Abstract
We investigate eruptive activity by analysis of thermal-alert data from the MODIS (moderate resolution imaging spectrometer) thermal infrared satellite instrument, detected by the MODVOLC (MODIS Volcano alert) algorithm. These data are openly available on the Internet, and easy to use. We show how such data can plug major gaps in the conventional monitoring record of volcanoes in an otherwise generally poorly documented region (Melanesia), including: characterising the mechanism of lava effusion at Pago; demonstrating an earlier-than-realised onset of lava effusion at Lopevi; extending the known period of lava lake activity at Ambrym; and confirming ongoing activity at Bagana, Langila and Tinakula. We also add to the record of activity even at some generally better-monitored volcanoes in Indonesia, but point out that care must be taken to recognise and exclude fires.
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Abbreviations
- MODIS:
-
Moderate-resolution imaging spectrometer
- MODVOLC:
-
MODIS Volcano alert
- NTI:
-
Normalised thermal index
References
Aries AE, Harris AJL, Rothery DA (2001) Remote infrared detection of the cessation of volcanic eruptions. Geophys Res Lett 28(9):1803–1806
Bultitude RJ (1976) Eruptive history of Bagana Volcano, Papua New Guinea, between 1882 and 1975, In: Johnson RW (ed) Volcanism in Australasia. Elsevier, New York, pp 317–336
Carn S (2000) The Lamongan volcanic field, East Java, Indonesia: physical volcanology, historic activity and hazards. J Volcanol Geotherm Res 95:81–108
Carn S, Oppenheimer C (2000) Remote monitoring of Indonesian volcanoes using satellite data from the Internet. Int J Remote Sens 21(5):873–910
Cook J (1999) In: P Edwards (ed) The journals of Captain Cook. Penguin Classics, New York, pp 379–389
Flynn LP, Wright R, Garbeil H, Harris AJL, Pilger E (2002) A global thermal alert system using MODIS: initial results from 2000–2001. Adv Environ Monit Model 1(3):37–69 (http://www.kcl.ac.uk/kis/schools/hums/geog/advemm/vol1no3.html)
Gaonac’h H, Lovejoy S, Schertzer D (2003) Resolution dependence of infrared imagery of active thermal features at Kilauea Volcano. Int J Remote Sens 24(11):2323–2344
GVN (1985a) Tinakula. Bull Global Volcanism Network 10(6):12
GVN (1985b) Lamongan. Bull Global Volcanism Network 10(10):11–12
GVN (1991) Arjuno-Welirang. Bull Global Volcanism Network 16(8):7
GVN (1994) Rabaul. Bull Global Volcanism Network 19(8):2–6
GVN (1995) Bagana. Bull Global Volcanism Network 20(8):9–10
GVN (1999) Yasur. Bull Global Volcanism Network 24(4):8–9
GVN (2000) Langila. Bull Global Volcanism Network 25(9):5
GVN (2001a) Rabaul. Bull Global Volcanism Network 26(6):7–8
GVN (2001b) Rabaul. Bull Global Volcanism Network 26(10):6
GVN (2001c) Ulawun. Bull Global Volcanism Network 26(6):5–7
GVN (2001d) Lopevi. Bull Global Volcanism Network 26(8):2–4
GVN (2001e) Ambrym. Bull Global Volcanism Network 26(2):4–5
GVN (2001f) Ijen. Bull Global Volcanism Network 26(9):5–6
GVN (2001g) Ijen. Bull Global Volcanism Network 26(12):9
GVN (2001h) Merapi. Bull Global Volcanism Network 26(1):2–3
GVN (2001i) Merapi. Bull Global Volcanism Network 26(7):9–10
GVN (2001j) Merapi. Bull Global Volcanism Network 26(10):4–6
GVN (2001k) Krakatau. Bull Global Volcanism Network 26(9):5
GVN (2002a) Pago. Bull Global Volcanism Network 27(7):5–6
GVN (2002b) Pago. Bull Global Volcanism Network 27(8):2–3
GVN (2002c) Rabaul. Bull Global Volcanism Network 27(11):7–8
GVN (2002d) Manam. Bull Global Volcanism Network 27(5):7
GVN (2002e) Ulawun. Bull Global Volcanism Network 27(8):3–4
GVN (2002f) Ambrym. Bull Global Volcanism Network 27(12):2–4
GVN (2002g) Ijen. Bull Global Volcanism Network 27(4):10
GVN (2002h) Ijen. Bull Global Volcanism Network 27(8):12–13
GVN (2002i) Ijen. Bull Global Volcanism Network 27(11):9
GVN (2002j) Semeru. Bull Global Volcanism Network 27(6):2
