Abstract Understanding the behaviour of fluids in hydrothermal systems is a key factor in volcano monitoring. Measuring gas emissions in volcanic areas is strategic for detecting and interpreting precursory signals of variations in volcanic activity. The role of radon as a potential precursor of earthquakes has been extensively debated. However, radon anomalies appear to be better suited to forecast eruptive episodes as we know the loci of volcanic eruptions and we can follow the evolution of volcanic activity. Radon mapping is an effective tool in assessing diffuse and concentrated degassing at the surface. We hereby summarize the in-soil radon emissions collected worldwide and further discuss a collection of data on our key targets. These are closed-conduit and open-conduit volcanoes: Vesuvius (Italy) and La Soufrière (Guadeloupe, Lesser Antilles), Stromboli (Italy) and Villarrica (Chile), respectively. In all the above volcanoes, faults and fracture systems control radon degassing. Automatic and real-time measurements help us to detect major changes in volcanic activity. We present and discuss the radon time series associated with the last effusive eruption at Stromboli. Spectral analyses reveal diurnal and semi-diurnal cycles being probably modulated by atmospheric variations. Multiple linear regression (MLR) analyses have been performed by filtering the radon signals from the effects of local environmental parameters. The residuals do not show particular variations or precursory peaks as the gases have been released from this open-conduit volcano before the onset of the effusive phase (7 August 2014). It is finally emphasized that radon is not the sole precursor, and we should also rely on other geochemical and geophysical parameters. In this perspective, we propose a methodological procedure that can contribute to improving volcano surveillance in an attempt to mitigate volcanic risk.

Abstract During the period 28 February 2000–31 December 2013, the MODVOLC system ( http://modis.higp.hawaii.edu ) autonomously analysed almost 9 trillion (i.e. 9×10 12 ) pixels contained within almost 3 million MODIS images, searching for evidence of high-temperature thermal signatures associated with volcanic eruptions. Thermal unrest, mainly associated with active lava, be it in the form of flows, domes, lakes or confined to vents, was detected at 93 volcanoes during this period of time. The first part of this paper describes the physical basis and operational implementation of the MODVOLC algorithm. The second part presents data to detail the nature of the thermal emission from these 93 volcanoes over the past 14 years.

Abstract The observation of volcanic thermal activity from space dates back to the late 1960s. Several methods have been proposed to improve detection and monitoring capabilities of thermal volcanic features, and to characterize them to improve our understanding of volcanic processes, as well as to inform operational decisions. In this paper we review the RST VOLC algorithm, which has been designed and implemented for automated detection and near-real-time monitoring of volcanic hotspots. The algorithm is based on the general Robust Satellite Techniques (RST) approach, representing an original strategy for satellite data analysis in the space–time domain. It has proven to be a useful tool for investigating volcanoes worldwide, by means of different satellite sensors, onboard polar orbiting and geostationary platforms. The RST VOLC rationale, its requirements and main operational capabilities are described here, together with the advantages of the tool and the known limitations. Results achieved through the study of two past eruptive events are shown, together with some recent examples demonstrating the near-continuous monitoring capability offered by RST VOLC . A summary is also made of the type products that the method is able to generate and provide. Lastly, the future perspectives, in terms of its possible implementation on the new generation of satellite systems, are briefly discussed.

Abstract The AVHotRR routine has been in operation since 2006 to process satellite data for monitoring active volcanoes in the Mediterranean area. Although originally developed to work with advanced very high-resolution radiometer (AVHRR) data, AVHotRR has been developed over the years to adapt to other sensors. In this work we present an improved version of the algorithm for hot-spot detection and effusion rate estimate. The underlying principles upon which the algorithm is based are discussed, focusing on the enhancements. The currently implemented version makes it possible to integrate results from different datasets in order to better constrain the detection of volcanic hot spots. In particular, the high temporal resolution of the SEVIRI instrument aboard MSG is key to reducing false positives in AVHRR and moderate resolution imaging spectroradiometer MODIS images. We propose here a new detection method based on the wavelet transform of SEVIRI data. Results from the application of AVHotRR to a dataset of AVHRR and SEVIRI images from Mt Etna, Italy, are presented and discussed with reference to the advantages and limitations of the algorithm.

