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Explosive volcanic eruptions can disperse significant quantities of ash over large areas with consequences for human health, air traffic security, and critical infrastructure. Consequently, the detection and monitoring of volcanic ash clouds is of crucial importance to enhance the safety of human settlements and air traffic. The latest generation of high resolution satellite sensors (e.g. EUMETSAT MSG Spinning Enhanced Visible and InfraRed Imager) provide radiometric estimates to observe and to monitor volcanic clouds at global scale in an efficient and timely manner. However, the satellite data volume is too large to be manually processed and analyzed on a daily basis and global scale. Deep learning (DL), a fastest-growing technique of artificial intelligence in remote sensing data analysis applications, has an excellent ability to learn massive, high-dimensional image features and have been widely studied and applied in classification, recognition, and detection tasks involving satellite images. Here, we evaluate the ability of deep Convolutional Neural Networks (CNNs), a DL class, to detect and track the dispersion of volcanic ash clouds into the atmosphere, exploiting a variety of spatiotemporal information mainly coming from satellite sensors. We train some popular deep CNN models through transfer learning. We show that even when using transfer learning the size of the dataset plays a key role in the performance of the models, with those trained on the smaller datasets showing a strong tendency to overfit. These models were applied to the paroxysmal explosive events that occurred at Mt. Etna between 2020 and 2022., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

RED SEED stands for Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters, and combines stakeholders from the remote sensing, modelling and response communities with experience in tracking volcanic effusive events. The group first met during a three day-long workshop held in Clermont Ferrand (France) between 28 and 30 May 2013. During each day, presentations were given reviewing the state of the art in terms of (a) volcano hot spot detection and parameterization, (b) operational satellite-based hot spot detection systems, (c) lava flow modelling and (d) response protocols during effusive crises. At the end of each presentation set, the four groups retreated to discuss and report on requirements for a truly integrated and operational response that satisfactorily combines remote sensors, modellers and responders during an effusive crisis. The results of collating the final reports, and follow-up discussions that have been on-going since the workshop, are given here. We can reduce our discussions to four main findings. (1) Hot spot detection tools are operational and capable of providing effusive eruption onset notice within 15 min. (2) Spectral radiance metrics can also be provided with high degrees of confidence. However, if we are to achieve a truly global system, more local receiving stations need to be installed with hot spot detection and data processing modules running on-site and in real time. (3) Models are operational, but need real-time input of reliable time-averaged discharge rate data and regular updates of digital elevation models if they are to be effective; the latter can be provided by the radar/photogrammetry community. (4) Information needs to be provided in an agreed and standard format following an ensemble approach and using models that have been validated and recognized as trustworthy by the responding authorities. All of this requires a sophisticated and centralized data collection, distribution and reporting hub that is based on a philosophy of joint ownership and mutual trust. While the next chapter carries out an exercise to explore the viability of the last point, the detailed recommendations behind these findings are detailed here.

We present new insights into the short- and long-term thermal activity of the Nyiragongo lava lake by ground-based and satellite infrared thermal imagery recorded in the first half of 2012. This is the very first time in which FLIR camera and SEVIRI data have been compared at this volcano. Maximum temperatures recorded at the molten lava were of ~1180 K, whereas the lake skin remained always below ~734 K in areas far from the upwelling zone and below ~843 K in those proximal to the source region. Ground-based imagery yielded mean radiative power values between ~0.80 and 1.10 GW. Consistently, satellite observations showed similar mean values of 1.10 GW. Overall the thermal activity of the lava lake was quite variable along the three days of field measurements at both daily and intradaily scale. SEVIRI radiative power values retrieved for the January-June 2012 period revealed fluctuations within the same variability range suggesting that no significant changes of the lava lake area had occurred over the six months. Comparison with previous radiative power estimates showed that our data well agree with the general increasing trend recorded since the reappearance of the lava lake after the last flank eruption in 2002. Key Points Validation of satellite data by ground-based thermal imagery Characterisation of the Nyiragongo lava lake surface activity in March 2012 Comparison between the March 2012 results and previous observations ©2013. American Geophysical Union. All Rights Reserved.

The 1989 eruption of Mt. Etna was characterized by the opening of two fracture systems spread from the South-East summit crater base with approximate North-East and South-East trends, respectively. The northern fracture system fed a lateral eruption, whereas the fracture system of the southern side did not seem to take up magma, even though it shows elements of compatibility with a shallow dyke intrusion. With the aim of explaining whether the southern system was really connected to a dyke, during October 1989 a self-potential profile 1320 m long and a magnetic profile 2230 m long were realized at the altitude of 1650 m, orthogonally to the direction of the above mentioned system. The measurements, executed many times until September 1991 for the magnetism and April 1993 for the self-potential, allowed us to reveal marked anomalies tied to phenomena of rock fracturing and fluid invasion for the self-potential anomaly, and to progressive magnetization of cooling dyke for the magnetic anomaly. The magnetic anomaly indicates that the dyke would appear to be c.a. 4 m thick and to culminate ca. 400 m under the topographic surface. Accordingly, the self-potential anomaly suggests that positive charge would accumulate inside a newly fractured zone above the dyke ranging from ca. 150 m to ca. 400 m below the ground level, while the negative charge accumulations appear at both sides of the dyke at a lesser that (from less than 100 m to about 250 m at most) and separated from the positive nucleus by a horizontal spacing of some hundred meters.