GVN (2002k) Merapi. Bull Global Volcanism Network 27(6):2–3
GVN (2002l) Merapi. Bull Global Volcanism Network 27(9):8
GVN (2003a) MODIS Thermal Alerts. Bull Global Volcanism Network 28(1):2–26
GVN (2003b) Pago. Bull Global Volcanism Network 28(1):13–14
GVN (2003c) Manam. Bull Global Volcanism Network 28(1):15–16
GVN (2003d) Yasur. Bull Global Volcanism Network 28(1):6–9
GVN (2003e) Bagana. Bull Global Volcanism Network 28(1):9–10
GVN (2003f) Langila. Bull Global Volcanism Network 28(1):14
GVN (2003g) Nyamuragira. Bull Global Volcanism Network 28(1):17–18
GVN (2003h) Stromboli. Bull Global Volcanism Network 28(5):15–16
GVN (2003i) Nyiragongo. Bull Global Volcanism Network 28(5):16–21
Harris AJL, Butterworth AL, Carlton RW, Downey I Miller P Navarro P Rothery DA (1997) Low-cost volcano surveillance from space: case studies from Etna, Krafla, Cerro Negro, Fogo, Lascar and Erebus. Bull Volcanol 59:49–64
Harris AJL, Murray JB, Aries SE, Davies MA, Flynn LP, Wooster MJ, Wright R Rothery DA (2000) Effusion rate trends at Etna and Krafla and their implications for eruptive mechanisms. J Volcanol Geotherm Res 102:237–269
Hendon HH (2003) Indonesian rainfall variability: impacts of ENSO and local air-sea interaction. J Climate 16(11):1775–1790
Justice CO, Giglio L, Korontzi S, Owen J, Morisette JT, Roy D, Descloitres J, Alleaume S, Pertitcolin F, Kaufman Y (2002) The MODIS fire products. Remote Sens Environ 83:244–262
Kirono DGC, Tapper NJ, McBride JL (1999) Documenting Indonesian rainfall in the 1997/1998 El Nino event. Phys Geogr 20:422–435
Kuno H (1962) Japan, Taiwan and Marianas. Catalog of active volcanoes of the world. Rome, IAVCEI, 11:1–332
Palfreyman W, Cooke RJS (1976) Eruptive history of Manam volcano, Papua New Guinea. In: Johnson RW (ed) Volcanism in Australasia, Elsevier, New York, pp 117–128
Robin C, Eissen J-P, Monzier M (1993) Giant tuff cone and 12-km-wide associated caldera at Ambrym volcano (Vanuatu, New Hebrides arc). J Volcanol Geotherm Res 55:225–238
Rothery DA, Thorne MT, Flynn LP (2003) MODIS thermal alerts in Britain and the North Sea during the first half of 2001. Int J Remote Sens 24:817–826
Siswowidjoyo S, Suryo I, Yokoyama I (1995) Magma eruption rates of Merapi volcano, Central Java, Indonesia during one century (1980–1992). Bull Volcanol 57:111–116 DOI: 10.1007/s004450050082
Williams SN (1995) Erupting neighbors—at last. Science 267:340–341
Wooster MJ, Strub N (2002) Study of the 1997 Borneo fires: Quantitative analysis using global area coverage (GAC) satellite data. Global Biochem Cycles 16 DOI 10.1029/2000GB001357
Wright R, Blake S, Harris AJL, Rothery DA (2001) A simple explanation for the space-based calculation of lava eruption rates. Earth Planet Sci Lett 192:223–233
Wright R, Flynn L (2004) Space-based estimate of the volcanic heat flux into the atmosphere during 2001 and 2002. Geology 32:189–192
Wright R, Flynn L, Garbeil H, Harris A, Pilger E (2002) Automated volcanic eruption detection using MODIS. Remote Sens Environ 82:135–155
Wright R, Flynn L, Garbeil H, Harris A, Pilger E (2004) MODVOLC: near-real-time thermal monitoring of global volcanism. J Volcanol Geotherm Res 135:29–49
Acknowledgements
Diego Coppola’s work was funded by the European Volcano Dynamics Research Training Network. MODIS data were available courtesy of the HIGP MODIS thermal alert team, members of which, notably Rob Wright, were very helpful in answering queries about geolocation and the daytime MODVOLC algorithm. We thank Dahli Ahmad and Rudy Dalimin for advice on the nature of some of the Javanese false alarms, Martin Wooster and Athanassios Zoumas for advice on fires and rainfall in Indonesia generally, Takayuki Kaneko for confirming the ongoing activity at Suwanose-Jima, and Matt Patrick and Rob Wright for comments on a draft of this paper. Formal reviews by David Pyle, Bill Rose, Helne Gaonac’h and Lois Wardell helped us to refine this paper into its current form
