data is plotted for an emissivity of 0.95, with atmospheric temperature and pressure of 26.5 °C and 94,300 Pa, respectively; relative humidity is quoted using a path length of 412 m, used in the field tests on Masaya volcano (see <a href="#sec2dot5-remotesensing-10-00450" class="html-sec">Section 2.5</a>).</p> "> Figure 4
<p>Calculated measurement uncertainties vs measured temperature for 1 ms exposure time on the PiCam. As in the discussion of <a href="#sec2dot4-remotesensing-10-00450" class="html-sec">Section 2.4</a>, all uncertainties are for a 95% confidence interval. For the majority of uncertainties, a larger temperature is concomitant with larger measurement uncertainty, apart from the sensor noise uncertainty, since the signal-to-noise ratio increases with increasing signal/temperature; longer exposure times will decrease the sensor noise uncertainty for a given temperature and, thus, somewhat extend the use of this system to lower temperatures. Since flat-field uncertainty could be corrected for and emissivity could possibly be more accurately constrained than in this study, the minimum uncertainties of this technique are likely constrained by the sensor noise and calibration uncertainties.</p> "> Figure 5
<p>A PiCam image of the Masaya lava lake, taken on 12 June 2017 at 18:12:20 UTC. Lake temperatures of up to 1059 ± 14 °C are observed here. Temperatures are highest towards the edges where collisions with the crater wall appear to occur and elsewhere in the lake when bubble bursts expose fresh magma. The high apparent temperature of the crater wall is due to reflection of the lake’s radiation, either by aerosols or by the wall itself; these temperatures are, therefore, inaccurate.</p> "> Figure 6
<p>Temperature time series from 18:12:20 to 18:44:48 UTC on 12 June 2017, taken with a 1 ms shutter speed at a framerate of 0.5 Hz. Maximum, minimum and average temperatures of the lava lake region of interest (ROI) and displayed. Maximum and minimum temperatures have associated total uncertainties displayed as a shaded region.</p> "> Figure 7
<p>Radiant flux time series from 18:12:20 to 18:44:48 UTC on 12 June 2017. The flux ranges from 30 to 45 MW, with an average of 37 MW. The lake area, used in this calculation (Equation (11)), was estimated to be 280 m<sup>2</sup>.</p> "> Figure 8
<p>A stack of lava lake temperature histograms (central pane), similar to the RadTherm plots of Coppola et al. [<a href="#B44-remotesensing-10-00450" class="html-bibr">44</a>]. Surrounding subplots display lava lake thermal images and the associated temperature histograms; for ease of comparison, all histograms are plotted on the same axis scale, as in <a href="#remotesensing-10-00450-f009" class="html-fig">Figure 9</a>. Subplots show examples of: (<b>A</b>) bimodal temperature distribution due to a relatively large amount of spattering at the lake edge and the cooler crust surface; (<b>B</b>) extremely hot temperatures due to high levels of edge spattering and large bubble bursts exposing fresh hot lava; (<b>C</b>) weak-positively skewed distribution of temperatures due to a relatively undisturbed cooled crust, along with small bubble bursts; (<b>D</b>) aerosol extinction obscuring the view of the lava lake and, thus, causing significantly lower retrieved temperatures. Note that the frequency colour scale relates to the central stacked histogram figure, whilst the temperature colour scale relates to the lava images.</p> "> Figure 9
