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Abstract Lava ingress into a vulnerable population will be difficult to control, so that evacuation will be necessary for communities in the path of the active lava, followed by post-event population, infrastructural, societal and community replacement and/or relocation. There is a pressing need to set up a response chain that bridges scientists and responders during an effusive crisis to allow near-real-time delivery of globally standard ‘products’ for a timely and adequate humanitarian response. In this chain, the scientific research groups investigating lava remote-sensing and modelling need to provide products that are both useful to, and trusted by, the crisis response community. Requirements for these products include (a) formats that can be immediately integrated into a crisis management procedure, and (b) in an agreed and stable standard. A review of current capability reveals that we are at a point where the community can provide such a response, as is the aim of the RED SEED (Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters) working group. This book is the first production of this group and is intended not only as a directory of current capabilities and operational service providers, but also as a statement of intent and need, while providing a simulation designed to demonstrate how a truly pan-disciplinary response to an effusive crisis could work.
MODVOLC: 14 years of autonomous observations of effusive volcanism from space
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.
AVHotRR: near-real time routine for volcano monitoring using IR satellite data
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.
Thermal monitoring of volcanic effusive activity: the uncertainties and outlier detection
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.
Synergistic use of satellite thermal detection and science: a decadal perspective using ASTER
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.
The NASA Volcano Sensor Web, advanced autonomy and the remote sensing of volcanic eruptions: a review
Abstract The Volcano Sensor Web (VSW) is a globe-spanning net of sensors and applications for detecting volcanic activity. Alerts from the VSW are used to trigger observations from space using the Earth Observing-1 ( EO-1 ) spacecraft. Onboard EO-1 is the Autonomous Sciencecraft Experiment (ASE) advanced autonomy software. Using ASE has streamlined spacecraft operations and has enabled the rapid delivery of high-level products to end-users. The entire process, from initial alert to product delivery, is autonomous. This facility is of great value as a rapid response is vital during a volcanic crisis. ASE consists of three parts: (1) Science Data Classifiers, which process EO-1 Hyperion data to identify anomalous thermal signals; (2) a Spacecraft Command Language; and (3) the Continuous Activity Scheduling Planning Execution and Replanning (CASPER) software that plans and replans activities, including downlinks, based on available resources and operational constraints. For each eruption detected, thermal emission maps and estimates of eruption parameters are posted to a website at the Jet Propulsion Laboratory, California Institute of Technology, in Pasadena, CA. Selected products are emailed to end-users. The VSW uses software agents to detect volcanic activity alerts generated from a wide variety of sources on the ground and in space, and can also be easily triggered manually.
Automated monitoring of high-temperature volcanic features: from high-spatial to very-high-temporal resolution
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.
Enhanced volcanic hot-spot detection using MODIS IR data: results from the MIROVA system
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.
HOTSAT: a multiplatform system for the thermal monitoring of volcanic activity using satellite data
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.
A fluid dynamics perspective on the interpretation of the surface thermal signal of lava flows
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.
Inverting multispectral thermal time-series images of volcanic eruptions for lava emplacement models
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.
On the detection and monitoring of effusive eruptions using satellite SO 2 measurements
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 DOWNFLOW is a probabilistic code for the simulation of the area covered by lava flows. This code has been used extensively for several basaltic volcanoes in the last decade, and a review of some applications is presented. DOWNFLOW is based on the simple principle that a lava flow tends to follow the steepest descent path downhill from the vent. DOWNFLOW computes the area possibly inundated by lava flows by deriving a number, N , of steepest descent paths, each path being calculated over a randomly perturbed topography. The perturbation is applied at each point of the topography, and ranges within the interval ±Δ h . N and Δ h are the two basic parameters of the code. The expected flow length is constrained by statistical weighting based on the past activity of the volcano. The strength of the code is that: (i) only limited volcanological knowledge is necessary to apply the code at a given volcano; (ii) there are only two (easily tunable) input parameters; and (iii) computational requirements are very low. However, DOWNFLOW does not provide the progression of the lava emplacement over time. The use of DOWNFLOW is ideal when a large number of simulations are necessary: for example, to compile maps for hazard and risk-assessment purposes.
Simulating the thermorheological evolution of channel-contained lava: FLOWGO and its implementation in EXCEL
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 VolcFlow is a finite-difference Eulerian code based on the depth-averaged approach and developed for the simulation of isothermal geophysical flows. Its capability for reproducing lava flows is tested here for the first time. The field example chosen is the 2010 lava flow of Tungurahua volcano (Ecuador), the emplacement of which is tracked by projecting thermal images onto a georeferenced digital topography. Results show that, at least for this case study, the isothermal approach of VolcFlow is able to simulate the velocity of the lava through time, as well as the extent of the solidified lava. However, the good fit between the modelled and the natural flow may be explained by the short emplacement time ( c. 20 h) of a thick lava ( c. 5 m), which could limit the influence of cooling on the flow dynamics, thus favouring the use of an isothermal rheology.
SCIARA: cellular automata lava flow modelling and applications in hazard prediction and mitigation
Abstract The use of thematic volcanic hazard maps is essential for policy managers and administrators in land use planning and to determine the best form of action during emergencies. In particular, hazard maps are a key tool in emergency management and are used to describe the threat expected at a certain location in the event of future eruptions. We applied the latest version of the SCIARA lava flow cellular automata model using parallel computing through general purpose graphics processing units technology to derive lava flow hazard maps for Mt Etna, Sicily. The methodology relies on an accurate analysis of the past behaviour of the volcano and is appropriate for land use planning and civil defence applications.
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.