Abstract Calderas are formed by the collapse of large magma reservoirs and are commonly elliptical in map view. The orientation of elliptical calderas is often used as an indicator of the local stress regime; but, in some rift settings, pre-existing structural trends may also influence the orientation. We investigated whether either of these two mechanisms controls the orientation of calderas in the Kenyan Rift. Satellite-based mapping was used to identify the rift border faults, intra-rift faults and orientation of the calderas to measure the stress orientations and pre-existing structural trends and to determine the extensional regime at each volcano. We found that extension in northern Kenya is orthogonal, whereas that in southern Kenya is oblique. Elliptical calderas in northern Kenya are orientated NW–SE, aligned with pre-existing structures and perpendicular to recent rift faults. In southern Kenya, the calderas are aligned NE–SW and lie oblique to recent rift faults, but are aligned with pre-existing structures. We conclude that, in oblique continental rifts, pre-existing structures control the development of elongated magma reservoirs. Our results highlight the structural control of magmatism at different crustal levels, where pre-existing structures control the storage and orientation of deeper magma reservoirs and the local stress regime controls intra-rift faulting and shallow magmatism. Supplementary material: Details of the Standard Deviation Ellipse function and statistical methods are available at http://www.geolsoc.org.uk/SUP18849 .

Abstract Measuring volcano deformation is key to understanding the behaviour of erupting volcanoes and detecting those in periods of unrest. Satellite techniques provide the opportunity to do so on a global scale but, with some notable exceptions, the deformation of volcanoes in the tropics has been understudied relative to those at higher latitudes, largely due to technical difficulties in applying Interferometric Synthetic Aperture Radar (InSAR). We perform a systematic survey of the Central American Volcanic Arc to investigate the applicability of Interferometric Synthetic Aperture Radar (InSAR) to volcanoes in the tropics. Volcano characteristics that may prevent InSAR measurement include: (1) dense vegetation cover; (2) persistent activity; and (3) steep slopes. Measurements of deformation are further inhibited by atmospheric artefacts associated with: (4) large changes in topographical relief. We present a systematic method for distinguishing between water vapour artefacts and true deformation. Our data show a linear relationship ( c . 2 cm/km) between the magnitudes of water vapour artefacts and volcano edifice height. For high relief volcanoes (e.g. Fuego, Guatemala, 3763 m a.s.l. (above sea level)) errors are of the order of 4–5 cm across the volcano's edifice but are less than 2 cm for lower relief (e.g. Masaya, Nicaragua, 635 m a.s.l.). Examples such as Arenal, Atitlan and Fuego illustrate that satellite acquisition strategies incorporating ascending and descending tracks are particularly important for studying steep-sided volcanoes. Poor coherence is primarily associated with temporal decorrelation, which is typically more rapid in southern Central America where Evergreen broadleaf vegetation dominates. Land-use classification is a better predictor of decorrelation rate than vegetation index. Comparison of coherence for different radar wavelengths match expectations; high resolution X-band radar is best suited to local studies where high-resolution digital elevation models (DEMs) exist, while L-band wavelengths are necessary for regional surveys. However, this is the first time that relationships between phase coherence and time, perpendicular baseline, radar wavelength, and land use have been quantified on the scale of a whole volcanic arc.

Abstract Nyamulagira, located in the east of the Democratic Republic of Congo on the western branch of the East African rift, is Africa’s most active volcano, with an average of one eruption every 3 years since 1938. Owing to the socio-economical context of that region, the volcano lacks ground-based geodetic measurements but has been monitored by interferometric synthetic aperture radar (InSAR) since 1996. A combination of 3D Mixed Boundary Element Method and inverse modelling, taking into account topography and source interactions, is used to interpret InSAR ground displacements associated with eruptive activity in 1996, 2002, 2004, 2006 and 2010. These eruptions can be fitted by models incorporating dyke intrusions, and some (namely the 2006 and 2010 eruptions) require a magma reservoir beneath the summit caldera. We investigate inter-eruptive deformation with a multi-temporal InSAR approach. We propose the following magma plumbing system at Nyamulagira by integrating numerical deformation models with other available data: a deep reservoir ( c . 25 km depth) feeds a shallower reservoir ( c . 4 km depth); proximal eruptions are fed from the shallow reservoir through dykes while distal eruptions can be fed directly from the deep reservoir. A dyke-like conduit is also present beneath the upper southeastern flank of Nyamulagira.