<p>Histograms of temperature distributions, in 10 °C bins, across the lava lake from 18:12:20 to 18:44:48 UTC on 12 June 2017. The lava lake area was defined by a user-defined region of interest. For clarity, histograms are coloured by the frame time they represent; earlier frames are more blue and later frames are more red. The bold yellow line represents the mean distribution, which is a slight positive skew. This is likely due to bubble bursts and lake turbulence which introduce hotter lava into what otherwise would be a steadily cooling crust which you may expect to display a Gaussian temperature distribution.</p> "> Figure A1
<p>(<b>A</b>) Temperature errors associated with solar reflection vs. emissivity, for a range of temperatures. (<b>B</b>) As in (<b>A</b>) but for a much lower temperature of 500 °C. For lava lake temperatures presented in this article (predominantly 900–1100 °C) errors caused by solar reflections are minimal (all < 6 °C) for emissivities > 0.9. At much lower temperatures (500 °C) the solar effect is much more significant, even at emissivities approaching 1; therefore, it is likely that applications imaging such temperatures would need to be either away from direct sunlight, at night, or possibly with a sophisticated correction for solar radiance.</p> "> Figure A2
<p>A plot of Digital Number (DN) vs. Shutter Speed (ms), where the DN is found from an average of 30 images taken imaging the blackbody furnace at the specified temperature. Error bars represent the associated uncertainty of this 30-member mean. The optical system used for this test had the 1080 nm band-pass filter mounted to the fore of the system, as well as the 850 nm long pass filter mounted behind the lens triplet.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
2.1. Instrumental Design
2.2. Calibration Procedure
2.3. Extinction and Emissivity
2.4. Uncertainty Analysis
2.5. Field Deployment
3. Results and Discussion
4. Concluding Remarks
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Appendix B
Parameter | Value | Used in Equation |
---|---|---|
A0 | 1.35 × 10−8 | 1–3 |
A1 | 8.6697 × 10−7 | 1–3 |
A2 | 3.90586 × 10−5 | 1–3 |
[°C] | 1.08 | 4 |
B0 | 0.6966 | 5 |
B1 | 0.002594 | 5 |
C0 | 0.1098 | 6 |
C1 | 0.1545 | 6 |
Appendix C
References
- Spampinato, L.; Calvari, S.; Oppenheimer, C.; Boschi, E. Volcano surveillance using infrared cameras. Earth Sci. Rev. 2011, 106, 63–91. [Google Scholar] [CrossRef]
- Patrick, M.R.; Orr, T.; Antolik, L.; Lee, L.; Kamibayashi, K. Continuous monitoring of Hawaiian volcanoes with thermal cameras. J. Appl. Volcanol. 2014, 3, 1. [Google Scholar] [CrossRef]
- Oppenheimer, C.; Yirgu, G. Thermal imaging of an active lava lake: Erta ‘Ale volcano, Ethiopia. Int. J. Remote Sens. 2002, 23, 4777–4782. [Google Scholar] [CrossRef]
- Peters, N.; Oppenheimer, C.; Killingsworth, D.R.; Frechette, J.; Kyle, P. Correlation of cycles in Lava Lake motion and degassing at Erebus Volcano, Antarctica. Geochem. Geophys. Geosyst. 2014, 15, 3244–3257. [Google Scholar] [CrossRef]
- Delle Donne, D.; Ripepe, M. High-frame rate thermal imagery of strombolian explosions: Implications for explosive and infrasonic source dynamics. J. Geophys. Res. Solid Earth 2012, 117, B09206. [Google Scholar] [CrossRef]
- McGonigle, A.J.S.; Aiuppa, A.; Giudice, G.; Tamburello, G.; Hodson, A.J.; Gurrieri, S. Unmanned aerial vehicle measurements of volcanic carbon dioxide fluxes. Geophys. Res. Lett. 2008, 35, 3–6. [Google Scholar] [CrossRef]