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Appendix: Transfer of MODVOLC data from Web site to spreadsheets and further processing
Appendix: Transfer of MODVOLC data from Web site to spreadsheets and further processing
We extracted MODVOLC data for each target volcano from the MODIS Web site (http://modis.higp.hawaii.edu/). By using the option Summarize by month and then downloading the related Text alert file (.txt format) we obtained the data for one entire month are displayed in rows. Each row contains the information for a single alert pixel. The information consists of the time of the satellite’s overpass, the latitude and longitude of the centre of the alert-pixel, the detected radiance in five MODIS channels, the satellite zenith angle and azimuth relative to the alert-pixel cent, the solar zenith angle at the alert-pixel centre, and the value of the alert ratio.
By saving the Text alert file in an Excel spreadsheet we were able to order and analyze the data by column. Sorting by latitude and longitude in turn made it convenient for us to delete all the alert-pixels falling beyond the area of interest (usually a 10-km box around the summit). We then added each month’s spatially filtered data to a master spreadsheet for the volcano, containing all that volcano’s alerts for the entire reporting period. From this, we generated three different worksheets: one for analysis of the NTI or alert ratio (ratio); one for the number of alert pixels (n_alert); and one for the total 4.0-µm spectral radiance (radiance). The time-series graphs presented in this paper were generated from these.
In the case of daytime data, the 4.0-µm thermal signal is always contaminated by reflected sunlight, so we applied the same empirical correction used by the MODIS team to generate daytime NTI (R. Wright 2003, personal communication). We identified as daytime all those data acquisitions for which the solar zenith angle was <90° and for these we made a solar correction to the MODIS band 21 (4.0 µm) spectral radiance by subtracting from it 4.26% of the MODIS band 6 (1.6 µm) spectral radiance.
In the ratio worksheet, we ordered the data by date and time (for this we generated an extra data column, called date-time, containing year, month, day, hour, and minute of the satellite’s overpass) and we plotted the value of alert ratio versus date-time in a graph covering all the monitored period.
To analyse the number of alert pixels and the total spectral radiance recorded by each satellite overpass, it was necessary to distinguish groups of pixels sharing the same date and time (date would be insufficient at high latitudes, where there may be data from several overpasses on a single date). We achieved this using a function in Excel called “subtotals” (Menu Bar – Data). For each change in the column date-time, we used the formula “count the cells with the same value in the date-time column” (to count the number of pixels) and “sum the value of 4.0-µm radiance of the cells with the same value in date-time column” (to calculate the total spectral radiance at 4.0 µm). We thus obtained (for each satellite overpass) the number of alert-pixels and the total (solar-corrected) spectral radiance at 4.0 m. We used the latitudes and longitudes of alert-pixel centres in the spreadsheets to plot the spatial distribution of the alerts, which we used as overlays on maps of each volcano.
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Rothery, D., Coppola, D. & Saunders, C. Analysis of volcanic activity patterns using MODIS thermal alerts. Bull Volcanol 67, 539–556 (2005). https://doi.org/10.1007/s00445-004-0393-3
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DOI: https://doi.org/10.1007/s00445-004-0393-3