Abstract Asama Volcano, Japan, is one of the most active volcanoes in the Japanese islands. Recent development of geophysical monitoring in Asama Volcano allows us to infer the magma pathway and its structural controls beneath the volcano. Combining geodetic data and precise earthquake locations during recent eruptions suggests that the magma intrudes several kilometres to the west of the summit to a depth of about 1 km below sea level as a nearly east–west-trending dyke. The vertically intruded magma then moves horizontally by several kilometres to beneath the summit before it ascends vertically to make the surface. Combining the P-wave velocity and the resistivity structure shows that the intrusions are under structural controls. Frozen and fractureless magma associated with volcanic activity until 24 000 years ago impedes the ascent of rising magma on its way to the surface. The S-wave velocity structure inferred from ambient noise tomography reveals a low-velocity body beneath the modelled dyke. From independent information, we have inferred that this low-velocity body is likely to be a magma chamber.

Abstract Recent advances in Global Positioning System (GPS), tilt and Interferometric Synthetic Aperture Radar (InSAR) have greatly increased the availability of volcano deformation data. These measurements, combined with appropriate source models, can be used to estimate magma chamber depth, and to provide information on chamber shape and volume change. However, kinematic models cannot constrain magma chamber volume, and provide no predictive capability. Volcanic eruptions are commonly preceded by periods of inflation. Under appropriate conditions, eruptions are ‘inflation predictable’; that is, subsequent eruptions occur when inflation recovers the deflation during the preceding event. Notable successes in forecasting eruptions have come largely through the ability to discern repeatable patterns in seismic activity, ground deformation and gas emission, combined with historical and geological evidence of past eruptive behaviour. To move beyond empirical pattern recognition to forecasting based on deterministic physical–chemical models of the underlying dynamics, will require integration of different data types and models. I suggest two areas poised for progress: quantitative integration of deformation and seismicity; and model-based forecasts conditioned on estimates of material parameters and initial conditions from inversion of available datasets. Deformation and seismicity are the principal geophysical methods for volcano monitoring, and in some cases have signalled dyke propagation minutes to hours prior to eruptions. Quantitative models relating these processes, however, have been lacking. Modern theories of seismicity rate variations under changing stress conditions can be used to integrate deformation and (volcano–tectonic) seismicity into self-consistent inversions for the spatio-temporal evolution of dyke geometry and excess magma pressure. This approach should lead to improved resolution over existing methods and, perhaps, to improved real-time forecasts. The past few decades have also witnessed a marked increase in the sophistication of physical–chemical models of volcanic eruptions. I review conduit models that can be combined with GPS and extrusion rate data through Markov Chain Monte Carlo (MCMC) inversion to estimate the absolute volume of the crustal magma chamber, initial chamber overpressure, initial volatile concentrations and other parameters of interest. The MCMC estimation procedure can be extended to deterministic forecasting by using the distribution of initial conditions and material parameters consistent with available data to initiate predictive forward models. Such physics-based MCMC forecasts would be based on all knowledge of the system, including data up to the current date. The underlying model is completely deterministic; however, because the method samples initial conditions and physical parameters consistent with the given data, it yields probabilistic forecasts including uncertainties in the underlying parameters. Because there are almost certain to be effects not factored into the forward models, there is likely to be a substantial learning curve as models evolve to become more realistic.

Abstract This chapter provides a historical review of the use of infrared remote sensing for the monitoring of volcanic activity. It (1) examines the theoretical basis for infrared observations of thermally anomalous volcanic features, (2) presents the various sensors that have been used and are currently available and (3) describes the techniques that have been developed to analyse such data. The chapter ends with a case study of data derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer shortwave infrared observations of Lascar Volcano in Chile. This case study aims to highlight the utility of infrared observations in volcanological studies, assessing the various techniques that can be used and examining the different factors which influence these analyses. The chapter ends discussing future prospects for volcanic infrared remote sensing.

