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The TanDEM-X satellite mission has revolutionized DEM generation from spaceborne synthetic aperture radar. In addition to the primary objective of generating a consistent digital elevation model with global coverage and unprecedented accuracy, the mission has acquired time series of topographic data over several volcanoes, providing an excellent opportunity to test the use of this innovative dataset for volcano monitoring and research. In this article, we review the utilization of the single-pass TanDEM-X data for studying various kinds of volcanic activity, such as basaltic lava flows, the formation and destruction of lava domes and related pyroclastic density currents, and subsurface magma withdrawal and intrusion. We then consider the uses of these data for hazard assessment and forecasting. Our goal is to highlight the importance of timely and repeated topographic information in volcanology, and to suggest the development of future spaceborne bistatic synthetic aperture radar satellite missions, such as ESA's Earth Explorer 10 candidate mission, “Harmony.”

The 2018 summit and flank eruption of Kīlauea Volcano was one of the largest volcanic events in Hawaiʻi in 200 years. Data suggest that a backup in the magma plumbing system at the long-lived Puʻu ʻŌʻō eruption site caused widespread pressurization in the volcano, driving magma into the lower flank. The eruption evolved, and its impact expanded, as a sequence of cascading events, allowing relatively minor changes at Puʻu ʻŌʻō to cause major destruction and historic changes across the volcano. Eruption forecasting is inherently challenging in cascading scenarios where magmatic systems may prime gradually and trigger on small events.

Satellite monitoring of volcanic activity typically includes four primary observations: (1) deformation and surface change, (2) gas emissions, (3) thermal anomalies, and (4) ash plumes. These phenomena are imaged by remote sensing data that span the electromagnetic spectrum, from microwave to ultraviolet energy and including visible and infrared wavelengths. The primary uses of satellite data in volcanology are forecasting, detecting, and tracking eruptive activity. Eruptions are often preceded by a number of indicators that are detectable from space, including surface deformation, subtle increases in surface temperature, and elevated gas emissions. The first indications of eruption, especially at remote volcanoes, are often identified in satellite data by strong thermal anomalies and/or the presence of ash and gas in the atmosphere, the recognition of which can be automated for rapid eruption detection. Once an eruption is in progress, space-based imagery of all types can track activity over time, providing information on the emplacement of volcanic deposits, the presence and character of ash plumes, and potential changes in the character of the eruption, all of which aid hazards assessment. Activity at Agung volcano, Indonesia, during 2017–2019, offers an excellent example of the importance of remote sensing datasets for forecasting, detecting, and tracking eruptions. Challenges to exploiting current and future satellite data include ensuring regular acquisitions over active volcanoes and developing tools for automated analysis of the massive volume of imagery for volcano-related signals.

The mobile south flank of Kīlauea Volcano hosts two normal fault systems, the Koa'e fault system (KFS) and the Hilina fault system (HFS). In historical time, at least three M>6.5 earthquakes have occurred on the basal detachment of the Kīlauea Volcano's south flank, with the most recent being the 4 May 2018 M6.9 earthquake. Here we analyze kinematic Global Positioning System data collected from 2001 to 2017 and interferometric synthetic aperture radar data before, during, and after the 2018 M6.9 earthquake to determine the crustal motion across the HFS and KFS faults. Our results indicate that the HFS faults did not significantly slip during the interseismic period from 2007 to 2011. Despite its substantial magnitude, interferometric synthetic aperture radar (InSAR) data show that the 2018 M6.9 earthquake triggered subcentimeter level slip along sections of the previously mapped HFS branches. Up to 20 cm of offset occurred on what appears to be a newly formed (or previously unknown) fault near the eastern end of the HFS. During the 3 months following the M6.9 earthquake, up to ~30 cm of slip occurred along the KFS, which helps accommodate rapid large‐scale subsidence of Kīlauea's summit region as large volumes of summit reservoir magma fed the lower East Rift Zone eruption. The HFS appears to activate only in concert with large earthquakes on the basal detachment. The KFS, on the other hand, moves both seismically during small local earthquakes and aseismically in response to nearby earthquakes and caldera subsidence.

Kīlauea Volcano (Hawaiʻi, USA) is underlain by a complex, laterally extensive magmatic plumbing system. Although in recent decades it has mainly erupted through vents along the middle East Rift Zone and summit caldera, eruptions can occur anywhere along its laterally extensive rift zones, as demonstrated by the dramatic eruptive activity of 2018. Forecasting eruptive activity requires an understanding of whether an episode of volcano-seismic unrest at Kīlauea and similar volcanoes is caused directly at the edges of an active intrusion or reservoir, or in a volume of wall rock at a distance from the intrusion. Seismic unrest in Kīlauea’s upper East Rift Zone (UERZ) has to date been interpreted as the result either of magma intrusion in this region of the volcano or of stresses due to seaward flank migration. However, recent observations suggest that UERZ seismicity may result from variable pressurization of Kīlauea’s summit magma system. We analyze seismic and deformation (multi-temporal interferometric synthetic aperture radar [InSAR] and GPS) data during a period of variable summit deformation and UERZ seismicity in mid- to late 2007 and calculate Coulomb stress changes on UERZ faults due to modeled summit inflation or deflation. UERZ seismicity during our study period can be explained entirely by stresses arising from pressure changes within Kīlauea’s summit reservoirs. Furthermore, a comparison of UERZ fault plane solutions (FPSs) calculated for this study to published UERZ FPSs for previous periods suggests that the UERZ has undergone a transition from a mechanically strong, discontinuous, and immature magma transport system to a mature, mechanically weak, and fully connected transport system over the course of the 1983–2018 eruption.

