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Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
Published on: August 7, 2017
Volcanic SO2 total mass dataset on Mt. Etna (Italy) from 2018 to 2025 using sentinel-5P TROPOMI
Maddalena Dozzo1,2, Alessandro Aiuppa2, Giuseppe Bilotta1
1Istituto Nazionale di Geofisica e Vulcanologia, OE 95125 Catania, CT, Italy.
None:
Sulfur dioxide (SO₂) is released by the magma degassing in the shallow crust, constituting a key indicator of magma ascent rates in the feeding conduit, as well as providing information on the style and the intensity of eruptive activity. Continuous monitoring of this gas is important to understand volcanic processes and to contribute to hazard assessment. The dataset presented here provides a comprehensive time series of SO₂ total mass from Mount Etna (Sicily, Italy), covering the period from 2018 to 2025. The data have been obtained from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which has been operational since 2018, delivering atmospheric column measurements of sulfur dioxide and other gases at unprecedented spatial resolution and daily revisit time. Volcanic SO₂ plumes were automatically identified through a two-step procedure: firstly, the Simple Non-Iterative Clustering (SNIC) segmentation method was applied, which is an object-based image analysis technique and secondly, K-means unsupervised clustering was used on the segmented imagery to further improve cloud detection. The algorithm has been implemented in the open-source Google Earth Engine platform, enabling efficient processing of the TROPOMI imagery collection, to which quality control filters are already applied. This methodological framework supports the generation of SO₂ total mass time series with reduced delay and improved calculation time, thus providing a valuable tool for rapid and reliable monitoring of volcanic emissions and for enhancing volcanic hazard assessment capabilities.
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