Abstract Many volcanoes around the world are poorly monitored and new eruptions increase the need for rapid ground-based monitoring, which is not always available in a timely manner. Initial observations therefore are commonly provided by orbital remote sensing instruments at different temporal, spatial and wavelength scales. Even at well-monitored volcanoes, satellite data still play an important role. The ASTER (Advanced Spaceborne Thermal Emission Radiometer) orbital sensor provides moderately high spatial resolution images in multiple wavelength regions; however, because ASTER is a scheduled instrument, the data are not acquired over specific targets every orbit. Therefore, in an attempt to improve the temporal frequency of ASTER specifically for volcano observations and to have the images integrate synergistically with high temporal resolution data, the Urgent Request Protocol (URP) system was developed in 2004. Now integrated with both the AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot monitoring programmes, the URP acquires an average of 24 volcanic datasets every month and planned improvements will allow this number to increase in the future. New URP data are sent directly to investigators responding to the ongoing eruption, and the large archive is also being used for retrospective science and operational studies for future instruments. The URP Program has been very successful over the past decade and will continue until at least 2017 or as long as the ASTER sensor is operational. Several volcanic science examples are given here that highlight the various stages of the URP development. However, not all are strictly focused on effusive eruptions. Rather, these examples were chosen to demonstrate the wide range of applications, as well as the general usefulness of the higher resolution, multispectral data of ASTER.

Abstract Developments in spaceborne Earth Observation (EO) sensor technology over the last decade, combined with well-tested physical models and multispectral data-processing techniques developed from the early 1980s, have paved the way to the global monitoring of volcanoes by sensors of metric, decametric, kilometric and multi-kilometric spatial resolution. Such variable geometries provide for revisit intervals ranging from about monthly – at high-spatial resolution in Low-Earth Orbit – to less than 5 min – at low-spatial resolution, from geostationary platforms. There are currently about 20 spacecrafts available for carrying out 24/7 quantitative observations of volcanic unrest, at all resolutions and as close as possible to real-time. We show some successful examples of synergetic EO on volcanoes on three continents from 10 different payloads, automatically processed with three, end-to-end unsupervised procedures, on eight major eruptions and a lava lake between 2006 and 2014.

Abstract We describe a new volcanic hotspot detection system, named Middle InfraRed Observation of Volcanic Activity (MIROVA), based on the analysis of infrared data acquired by the Moderate Resolution Imaging Spectroradiometer sensor (MODIS). MIROVA uses the middle infrared radiation (MIR), measured by MODIS, in order to detect and measure the heat radiation deriving from volcanic activity. The algorithm combines spectral and spatial principles, allowing the detection of heat sources from 1 megawatt (MW) to more than 10 gigawatt (GW). This provides a unique opportunity to: (i) recognize small-scale variations in thermal output that may precede the onset of effusive activity; (ii) track the advance of large lava flows; (iii) estimate lava discharge rates; (iv) identify distinct effusive trends; and, lastly, (v) follow the cooling process of voluminous lava bodies for several months. Here we show the results obtained from data sets spanning 14 years recorded at the Stromboli and Mt Etna volcanoes, Italy, and we investigate the above aspects at these two persistently active volcanoes. Finally, we describe how the algorithm has been implemented within an operational near-real-time processing chain that enables the MIROVA system to provide data and infrared maps within 1–4 h of the satellite overpass.

Abstract The HOTSAT multiplatform system for the analysis of infrared data from satellites provides a framework that allows the detection of volcanic hotspots and an output of their associated radiative power. This multiplatform system can operate on both Moderate Resolution Imaging Spectroradiometer and Spinning Enhanced Visible and Infrared Imager data. The new version of the system is now implemented on graphics processing units and its interface is available on the internet under restricted access conditions. Combining the estimation of time-varying discharge rates using HOTSAT with the MAGFLOW physics-based model to simulate lava flow paths resulted in the first operational system in which satellite observations drive the modelling of lava flow emplacement. This allows the timely definition of the parameters and maps essential for hazard assessment, including the propagation time of lava flows and the maximum run-out distance. The system was first used in an operational context during the paroxysmal episode at Mt Etna on 12–13 January 2011, when we produced real-time predictions of the areas likely to be inundated by lava flows while the eruption was still ongoing. This allowed key at-risk areas to be rapidly and appropriately identified.

