Abstract
Fast and accurate quantification of gas fluxes emitted by volcanoes is essential for the risk mitigation of explosive eruption, and for the fundamental understanding of shallow eruptive processes. Sulphur dioxide (SO2), in particular, is a reliable indicator to predict upcoming eruptions, and its systemic characterization allows the rapid assessment of sudden changes in eruptive dynamics. In this regard, infrared (IR) hyperspectral imaging is a promising new technology for accurately measure SO2 fluxes day and night at a frame rate down to 1 image per second. The thermal infrared region is not very sensitive to particle scattering, which is an asset for the study of volcanic plume. A ground based infrared hyperspectral imager was deployed during the IMAGETNA campaign in 2015 and provided high spectral resolution images of the Mount Etna (Sicily, Italy) plume from the North East Crater (NEC), mainly. The LongWave InfraRed (LWIR) hyperspectral imager, hereafter name Hyper-Cam, ranges between 850–1300 cm−1 (7.7–11.8 µm). The LATMOS (Laboratoire Atmosphères Milieux Observations Spatiales) Atmospheric Retrieval Algorithm (LARA), which is used to retrieve the slant column densities (SCD) of SO2, is a robust and a complete radiative transfer model, well adapted to the inversion of ground-based remote measurements. However, the calculation time to process the raw data and retrieve the infrared spectra, which is about seven days for the retrieval of one image of SO2 SCD, remains too high to infer near real-time (NRT) SO2 emission fluxes. A spectral image classification methodology based on two parameters extracting spectral features in the O3 and SO2 emission bands was developed to create a library. The relevance is evaluated in detail through tests. From data acquisition to the generation of SO2 SCD images, this method requires only ~40 s per image, which opens the possibility to infer NRT estimation of SO2 emission fluxes from IR hyperspectral imager measurements.
Highlights
More than 500 million people live within the potential exposure range of a volcano [1]
We present a spectral image classification methodology for infrared hyperspectral images from Mount Etna volcanic plume
The IMAGETNA campaign was held from 21–26 June 2015 from the Pizzi De Neri Volcano observatory on the North side of Mount Etna at 2850 m altitude and at ~2 km from the plume
Summary
More than 500 million people live within the potential exposure range of a volcano [1]. Monitoring volcanoes is essential and involves different types of measurements, such as volcanic degassing, seismicity, and ground deformation detection [2]. Measurements of volcanic degassing have been one of the most widely used methods in volcanic monitoring networks for more than 40 years. In addition to the risks induced by volcanic eruptions, monitoring the volcanoes degassing emissions in the atmosphere is important for an environmental impact and a hazardous effect on human health. After H2O and CO2, sulfur dioxide is the main volcanic gas emitted by volcanoes. The impact of SO2 emission on atmospheric chemistry and the estimation of the global budget of SO2 in the atmosphere induced by volcanoes are part of climate and environmental monitoring as well as public health prevention [11]. The oxidation of SO2 leads to the formation of sulfur aerosols responsible for acid rain [12], problems on vegetation growth close to volcanoes, and cause asthma or respiratory problems to humans [13,14]
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