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 The remote sensing of volcanic ash plumes from space can provide a warning of an aviation hazard and knowledge on eruption processes and radiative effects. In this paper new algorithms are presented to provide volcanic plume properties from measurements by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), the Advanced Along Track Scanning Radiometer (AATSR) and the Spinning Enhanced Visible and Infrared Imager (SEVIRI). A challenge of remote sensing is to provide near-real-time methods to identify, and so warn of, the presence of volcanic ash. To achieve this, a singular vector decomposition method has been developed for the MIPAS instrument on board the Environmental Satellite. This method was applied to observations of the ash clouds from the eruptions of Nabro and the Puyehue–Cordón Caulle in 2011 and led to a sensitive volcanic signal flag which was capable of tracking changes in the volcanic signal spectra as the plume evolved. A second challenge for remote sensing is to identify the ash plume height. This is a critical parameter for the initialization of algorithms that numerically model the evolution and transport of a volcanic plume. As MIPAS is a limb sounder, the identification of ash also provides an estimate of height provided the plume is above about 6 km. This is complemented by a new algorithm, Stereo Ash Plume Height Retrieval Algorithm, that identifies plume height using the parallax between images provided by Along Track Scanning Radiometer-type instruments. The algorithm was tested on an image taken at 14:01 GMT on 6 June 2011 of the Puyehue–Cordón Caulle eruption plume and gave a height of 11.9±1.4 km, which agreed with the value derived from the location of the plume shadow (12.7±1.8 km). This plume height was similar to the height observed by MIPAS (12 ± 1.5 km) at 02:56 GMT on 6 June. The quantitative use of satellite imagery and the full exploitation of high-resolution spectral measurements of ash depends upon knowing the optical properties of the observed ash. Laboratory measurements of ash from the 1993 eruption of Mt Aso, Japan have been used to determine the refractive indices from 1 to 20 µm. These preliminary measurements have spectral features similar to ash values that have been used to date, albeit with slightly different positions and strengths of the absorption bands. The refractive indices have been used to retrieve ash properties (plume height, optical depth and ash effective radius) from AATSR and SEVIRI instruments using two versions of Oxford-RAL Retrieval of Aerosol and Cloud (ORAC) algorithm. For AATSR a new ash cloud type was used in ORAC for the analysis of the plume from the 2011 Eyjafjallajökull eruption. For the first c . 500 km of the plume ORAC gave values for plume height of 2.5–6.5 km, optical depth 1–2.5 and effective radius 3–7 µm, which are in agreement with other observations. A weakness of the algorithm occurs when underlying cloud invalidates the assumption of a single cloud layer. This is rectified in a modified version of ORAC applied to SEVIRI measurements. In this case an extra model of a cloud underlying the ash plume was included in the range of applied models. In cases where the plume overlay cloud, this new model worked well, showing good agreement with correlative Cloud–Aerosol Lidar with Orthogonal Polarization observations.

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 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 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 The activity status of a volcano can be evaluated from the remotely measured radiant power ( RP ). The measured RP contains noise due to reasons such as atmospheric effects and instrument characteristics. Here we first show how to estimate the uncertainty of each single RP measurement. To additionally reduce the temporal noise of the RP time series we apply a Kalman filter. The Kalman filter is able to recursively analyse an unevenly sampled time series. To validate our filtering scheme, we applied it to an eruption of Etna in 2002, as well as to the eruption of Nyamuragira in 2010. In the case of the Etna eruption, the denoised time series agrees well with in situ observations of a waxing and waning flow. For the case of Nyamuragira, the enhanced time series of RP shows more fluctuation probably due to cloud coverage. Thus, we propose a multiple instrument approach that increases the temporal resolution of the RP time series and reduces the associated noise.

Abstract Erta ‘Ale volcano lies at the centre of the Erta ‘Ale rift segment in northern Afar, Ethiopia and hosts one of the few persistent lava lakes found on Earth in its summit caldera. Previous studies have reported anecdotal evidence of a correlation between lake activity and magmatic and tectonic events in the broader region. We investigated this hypothesis for the period 2000–15 by comparing a catalogue of regional events with changes in lake activity reconstructed from Earth Observation data. The lava lake underwent dramatic changes during the study period, exhibiting an overall rise in height with concomitant changes in geometry consistent with a change in heat energy balance. Numerous paroxysms occurred in the lake and in the north pit; a significant dyke intrusion with subsequent re-intrusions indicated a role for dykes in maintaining the lake. However, despite some coincidences between the paroxysms and regional events, we did not find any statistically significant relationship between the two on a timescale of days to weeks. Nevertheless, changes in lake activity have preceded the broad increase in regional activity since 2005 and we cannot rule out a relationship on a decadal scale.

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 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.

Abstract The sequence of dyke intrusions between 2005 and 2010 in the Manda Hararo rift segment, Ethiopia, provided an opportunity to test conceptual models of continental rifting. Based on trends up to dyke 13 in the sequence, it was anticipated that, should magma supply continue, dykes would shorten in length and eruptions would increase in size and decrease in distance from the segment centre as extensional stress was progressively released. In this paper we revisit these predictions by presenting a comprehensive overview of the May 2010 dyke and fissure eruption, the 14th and last in the sequence, from InSAR, seismicity, satellite thermal data, ultraviolet SO 2 retrievals and multiple LiDAR surveys. We find the dyke is longer than other eruptive dykes in the sequence, propagating in two directions from the segment centre, but otherwise fairly typical in terms of opening, propagation speed and geodetic and seismic moment. However, though the eruption is located closer to the segment centre, it is much smaller than previous events. We interpret this as indicating that either the Manda Hararo rifting event was magma limited, or that extensional stress varies north and south of the segment centre.

Abstract We present a novel method for interpreting time series of multispectral observations of volcanic eruptions. We show how existing models relating to radiance and area emplacement can be generalized into an integration-convolution of a Net Area Emplacement (NAE) function and a cooling function, assuming all surfaces follow the same cooling curve. The NAE describes the variation in the rate of emplacement of hot material with time and temperature, while the cooling function describes the cooling of a hot surface with time. Discretizing the integration-convolution equation yields an underdetermined matrix equation that we solve using second-order Tikhonov regularization to stabilize the solution. We test the inversion by modelling plausible NAE surfaces, calculating the radiances, adding noise and inverting for the original surface. Three or more spectral bands are required to capture the overall shape of the NAE, and recovering specific quantities is difficult. Single wavebands that yield flat kernels recover the total area emplacement curve (rate of increase of hot area – the integral of the NAE with respect to temperature) surprisingly well due to their property of conserving NAE, suggesting novel methods for calculating area emplacement rates (and effusion rates) from time series of satellite images and radiometer measurements.

Abstract Thermal observations of volcanic activity when the volcano is partially covered by clouds or observed under a wide-scan angle are often removed from further analyses. In the event of a volcanic crisis, such a reduced set of data is not adequate. Even when the observation conditions are favourable, the full observation set is still required to provide decision-makers with quality information about the data. Automatic quality estimation and outlier detection was not estimated in the past. We propose to analytically define the uncertainty for individual observations based on the measurement circumstances. To additionally reduce the temporal noise of the radiant power ( RP ) time series we apply a Kalman Filter (KF). The KF is able to recursively analyse an unevenly sampled time series. Based on some proposed rules, it can also detect outliers. We apply the proposed methodology to the 2008–09 Etna eruption monitored by MODIS (Moderate Resolution Imaging Spectroradiometer). The analysis of the results shows that the topography has a greater influence on RP than previously considered.