- Amici, S.; Turci, M.; Giulietti, F.; Giammanco, S.; Buongiorno, M.F.; La Spina, A.; Spampinato, L. Volcanic environments monitoring by drones, Mud Volcano case Study. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2013, XL-1/W2, 5–10. [Google Scholar] [CrossRef]
- Mori, T.; Hashimoto, T.; Terada, A.; Yoshimoto, M.; Kazahaya, R.; Shinohara, H.; Tanaka, R. Volcanic plume measurements using a UAV for the 2014 Mt. Ontake eruption. Earth Planets Space 2016, 68, 49. [Google Scholar] [CrossRef]
- Chio, S.H.; Lin, C.H. Preliminary study of UAS equipped with thermal camera for volcanic geothermal monitoring in Taiwan. Sensors 2017, 17, 1649. [Google Scholar] [CrossRef] [PubMed]
- Saito, T.; Sakai, S.; Iizawa, I.; Suda, E.; Umetani, K.; Kaneko, K.; Furukawa, Y.; Ohkura, T. A new technique of radiation thermometry using a consumer digital camcorder: Observations of red glow at Aso volcano, Japan. Earth Planets Space 2005, 57, 5–8. [Google Scholar] [CrossRef]
- Furukawa, Y. Infrared thermography of the fumarole area in the active crater of the Aso volcano, Japan, using a consumer digital camera. J. Asian Earth Sci. 2010, 38, 283–288. [Google Scholar] [CrossRef] [Green Version]
- Radebaugh, J.; Lopes, R.M.; Howell, R.R.; Lorenz, R.D.; Turtle, E.P. Eruptive behavior of the Marum/Mbwelesu lava lake, Vanuatu and comparisons with lava lakes on Earth and Io. J. Volcanol. Geotherm. Res. 2016, 322, 105–118. [Google Scholar] [CrossRef]
- Dixon, J. Radiation Thermometry; John Wiley & Sons: Hoboken, NJ, USA, 1988. [Google Scholar]
- Ball, M.; Pinkerton, H. Factors affecting the accuracy of thermal imaging cameras in volcanology. J. Geophys. Res. Solid Earth 2006, 111, B11203. [Google Scholar] [CrossRef]
- Wilkes, T.C.; McGonigle, A.J.S.; Pering, T.D.; Taggart, A.; White, B.; Bryant, R.; Willmott, J.R. Ultraviolet Imaging with Low Cost Smartphone Sensors: Development and Application of a Raspberry Pi-Based UV Camera. Sensors 2016, 16, 1649. [Google Scholar] [CrossRef] [PubMed]
- Gunturk, B.K.; Glotzbach, J.; Altunbasak, Y.; Schafer, R.W.; Mersereau, R.M. Demosaicking: Color filter array interpolation. IEEE Signal Process. Mag. 2005, 22, 44–54. [Google Scholar] [CrossRef]
- Patrick, M.R.; Orr, T.; Lee, L.; Moniz, C.J. A Multipurpose Camera System for Monitoring Kilauea Volcano, Hawai’i; U.S. Geological Survey: Reston, VA, USA, 2015.
- Wilkes, T.C.; Pering, T.D.; McGonigle, A.J.S.; Tamburello, G.; Willmott, J.R. A Low-Cost Smartphone Sensor-Based UV Camera for Volcanic SO2 Emission Measurements. Remote Sens. 2017, 9, 27. [Google Scholar] [CrossRef]
- Wilkes, T.C.; McGonigle, A.J.S.; Willmott, J.R.; Pering, T.D.; Cook, J.M. Low-cost 3D printed 1 nm resolution smartphone sensor-based spectrometer: Instrument design and application in ultraviolet spectroscopy. Opt. Lett. 2017, 42, 4323. [Google Scholar] [CrossRef] [PubMed]
- Aiuppa, A.; de Moor, J.M.; Arellano, S.; Coppola, D.; Francofonte, V.; Galle, B.; Giudice, G.; Liuzzo, M.; Mendoza, E.; Saballos, A.; et al. Tracking Formation of a Lava Lake From Ground and Space: Masaya Volcano (Nicaragua), 2014–2017. Geochem. Geophys. Geosyst. 2018, 2014–2017. [Google Scholar] [CrossRef]
- Report on Masaya (Nicaragua). In Bulletin of the Global Volcanism Network; Venzke, E. (Ed.) Smithsonian Institution: Washington, DC, USA, 2017; Volume 42. [Google Scholar]
- Lane, B.; Whitenton, E.P. Calibration and Measurement Procedures for a High Magnification Thermal Camera; National Institute of Standards and Technology: Gaithersburg, MD, USA, 2015. [CrossRef]
- Saunders, P.; White, D.R. Physical basis of interpolation equations for radiation thermometry. Metrologia 2003, 40, 195–203. [Google Scholar] [CrossRef]
