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 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 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 A new shallow-depth approximation model for lava flow advance and cooling on a quantized topography is presented in this paper. To apply the model, lava rheology is described using a non-isothermal three-dimensional viscoplastic fluid in which the rheological properties are assumed to be temperature dependent. Asymptotic analysis allows a three-dimensional flow scenario to be reduced to a two-dimensional problem using depth-averaged equations. These equations are numerically approximated by an autoadaptive finite element method, based on the Rheolef C++ library, which allows economy of computational time. Here, the proposed approach is first evaluated by comparing numerical output with non-isothermal experimental results for a flow of silicon oil. Finally, the December 2010 eruption of Piton de la Fournaise (La Réunion Island) is numerically reproduced and compared with available data.

Abstract Piton de la Fournaise (La Reunion) and Karthala (Grande Comore) are the two active volcanoes of the Southwestern Indian Ocean. A 14 month (April 2013 to June 2014) monitoring period was carried out at both volcanoes using synthetic aperture RADAR interferometry (InSAR) techniques on RADARSAT-2 data. Thanks to the SEAS-OI (Survey of Environment Assisted by Satellite in the Indian Ocean) station, 21 SAR scenes were acquired over this period and InSAR results revealed the slow subsidence of the Dolomieu caldera floor at Piton de la Fournaise, following the 2009 and 2010 eruptions, and the subsidence of the whole cone between April and July 2013. At Karthala no evidence of any volcanic activity was found for the period April 2013 to June 2014. The use of systematic InSAR for volcano monitoring is an efficient tool to study effusive eruptions. We showed that, during periods of unrest, InSAR is able to pick up early signs of a future eruption and monitor secondary phenomena that require no real-time data. During an effusive crisis, it is still difficult to carry out fully operational InSAR monitoring, but using the example of the June 2014 eruption at Piton de la Fournaise, we show that SAR data can help with the detection and tracking of lava flows and active flow paths during effusive eruptions, based on SAR coherence and SAR amplitude. These preliminary results are very promising for the future of InSAR monitoring of active volcanoes and highlight the need for near-real-time access to SAR data in the mapping of active lava flows during effusive eruptions. This study also revealed the major role of ground stations like SEAS-OI in the efficiency of this monitoring, supplying free, near-real-time remote sensing data to the scientific and institutional communities.

Abstract Accurate and fast delivery of information about recent lava flows is important for near-real-time monitoring of eruptions. Here, we have characterized the October 2010 lava flow at Piton de la Fournaise using various InSAR datasets. We first produced a map of the area covered by the lava flow (i.e. Area lava =0.71–0.75 km 2) using the coherence of two syn-eruptive interferograms. Then we analysed two post-eruptive InSAR datasets (i.e. monostatic and bistatic data). The monostatic database provided us simultaneously with the displacement rates, lava thickness, volume and volume flux. We found that the lava flow was subsiding and moving eastward at maximum rates of 13±0.3 and 4±0.2 cm a −1 , respectively. Also, it had a mean thickness of Z mean =5.85 m, Vol DRE =1.77±0.75×10 6 m 3 (1σ) and MOR=1.25±0.53 m 3 s −1 . The bistatic database provided us only with the thickness and volume information (i.e. Z mean =6.00 m, Vol DRE =1.83±0.65×10 6 m 3 and MOR=1.29±0.46 m 3 s −1). Finally, we used a thermal remote sensing technique to verify the InSAR-derived measurements. Results show that the monostatic and bistatic datasets were both well within the range for the DRE volume obtained from MODIS data (2.44–4.40×10 6 m 3). Supplementary material: Tables A1 and A2 give satellite images used in this study. Table A3 gives the parameters used for the calculation of the effusion rates. The figures give the data processing of the post-eruptive radar images. These are available at https://doi.org/10.6084/m9.figshare.c.2213563