Ernst, Gerald

HARRIS, A

Jacobs, Patric

Kervyn de Meerendre, Matthieu

MBEDE, E

English

Ghent University Academic Bibliography

Geophysical Research Abstracts, Vol. 8, 03887, 2006SRef-ID: 1607-7962/gra/EGU06-A-03887© European Geosciences Union 2006MODIS thermal remote sensing monitoring oflow-intensity anomalies at volcanoes: Oldoinyo Lengai(Tanzania) and the MODLEN algorithmM. Kervyn (1), A.J.L. Harris (2), E. Mbede (3), P. Jacobs (1), G.G.J. Ernst (1)(1) Mercator & Ortelius Research Center for Eruption Dynamics, Geology Dept, GhentUniversity, Belgium, (2) HIGP/SOEST, University of Hawaii, USA, (3) Department ofGeology, University of Daar-es-Salaam, Tanzania (Matthieu.KervynDeMeerendre@UGent.be)Active and potentially hazardous volcanoes in East Africa (Tanzania, Kenya, Ethiopia)are not currently monitored on a regular basis by local scientists or scientists any-where. Oldoinyo Lengai, one of the most active volcanoes, has been almost con-tinuously emitting fluid natro-carbonatite lava in its summit crater since 1983. Ac-tivity, generally confined to the summit crater, ranges from lava pool degassing torelatively intense lava outpouring (∼ 5-10 m3.s−1) and <30m-high lava fountains.Historical eruptions’ accounts illustrate that Oldoinyo Lengai also repeatedly displaysmuch more explosive – violent strombolian or sub-plinian style - eruptions of sili-cate magma. Monitoring is needed to try and anticipate the transition to this morehazardous eruption style and gain insights into the controls on eruption intensity atOldoinyo Lengai. A semi-automated algorithm (MODLEN) using MODIS night-timesatellite images to record thermal activity and detect abnormally high-intensity erup-tive events is presented. MODLEN builds upon the MODVOLC algorithm, devel-oped by the University of Hawaii as a fully-automated global-coverage hot spot de-tection system. MODLEN is specifically adapted to the low-temperature and small-scale eruptive activity at Oldoinyo Lengai. Calibrated and validated against field data,MODLEN is able to detect all events described as abnormally intense. Baseline datarecords allow assessing the influence of limitations such as partial or total cloud cov-erage or data acquisition gaps. A 15-month-long data series is presented and analysed.Perspectives for analysis of the temporal distribution of eruptive events on longer timeseries are highlighted. Low-cost thermal IR remote sensing monitoring is an essentialcomponent of the needed monitoring programme at several volcanoes in East Africa.Perspectives for near-real time routine implementation at Oldoinyo Lengai and othervolcanoes of East Africa are also discussed.

MODIS thermal remote sensing monitoring of low-intensity anomalies at volcanoes: Oldoynio Lengai (Tanzania) and the MODLEN algorithm

https://biblio.ugent.be/publication/347387/file/568127

MODIS thermal remote sensing monitoring of low-intensity anomalies at volcanoes: Oldoynio Lengai (Tanzania) and the MODLEN algorithm

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Ghent University Academic Bibliography