- Sawyer, G.M.; Burton, M.R. Effects of a volcanic plume on thermal imaging data. Geophys. Res. Lett. 2006, 33, L14311. [Google Scholar] [CrossRef]
- Gordon, I.E.; Rothman, L.S.; Hill, C.; Kochanov, R.V.; Tan, Y.; Bernath, P.F.; Birk, M.; Boudon, V.; Campargue, A.; Chance, K.V.; et al. The HITRAN2016 molecular spectroscopic database. J. Quant. Spectrosc. Radiat. Transf. 2017, 203, 3–69. [Google Scholar] [CrossRef]
- Pliutau, D.; Roslyakov, K. Bytran -|- spectral calculations for portable devices using the HITRAN database. Earth Sci. Inform. 2017, 10, 395–404. [Google Scholar] [CrossRef]
- Kochanov, R.V.; Gordon, I.E.; Rothman, L.S.; Wcisło, P.; Hill, C.; Wilzewski, J.S. HITRAN Application Programming Interface (HAPI): A comprehensive approach to working with spectroscopic data. J. Quant. Spectrosc. Radiat. Transf. 2016, 177, 15–30. [Google Scholar] [CrossRef]
- Pinkerton, H.; James, M.; Jones, A. Surface temperature measurements of active lava flows on Kilauea volcano, Hawai’i. J. Volcanol. Geotherm. Res. 2002, 113, 159–176. [Google Scholar] [CrossRef]
- Rothery, D.A.; Francis, P.W.; Wood, C.A. Volcano Monitoring Using Short Wavelength Infrared Data from Satellites. J. Geophys. Res. 1988, 93, 7993–8008. [Google Scholar] [CrossRef]
- Ripepe, M.; Harris, A.J.L.; Marchetti, E. Coupled thermal oscillations in explosive activity at different craters of Stromboli volcano. Geophys. Res. Lett. 2005, 32, L17302. [Google Scholar] [CrossRef]
- Lane, B.; Whitenton, E.; Madhavan, V.; Donmez, A. Uncertainty of temperature measurements by infrared thermography for metal cutting applications. Metrologia 2013, 50, 637–653. [Google Scholar] [CrossRef]
- Du, H.; Voss, K.J. Effects of Point-Spread Function on Calibration and Radiometric Accuracy of CCD Camera. Appl. Opt. 2004, 43, 665. [Google Scholar] [CrossRef] [PubMed]
- Baker, S.; Matthews, I. Lucas-Kanade 20 years on: A unifying framework. Int. J. Comput. Vis. 2004, 56, 221–255. [Google Scholar] [CrossRef]
- Evangelidis, G. IAT: A Matlab Toolbox for Image Alignment. Available online: https://sites.google.com/site/imagealignment/ (accessed on 10 November 2017).
- Spampinato, L.; Ganci, G.; Hernández, P.A.; Calvo, D.; Tedesco, D.; Pérez, N.M.; Calvari, S.; Del Negro, C.; Yalire, M.M. Thermal insights into the dynamics of Nyiragongo lava lake from ground and satellite measurements. J. Geophys. Res. Solid Earth 2013, 118, 5771–5784. [Google Scholar] [CrossRef]
- Carling, G.T.; Radebaugh, J.; Saito, T.; Lorenz, R.D.; Dangerfield, A.; Tingey, D.G.; Keith, J.D.; South, J.V.; Lopes, R.M.; Diniega, S. Temperatures, thermal structure, and behavior of eruptions at Kilauea and Erta Ale volcanoes using a consumer digital camcorder. GeoResJ 2015, 5, 47–56. [Google Scholar] [CrossRef]
- Harris, A.J.L.; Flynn, L.P.; Rothery, D.A.; Oppenheimer, C.; Sherman, S.B. Mass flux measurements at active lava lakes: Implications for magma recycling. J. Geophys. Res. 1999, 104, 7117–7136. [Google Scholar] [CrossRef]
- Calkins, J.; Oppenheimer, C.; Kyle, P.R. Ground-based thermal imaging of lava lakes at Erebus volcano, Antarctica. J. Volcanol. Geotherm. Res. 2008, 177, 695–704. [Google Scholar] [CrossRef]
- Le Guern, F.; Carbonnelle, J.; Tazieff, H. Erta’Ale lava lake: Heat and gas transfer to the atmosphere. J. Volcanol. Geotherm. Res. 1979, 6, 27–48. [Google Scholar] [CrossRef]
- Oppenheimer, C.; McGonigle, A.J.S.; Allard, P.; Wooster, M.J.; Tsanev, V. Sulfur, heat, and magma budget of Erta ’Ale lava lake, Ethiopia. Geology 2004, 32, 509–512. [Google Scholar] [CrossRef]