Abstract Infrared (IR) satellite-based sensors allow the detection and quantification of volcanic hot spots. Sensors flown on geostationary satellites are particularly helpful in the early warning and continuous tracking of effusive activity. Development of operational monitoring and dissemination systems is essential to achieve the real-time ingestion and processing of IR data for a timely response during volcanic crises. HOTVOLC is a web-based satellite-data-driven monitoring system developed at the Observatoire de Physique du Globe de Clermont-Ferrand (Clermont-Ferrand), designed to achieve near-real-time monitoring of volcanic activity using on-site ingestion of geostationary satellite data (e.g. MSG-SEVIRI, MTSAT, GOES-Imager). Here we present the characteristics of the HOTVOLC system for the monitoring of effusive activity. The system comprises two acquisition stations and secure databases (i.e. mirrored archives). The detection of volcanic hot spots uses a contextual algorithm that is based on a modified form of the Normalized Thermal Index (NTI*) and VAST. Raster images and numerical data are available to open-access on a Web-GIS interface. Tests are carried out and presented here, particularly for the 12–13 January 2011 eruption of Mount Etna, to show the capability of the system to provide quantitative information such as lava volume and time-averaged discharge rate. Examples of operational application reveal the ability of the HOTVOLC system to provide timely thermal information about volcanic hot spot activity.

Abstract Effusion rate is a crucial parameter for the prediction of lava-flow advance and should be assessed in near real-time in order to better manage a volcanic crisis. Thermal remote sensing offers the most promising avenue to attain this goal. We present here a ‘dynamic’ thermal proxy based on laboratory experiments and on the physical framework of viscous gravity currents, which can be used to estimate the effusion rate from thermal remote sensing during an eruption. This proxy reproduces the first-order relationship between effusion rate measured in the field and associated powers radiated by basaltic lava flows. Laboratory experiments involving fluids with complex rheology and subject to solidification give additional insights into the dynamics of lava flows. The introduction of a time evolution of the supply rates during the experiments gives rise to a transient adjustment of the surface thermal signal that further compromises the simple proportionality between the thermal flux and the effusion rate. Based on the experimental results, we conclude that a thermal proxy can only yield a minimum and time-averaged estimate of the effusion rate.

Abstract Timely detection and quantification of lava effusion rates are crucial for volcanic hazard mitigation during effusive eruptions. Satellite-based detection methods typically exploit the exceptional radiant heat fluxes associated with lava effusion, but effusive eruptions can also emit prodigious amounts of sulphur dioxide (SO 2 ). Measuring the magnitude and temporal evolution of SO 2 emissions provides an additional means for monitoring effusive eruptions, complementing thermal monitoring. Examples of effusive eruptions detected since 1978 using ultraviolet (UV) satellite measurements of SO 2 emissions by the Total Ozone Mapping Spectrometer (TOMS), Ozone Monitoring Instrument (OMI) and Ozone Mapping and Profiler Suite (OMPS) are reviewed. During many effusive eruptions, trends in SO 2 production mimic the classic waxing–waning pattern characteristic of such events that is also seen in thermal infrared (TIR) hotspot data, suggesting a qualitative link between SO 2 emissions and lava effusion rates. An example of lava effusion rate calculation based on TOMS SO 2 measurements is presented for the 1998 eruption of Cerro Azul (Galápagos Islands), for which detailed eruption observations and independent estimates of effusion rates are available. Combining TOMS-derived SO 2 emission rates with estimates of sulphur content in Cerro Azul lavas yields lava effusion rates almost identical to independently derived values, demonstrating the utility of the technique.

Abstract FLOWGO is a one-dimensional model that tracks the thermorheological evolution of lava flowing down a channel. The model does not spread the lava but, instead, follows a control volume as it descends a line of steepest descent centred on the channel axis. The model basis is the Jeffreys equation for Newtonian flow, modified for a Bingham fluid, and a series of heat loss equations. Adjustable relationships are used to calculate cooling, crystallization and down-channel increases in viscosity and yield strength, as well as the resultant decrease in velocity. Here we provide a guide that allows FLOWGO to be set up in Excel. In doing so, we show how the model can be executed using a slope profile derived from Google™ Earth. Model simplicity and ease of source-term input from Google™ Earth means that this exercise allows (i) easy access to the model, (ii) quick, global application and (iii) use in a teaching role. Output is tested using measurements made for the 2010 eruption of Piton de la Fournaise (La Réunion Island). The model is also set up for rapid syneruptive hazard assessment at Piton de la Fournaise, as we show using the example of the response to the June 2014 eruption.