After 53 years of quiescence, Mount Agung awoke in August 2017, with intense seismicity, measurable ground deformation, and thermal anomalies in the summit crater. Although the seismic unrest peaked in late September and early October, the volcano did not start erupting until 21 November. The most intense explosive eruptions with accompanying rapid lava effusion occurred between 25 and 29 November. Smaller infrequent explosions and extrusions continue through the present (June 2019). The delay between intense unrest and eruption caused considerable challenges to emergency responders, local and national governmental agencies, and the population of Bali near the volcano, including over 140,000 evacuees. This paper provides an overview of the volcanic activity at Mount Agung from the viewpoint of the volcano observatory and other scientists responding to the volcanic crisis. We discuss the volcanic activity as well as key data streams used to track it. We provide evidence that magma intruded into the mid-crust in early 2017, and again in August of that year, prior to intrusion of an inferred dike between Mount Agung and Batur Caldera that initiated an earthquake swarm in late September. We summarize efforts to forecast the behavior of the volcano, to quantify exclusion zones for evacuations, and to work with emergency responders and other government agencies to make decisions during a complex and tense volcanic crisis.

Connecting caldera collapse The Kīlauea Volcano on the island of Hawai‘i erupted for 3 months in 2018. Neal et al. present a summary of the eruption sequence along with a variety of geophysical observations collected by the Hawaiian Volcano Observatory. The cyclic inflation, deflation, and eventual collapse of the summit was tied to lava eruption from lower East Rift Zone fissures. A total volume of 0.8 cubic kilometers of magma erupted, roughly the equivalent of 320,000 swimming pools, which matched the change in volume at the summit. Science , this issue p. 367

Since the beginning of the 20th century, volcano geodesy has evolved from time- and personnel-intensive methods for collecting discrete measurements to automated and/or remote tools that provide data with exceptional spatiotemporal resolution. By acknowledging and overcoming limitations related to data collection and interpretation, geodesy becomes a powerful tool for forecasting the onset and tracking the evolution of volcanic eruptions. In addition, geodetic data can be used for novel applications, such as mapping surface and topographic change due to the emplacement of volcanic deposits, detecting volcanic plumes, and constraining the properties of magmatic systems. These collective capabilities provide critical support for understanding magmatic processes at erupting volcanoes, while also offering important baseline data in advance of potential volcanic unrest. Future developments in volcano geodesy will involve not just new technology, but also advanced modeling and automated analysis methods that will provide a new understanding of the volcanic activity.

We use ground and space geodetic data to study surface deformation at Kīlauea Volcano from January to September 2015. This period includes an episode of heightened activity in April and May 2015 that culminated in a magmatic intrusion beneath the volcano's summit. The data set consists of Global Navigation Satellite System (GNSS), tilt, visual and seismic time series along with 25 descending and 15 ascending acquisitions of the Sentinel-1 satellite. We identify four different stages of surface deformation and volcanic activity, which we attribute to pressure changes and the movement of magma in response to an imbalance between magma supply and withdrawal in the shallow plumbing system, eventually leading to an intrusion beneath the summit area. In particular, we model the deformation as due to pressure changes in two subsurface magma bodies: the Halema‘uma‘u Reservoir (HMMR) and South Caldera Reservoir (SCR). The SCR was best described by an ellipsoidal source at 2.8 (2.65–3.07 at 95% confidence) km depth below the south caldera region. The HMMR was modeled as a point source located just east of Halema‘uma‘u crater at 1.5 (0.95–2.62) km depth. We suggest that a short-term increase in the magma supply rate to the volcano is a potential mechanisms for the intrusion, although other factors, like the filling of available void space or a reduced efficiency of magma transport through the volcano's East Rift Zone, may also play a role.

We use high resolution satellite Synthetic Aperture RADAR (SAR) data to study surface deformation at KĪlauea Volcano from January to September 2015. This period includes an episode of heightened activity in May 2015, which we refer to as ‘the May 2015 event’. The data set consists of 25 descending and 15 ascending acquisitions of the Sentinel-1a satellite in Interferometric Wide swath mode. We identify at least two stages of surface deformation and volcanic activity during the May 2015 event which we attribute to the movement of magma and pressure changes in response to a magma supply and withdrawal imbalance in the shallow plumbing system. In particular, we model the deformation sources attributed to the Halema'uma'u Reservoir (HMMR) and Southern Caldera Reservoir (SCR). The SCR was best described by inflation of a spheroidal source at 2.8 (2.65-3.07) km depth below the Southern caldera region. The HMMR source was modelled by a point source deflation located East of the Halema'uma'u crater at 1.5 (0.95-2.62) km depth.