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 We examine 150 volcanoes and geothermal areas in the central, southern and austral Andes for thermal anomalies between the years 2000 and 2010 from two different spaceborne sensors: (1) those automatically detected by the MODVOLC algorithm from MODIS; and (2) manually identified hotspots in night-time images from ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer). Based on previous work, we expected to find eight volcanoes displaying thermal anomalies (Ubinas, Villarrica, Copahue, Láscar, Llaima, Chaitén, Lonquimay and Chiliques). We document 35 volcanic areas with pixel-integrated temperatures of 4 up to more than 100 K above background in at least two images, and another 16 areas that have questionable hotspots with either smaller anomalies or a hotspot identified in only one image. Most of the thermal anomalies are related to known activity (i.e. lava and pyroclastic flows, growing lava domes, fumaroles, and lakes) while others are of unknown origin or reflect activity at volcanoes that were not thought to have surface activity. A handful of volcanoes exhibit temporal variations in the magnitude and location of their temperature anomalies that can be related to both documented and undocumented pulses of activity. Our survey reveals that low-amplitude volcanic hotspots detectable from space are more common than expected, based on lower spatial resolution data, and that these features could be more widely used to monitor changes in the activity of remote volcanoes. We find no evidence from ASTER or MODVOLC that the thermal anomalies were affected by six earthquakes with M w above 7 in our study area from 2000 to 2010, although the observations may not have been optimal to detect such anomalies. Supplementary material: Supplementary tables of data and figures for the volcanoes studied are available at http://www.geolsoc.org.uk/SUP18581 .

Abstract Large volcanic explosions pose a severe risk to life and cargo by injecting ash into local and international air traffic routes. Prior to exploding, Bezymianny (Kamchatka) commonly shows an increase in lava extrusion rate, which can be detected by satellites as an increase in thermal radiance. Here we present the first method of forecasting explosive eruptions based solely on satellite data. A pattern recognition algorithm using Advanced Very High Resolution Radiometer (AVHRR) data has been developed based on known precursory trends of increasing radiance prior to 19 explosions at Bezymianny Volcano in 1993–2008. The algorithm retrospectively forecasts 89% of the explosions (100% of the explosions that show precursory increases in thermal radiance), with 71% of alerts issued in the 30 days beforehand. The method also provides the probability of an explosion occurring within a given number of days after an alert is triggered by the algorithm. When applied to independent data, the algorithm correctly provided alerts before the 16 December 2009, 31 May 2010 and 13 April 2011 explosions.

Abstract We investigate high-resolution digital photographs and infrared images of the lava dome eruption at Volcán de Colima, from 2007 to 2010. Qualitative observations provide insight into active volcanic processes (e.g. rockfalls and fracturing) and show that, as the dome advances a substantial cooled talus apron develops, which stabilizes the structure. Progressive collapse of the talus apron as it reaches the crater rim corresponds with the development of a lava lobe, extruding hot lava from deeper within the dome. Quantitative dome surface temperature time-series show that the highest temperature hotspots migrate from the dome sides (250–380 °C) to the top (150–300 °C) and finally to the lava lobe (220–400 °C) as the structurally unstable areas expose fresh material. Net surface heat loss from the dome ranges from 5 to 30 MW, comparable to other dome forming systems. Heat budget calculations confirm that the lava dome retained a hot viscous core throughout the period 2007–2010. We propose that the mechanical stability of the Volcán de Colima dome arises from the shear strength of flanking talus which stabilizes the hot viscous core.

Abstract The ultraviolet (UV) Ozone Monitoring Instrument (OMI), launched on NASA's Aura satellite in July 2004, was the first space-based sensor to provide operational sulphur dioxide (SO 2 ) measurements (OMSO2) for use by the scientific community. Herein, we discuss the application of OMSO2 data for the monitoring of global volcanic SO 2 emissions, with an emphasis on lower tropospheric volcanic plumes. We review the algorithms used to produce OMSO2 data and highlight some key measurement sensitivity issues. The data processing scheme used to generate web-based OMSO2 data subsets for volcanic regions and estimate SO 2 burdens in volcanic plumes is outlined. We describe three techniques to derive SO 2 emission rates from the OMSO2 measurements, and employ one method (using single OMI pixels to estimate SO 2 fluxes) to elucidate SO 2 flux detection thresholds on a global scale. Applications of OMSO2 data to volcanic degassing studies are demonstrated using four case studies. These examples show how OMSO2 measurements correlate with changes in eruptive activity at Kilauea volcano (Hawaii), constrain small, potentially significant SO 2 releases from reawakening, historically inactive volcanoes, track long-term changes in SO 2 degassing from Nyiragongo volcano (D.R. Congo), and detect SO 2 emissions from the remote Lastarria Volcano (Chile), in the actively deforming Lazufre region.