Abstract The MAGFLOW model for lava-flow simulations is based on the cellular automaton (CA) approach, and uses a physical model for the thermal and rheological evolution of the flowing lava. We discuss the potential of MAGFLOW to improve our understanding of the dynamics of lava-flow emplacement and our ability to assess lava-flow hazards. Sensitivity analysis of the input parameters controlling the evolution function of the automaton demonstrates that water content and solidus temperatures are the parameters to which MAGFLOW is most sensitive. Additional tests also indicate that temporal changes in effusion rate strongly influence the accuracy of the predictive modelling of lava-flow paths. The parallel implementation of MAGFLOW on graphic processing units (GPUs) can achieve speed-ups of two orders of magnitude relative to the corresponding serial implementation, providing a lava-flow simulation spanning several days of eruption in just a few minutes. We describe and demonstrate the operation of MAGFLOW using two case studies from Mt Etna: one is a reconstruction of the detailed chronology of the lava-flow emplacement during the 2006 flank eruption; and the other is the production of the lava-flow hazard map of the persistent eruptive activity at the summit craters.

Abstract LavaSIM is a lava -flow simulator to carry out three-dimensional (3D) analysis of solid–liquid two-phase lava flows. Heat transfer between molten lava and solidified crust into the air, water and ground is calculated using radiation equations, so we can simulate not only the lava-flow distribution but also its physical characteristics: for instance, the internal convectional structure. Lava viscosity can be treated as a function of temperature, and is associated with the percentage of crystallization. The stop condition for the lava flow is determined by calculating the minimum spreading thickness, taking into consideration the yield strength. This paper also discusses whether LavaSIM, the deterministic lava-flow simulation, can be applied to basaltic lava flows and allow lava-flow characteristics, such as inundated area, temperature distribution, crust–melt distribution, velocity and pressure field, to be quantitatively evaluated.

Abstract Hawaiian volcanoes are highly accessible and well monitored by ground instruments. Nevertheless, observational gaps remain and thermal satellite imagery has proven useful in Hawai‘i for providing synoptic views of activity during intervals between field visits. Here we describe the beginning of a thermal remote sensing programme at the US Geological Survey Hawaiian Volcano Observatory (HVO). Whereas expensive receiving stations have been traditionally required to achieve rapid downloading of satellite data, we exploit free, low-latency data sources on the internet for timely access to GOES, MODIS, ASTER and EO-1 ALI imagery. Automated scripts at the observatory download these data and provide a basic display of the images. Satellite data have been extremely useful for monitoring the ongoing lava flow activity on Kīlauea’s East Rift Zone at Pu‘u ‘Ō‘ō over the past few years. A recent lava flow, named Kahauale‘a 2, was upslope from residential subdivisions for over a year. Satellite data helped track the slow advance of the flow and contributed to hazard assessments. Ongoing improvement to thermal remote sensing at HVO incorporates automated hotspot detection, effusion rate estimation and lava flow forecasting, as has been done in Italy. These improvements should be useful for monitoring future activity on Mauna Loa.

Abstract Using two hypothetical effusive events in the Chaîne des Puys (Auvergne, France), we tested two geographical information systems (GISs) set up to allow loss assessment during an effusive crisis. The first was a local system that drew on all immediately available data for population, land use, communications, utility and building type. The second was an experimental add-on to the Global Disaster Alert and Coordination System (GDACS) global warning system maintained by the Joint Research Centre (JRC) that draws information from open-access global data. After defining lava-flow model source terms (vent location, effusion rate, lava chemistry, temperature, crystallinity and vesicularity), we ran all available lava-flow emplacement models to produce a projection for the likelihood of impact for all pixels within the GIS. Next, inundation maps and damage reports for impacted zones were produced, with those produced by both the local system and by GDACS being in good agreement. The exercise identified several shortcomings of the systems, but also indicated that the generation of a GDACS-type global response system for effusive crises that uses rapid-response model projections for lava inundation driven by real-time satellite hotspot detection – and open-access datasets – is within the current capabilities of the community.