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Hot-spot detection and characterization of strombolian activity from MODIS infrared data

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Identifying and characterizing strombolian activity from space is a challenging task for satellite-based infrared systems. Stromboli volcano is a natural laboratory that offers a unique opportunity for refining thermal remote-sensing applications that involve transient phenomena and small to moderate hot-spots. A new simple and fast algorithm gave us the opportunity to revisit the MODIS-derived thermal output at Stromboli volcano over the last 13 years. The new algorithm includes both night-time and daytime data and shows high performance with the detection of small-amplitude thermal anomalies (<1 MW), as well as a low occurrence of false alerts (<4%). Here, we show that the statistical distribution of volcanic radiative power (VRP; in Watts) is consistent with the detection of variable activity regimes that we subdivided into five levels of thermal activity: Very Low (VRP < 1 MW), Low (1 MW < VRP < 10 MW), Moderate (10 MW < VRP < 100 MW), High (100 MW < VRP < 1000 MW), and Very High (VRP > 1000 MW). The ‘Low’ and ‘Moderate’ thermal levels are associated with strombolian activity and reflect fluctuations of the magma level within the conduit feeding the activity at the surface. The ‘High’ level of thermal output represents the bulk thermal emissions during periods of effusive activity. The highest level (‘Very High’) was reached only during the onset of flank eruptions (28 December 2002 and 27 February 2007). We found that the retrieved thermal regimes are in general agreement with the explosive levels evaluated at Stromboli since 2005, and their correlation has been shown to be dependent on the observed activity (i.e. eruption onset, lateral flank effusion, summit overflows, strombolian activity). Our results suggest that remotely sensed thermal data provide a reliable tool for monitoring volcanic activity at Stromboli volcano.
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Document Type: Research Article

Affiliations: 1: Dipartimento di Scienze della Terra, Università di Torino, 10125, Torino, Italy 2: Dipartimento di Scienze della Terra e del Mare, Università di Palermo, 90123, Palermo, Italy 3: Dipartimento di Scienze della Terra, Università di Firenze, Firenze, Italy

Publication date: May 3, 2014

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