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Article Dans Une Revue Remote Sensing Année : 2022

VIGIA: A Thermal and Visible Imagery System to Track Volcanic Explosions

Andrew J.L. Harris
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Karim Kelfoun
Carlos Macías
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Silvana Hidalgo
Jorge Córdova
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Jean Battaglia
Jessica Mejía
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Santiago Arrais
Cristina Ramos

Résumé

The monitoring of the frequency, intensity/magnitude and dynamics of explosive events at volcanoes in a state of unrest is key to surveying and forecasting their activity. Thermal and visual video observations of eruptive phenomena, and their correlation with data from deformation and seismic networks, are often limited by technical constraints including lack of time synchronisation, data volumes and power consumption. Several solutions are currently available and here we present an instrument designed for the permanent and real-time observation of volcanic explosive events in the visible and thermal infrared wavelengths, the output of which can be fully synchronised with ancillary monitoring data. Our system (VIGIA: visual and infrared ground-based imagery analyser) follows an edge computing approach whereby information is processed on-site, and periodic reports are sent to the local observatory and the system “decides” when to acquire high-temporal resolution data so as to capture key explosive events. As a permanent installation, VIGIA enables the continuous, long-term and time-synchronised observation of volcanic activity while reducing power consumption and data volumes. We suggest that VIGIA-style instruments could provide useful scientific and monitoring information, and provide here the key details of the components, assembly, and code so that observatories can replicate the system and build their own VIGIA at minimal cost. We use the Reventador volcano, in Ecuador, as a case study to present the capabilities of the instrument.
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hal-03874851 , version 1 (28-11-2022)

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Freddy Vásconez, Yves Moussallam, Andrew J.L. Harris, Thierry Latchimy, Karim Kelfoun, et al.. VIGIA: A Thermal and Visible Imagery System to Track Volcanic Explosions. Remote Sensing, 2022, 14 (14), pp.3355. ⟨10.3390/rs14143355⟩. ⟨hal-03874851⟩
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