- Spampinato, L.; Oppenheimer, C.; Calvari, S.; Cannata, A.; Montalto, P. Lava lake surface characterization by thermal imaging: Erta ’Ale volcano (Ethiopia). Geochem. Geophys. Geosyst. 2008, 9, Q12008. [Google Scholar] [CrossRef]
- Cipar, J.J.; Anderson, G.P.; Cooley, T.W. Temperature and power output of the lava lake in Halema’uma’u crater, Hawaii, using a space-based hyperspectral imager. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2012, 5, 617–624. [Google Scholar] [CrossRef]
- Le Guern, F. Mechanism of Energy Transfer in the Lava Lake of Niragongo (Zaire), 1959–1977. J. Volcanol. Geotherm. Res. 1987, 31, 17–31. [Google Scholar] [CrossRef]
- Coppola, D.; Staudacher, T.; Cigolini, C. Field thermal monitoring during the August 2003 eruption at Piton de la Fournaise (La Réunion). J. Geophys. Res. Solid Earth 2007, 112, B05215. [Google Scholar] [CrossRef]
- Gueymard, C.A. Parameterized transmittance model for direct beam and circumsolar spectral irradiance. Sol. Energy 2001, 71, 325–346. [Google Scholar] [CrossRef]
Uncertainty | Symbol | Quantification |
---|---|---|
Thermocouple uncertainty | 0.4 °C | |
Blackbody cavity temperature uncertainty | 1 °C | |
Blackbody emissivity uncertainty | 0.04 * | |
Fit uncertainty | Standard error of Sakuma-Hattori fit (see Table A1 for value at 1 ms shutter speed) |
Volcano Year | Instrument | Area (m2) | Radiant Power (MW) | Reference |
---|---|---|---|---|
Masaya | ||||
2017 | GB NIR camera | 280 | 30–45 | This article |
Erebus | ||||
1985 | Landsat TM | 180 | 12–18 | [37] |
1989 | Landsat TM | 300 | 8–15 | [37] |
2004 (Ray Lake) | GB MWIR Camera | 1400 | 20–40 | [38] |
2004 (Werner Lake) | GB MWIR Camera | 1000–1200 | 20 | [38] |
2004 (Total) | GB MWIR Camera | 2400–2600 | 40–60 | [38] |
Erta ‘Ale | ||||
1973 | Landsat TM | 3800 | 3546 | [39], [37] |
1986 | Landsat TM | 2960 | 11–22 | [37] |
2001 | GB MWIR Camera | 6200 | 70–150 | [3] |
2003 | GB MWIR Camera | 910 | 5–30 | [40] |
2006 | GB LWIR Camera | 2500 | 45–76 | [41] |
Kilauea | ||||
1991 (Pu’u ‘O’o) | Landsat TM | 4000 | 322–327 | [37] |
2009 (Halema’uma’u) | ARTEMIS | Not quoted | 15–24 | [42] |
Nyiragongo | ||||
1959 | Landsat TM | Unclear | 540 | [43], [37] |
1972 | Landsat TM | 45,200 | 1220 | [43], [37] |
1987 | Landsat TM | 25 | 0.1–0.3 | [37] |
2012 | GB LWIR Camera | 31,400 | 600–1200 | [35] |
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Wilkes, T.C.; Stanger, L.R.; Willmott, J.R.; Pering, T.D.; McGonigle, A.J.S.; England, R.A. The Development of a Low-Cost, Near Infrared, High-Temperature Thermal Imaging System and Its Application to the Retrieval of Accurate Lava Lake Temperatures at Masaya Volcano, Nicaragua. Remote Sens. 2018, 10, 450. https://doi.org/10.3390/rs10030450
Wilkes TC, Stanger LR, Willmott JR, Pering TD, McGonigle AJS, England RA. The Development of a Low-Cost, Near Infrared, High-Temperature Thermal Imaging System and Its Application to the Retrieval of Accurate Lava Lake Temperatures at Masaya Volcano, Nicaragua. Remote Sensing. 2018; 10(3):450. https://doi.org/10.3390/rs10030450
Chicago/Turabian StyleWilkes, Thomas Charles, Leigh Russell Stanger, Jon Raffe Willmott, Tom David Pering, Andrew John Samuel McGonigle, and Rebecca Anne England. 2018. "The Development of a Low-Cost, Near Infrared, High-Temperature Thermal Imaging System and Its Application to the Retrieval of Accurate Lava Lake Temperatures at Masaya Volcano, Nicaragua" Remote Sensing 10, no. 3: 450. https://doi.org/10.3390/rs10030450