Abstract The Ozone Monitoring Instrument (OMI) is a satellite-based ultraviolet (UV) spectrometer with unprecedented sensitivity to atmospheric sulphur dioxide (SO 2 ) concentrations. Since late 2004, OMI has provided a high-quality SO 2 dataset with near-continuous daily global coverage. In this review, we discuss the principal applications of this dataset to volcano monitoring: (1) the detection and tracking of large eruption clouds, primarily for aviation hazard mitigation; and (2) the use of OMI data for long-term monitoring of volcanic degassing. This latter application is relatively novel, and despite showing some promise, requires further study into a number of key uncertainties. We discuss these uncertainties, and illustrate their potential impact on volcano monitoring with OMI through four new case studies. We also discuss potential future avenues of research using OMI data, with a particular emphasis on the need for greater integration between various monitoring strategies, instruments and datasets.

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 Scientific knowledge of transient and difficult-to-access airborne volcanic emissions comes primarily from remote sensing observations, and a few in situ data from sporadic heroic or inadvertent airborne encounters. In the past, patchy knowledge of the composition and behaviour of such plumes from explosive volcanic eruptions, and associated drifting ash and gas clouds, have centrally contributed to unwanted and dangerous aircraft encounters that have put crews at risk and, in some cases, greatly damaged aircraft. Thus, improved knowledge of boundary conditions and plume composition, as inputs to both mass retrieval and predictive models for cloud trajectories , would be of benefit. In this paper, we describe how small robotic unmanned aerial vehicles (sUAVs) can address a variety of measurements that are typically beyond the reach of, and sometimes too dangerous for, manned aircraft. The direct measurements and sampling that can be achieved by sUAVs address serious gaps in knowledge of volcanic processes, and provide important validation data for estimations of volcanogenic ash and gas concentrations gleaned using remote sensing techniques. These data, in turn, constrain key proximal and distal boundary conditions for aerosol and gas transport models on which are based a number of decisions and evaluations by hazard responders and regulatory agencies. We briefly describe a case study from our ongoing field study at Turrialba Volcano in Costa Rica, where we are conducting an international campaign of systematic airborne in situ measurements of volcanogenic SO 2 and other gases, as well as aerosols, with sUAVs and aerostats (e.g. tethered balloons and kites), in conjunction with data acquisitions by the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer onboard the NASA Terra Earth orbital platform. To our knowledge, this is the first such systematic in situ UAV- and aerostat-based observation programme for SO 2 and particulates in a volcanic plume for correlation with orbital data. We preliminarily report good agreement between our UAV/aerostat and ASTER SO 2 retrievals within a 5 km radius of the volcano summit, at altitudes of up to 12 500 ft ( c. 3850 m) above sea level (asl) for concentrations within the range of 5–20 ppmv (ppm by volume). Additional work continues.

Abstract Volcanoes have played a profound role in shaping our planet, and volcanic activity is a major hazard locally, regionally and globally. Many volcanoes are, however, poorly accessible and sparsely monitored. Consequently, remote sensing is playing an increasingly important role in tracking volcano behaviour, while synoptic remote sensing techniques have begun to make major contributions to volcanological science. Volcanology is driven in part by the operational concerns of volcano monitoring and hazard management, but the goal of volcanological science is to understand the processes that underlie volcanic activity. This volume shows how we may reach a deeper understanding by integrating remote sensing measurements with modelling approaches and, if available, ground-based observations. It includes reviews and papers that report technical advances and document key case studies. They span a range of remote sensing applications to volcanoes, from volcano deformation, thermal anomalies and gas fluxes, to the tracking of eruptive ash and gas plumes. The result is a state-of-the-art overview of the ever-growing importance of remote sensing to volcanology.