Synthesizing multi-sensor, multi-satellite, multi-decadal datasets for global volcano monitoring

Abstract

ReuseThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can't change the article in any way or use it commercially. More information and the full terms of the licence here: https://creativecommons.org/licenses/ TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. AbstractOwing to practical limitations less than half of Earth's 1400 subaerial volcanoes have no ground monitoring and few are monitored consistently. Earth-observing satellite missions provide global and frequent measurements of volcanic activity that are closing these gaps in coverage. We compare databases of global, satellite-detections of ground deformation (1992-2016), SO 2 emissions , and thermal features (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) that together include 306 volcanoes. Each database has limitations in terms of spatial and temporal resolution but each technique contributed 45-86 unique detections of activity that were not detected by other techniques.Integration of these three databases shows that satellites detected ~10 2 volcanic activities per year before the year 2000 and ~10 3 activities per year after the year 2000. We find that most of the 54 erupting volcanoes without satellite-detections are associated with low volcano explosivity index eruptions and note that many of these eruptions (71%, 97/135) occurred in the earliest decades of remote sensing (pre-2000) when detection thresholds were high. From 1978-2016 we conduct a preliminary analysis of the timing between the onset of satellite-detections of deformation (N=154 episodes, N=71 volcanoes), thermal features (N=16544 episodes, N=99 volcanoes), and SO 2 emissions (N=1495 episodes, N=116 volcanoes) to eruption start dates. We analyze these data in two ways: first, including all satellite-detected volcanic activities associated ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P Twith an eruption; and second, by considering only the first satellite-detected activity related to eruption. In both scenarios, we find that deformation is dominantly pre-eruptive (47% and 57%) whereas available databases of thermal features and SO 2 emissions utilizing mainly lowresolution sensors are dominantly co-eruptive (88% and 76% for thermal features, 97% and 96% for SO 2 emissions).

Thermal Remote Sensing for Global Volcano Monitoring: Experiences From the MIROVA System

“…The appearance of thermal anomalies before an eruption is often considered as an important precursor and a clear symptom of volcanic unrest (Reath et al, 2016). A recent review (Furtney et al, 2018) suggests that about 19% of major eruptions are anticipated by thermal precursors detected by satellites, although the mere presence of thermal activity to a volcano does not necessarily constitute a change from its background level.…”

“…This is possibly due to the sensitivity of this type of systems that fail to detect small, low-intensity thermal anomalies. Indeed, the percentage of thermal unrest rises considerably if thermal data with higher spatial resolution are used as suggested by Furtney et al (2018) and Reath et al (2019a). On the other hand, it cannot be excluded that the appearance of thermal precursors and the explosivity index of the subsequent eruption are somehow related to the degree of openness of the shallow magmatic system.…”

“…The acquisition of satellite images and data for volcanological applications is continuously and rapidly growing (Ramsey and Harris, 2013;Furtney et al, 2018;Pritchard et al, unpublished), so that big data analysis techniques (i.e., artificial intelligence and machine learning) are progressively used for research purposes and for monitoring activity (Piscini and Lombardo, 2014;Anantrasirichai et al, 2018;Valade et al, 2019). In particular, with the advent of the new millenium, and with the development of internet, the dissemination and sharing of satellite data/products can be considered a pillar of open science in volcanology, also thanks to the growing availability of open data by space agencies (Delgado et al, 2019).…”

“…Recent scientific pilot projects, as the European Volcano Observatory Space Services, EVOSS (Tait and Ferrucci, 2013) and the Committee on Earth Observation Satellite (CEOS) Volcano Pilot Project (Delgado et al, 2019), demonstrated the potential of integrating these space-based data for forecasting eruptions (Furtney et al, 2018), stressing the need to develop a volcanic monitoring system to support volcano observatories (Pritchard et al, unpublished). The Monitoring Unrest From Space (MOUNTS) project 1 , although in an embryonic stage, can be considered a first prototype of such integrated system, since it includes near-real time multi-parametric analysis (UV, IR and microwaves) derived from the ESA Sentinel constellation, at several volcanoes (Valade et al, 2019).…”

Explosive eruptions with little warning: Experimental petrology and geodetic observations from the 2014 eruption of Kelud, Indonesia

“…Bodies of magma can build up gradually by a process of successive intrusions (e.g., Santorini, Parks et al, 2012;Pyle, 2017) or by post-eruption recharge (e.g., Okmok, Lu & Dzurisin, 2014), and reside in the crust for months to decades before eruption. On a multi-decadal time scale, detection of deformation is a good statistical predictor for an eruption taking place over the same period of observation (J Biggs et al, 2014;Furtney et al, 2018). However, eruptions have also taken place at volcanoes where a lack of deformation has been measured (Rasmussen et al, 2018).…”