The February 1993 dike intrusion in the East Rift Zone (ERZ) of Kīlauea Volcano, Hawai'i, was recognized from tilt and seismic data, but ground-based geodetic data were too sparse to constrain the characteristics of the intrusion. Analysis of Interferometric Synthetic Aperture Radar (InSAR) from the Japan Aerospace Exploration Agency (JAXA) JERS-1 satellite reveals a maximum of ~30 cm of line-of-sight (LOS) displacement occurring near Makaopuhi Crater in the middle ERZ of Kīlauea. We model this deformation signal as a subvertical dike using a 3D-Mixed Boundary Element Method (3D-MBEM) paired with a nonlinear inversion algorithm to find the best-fit model. The best-fit dike is located just to the west of Makaopuhi Crater striking N50°W, extends to within 100 m of the surface, is ~1.3 km in length by ~4.2 km in width along strike, and has a total volume of ~7.4 × 106 m3. In addition, a post-intrusion interferogram from JERS-1 spanning 1993–1997 was analyzed. Guided by previous results, our model for the 4-year period consists of opening of the deep rift zones by about 0.5 m at 3–8.5 km depth beneath the Southwest Rift Zone (SWRZ), ERZ and the summit. A sub-horizontal detachment fault is connected to the seaward side of the vertical dike-like source to mimic the decollement known to exist beneath the volcano. We classify the 1993 dike intrusion as a passive intrusion similar to those that occurred in 1997 and 1999. Passive intrusions lack precursory inflation at Kīlauea's summit, and the likely triggering mechanism is persistent deep rift opening combined with seaward motion of the south flank along the basal decollement. Passive intrusions make forecasting and hazard assessment difficult since they are not preceded by inflation nor by large increases in seismicity.

Prior to the 2018 lower East Rift Zone (ERZ) eruption and summit collapse of Kīlauea Volcano, Hawai‘i, continuous gravimeters operated on the vent rims of ongoing eruptions at both the summit and Pu‘u ‘Ō‘ō. These instruments captured the onset of the 2018 lower ERZ eruption and the effects of lava withdrawal from both locales, providing constraints on the timing and style of activity and the physical properties of the lava lakes at both locations. At the summit, combining gravity, lava level, and a three-dimensional model of the vent indicates that the upper ∼200 m of the lava lake had a density of about 1700 kg m−3, slightly greater than estimates from 2011–2015 and possibly indicating a gradual densification over time. At Pu‘u ‘Ō‘ō, gravity and vent geometry were used to model both the density and the rate of crater collapse, which was unknown owing to a lack of visual observations. Results suggest the withdrawal of at least 11 × 10 6 m3 of lava over the course of two hours, and a material density of 1800–1900 kg m−3. In addition, gravity data at Pu‘u ‘Ō‘ō captured a transient decrease and increase about an hour prior to crater collapse and that was probably related to a small, short-lived fissure eruption on the west flank of the cone and possibly to dike intrusion beneath Pu‘u ‘Ō‘ō. The fissure was the first event in the subsequent cascade that ultimately led to the extrusion of over 1 km3 of lava from lower ERZ vents, collapse of the summit caldera floor by more than 500 m, and the destruction of over 700 homes and other structures. These results emphasize the importance of continuous gravity in operational monitoring of active volcanoes.

Estimates of the carbon content of Earth’s mantle and magmas vary. Analysis and modelling of gas emissions at Hawai‘i indicate that the amount of carbon in the Hawaiian mantle plume and CO2 in Hawaiian lavas is 40% greater than previously thought.

Persistent motion of the south flank of Kīlauea Volcano, Hawai'i, has been known for several decades, but has only recently been identified at other large basaltic volcanoes—namely Piton de la Fournaise (La Reunion) and Etna (Sicily)—thanks to the advent of space geodetic techniques. Nevertheless, understanding of long-term flank instability is based largely on the example of Kīlauea, despite the large differences in the manifestations and mechanisms of the process when viewed through a comparative lens. For example, the rate of flank motion at Kīlauea is several times that of Etna and Piton de la Fournaise and is accommodated on a slip plane several km deeper than is probably present at the other two volcanoes. Gravitational spreading also appears to be the dominant driving force at Kīlauea, given the long-term steady motion of the volcano's south flank regardless of eruptive/intrusive activity, whereas magmatic activity plays a larger role in flank deformation at Etna and Piton de la Fournaise. Kīlauea and Etna, however, are both characterized by heavily faulted flanks, while Piton de la Fournaise shows little evidence for flank faulting. A helpful means of understanding the spectrum of persistent flank motion at large basaltic edifices may be through a framework defined on one hand by magmatic activity (which encompasses both magma supply and edifice size), and on the other hand by the structural setting of the volcano (especially the characteristics of the subvolcanic basement or subhorizontal intravolcanic weak zones). A volcano's size and magmatic activity will dictate the extent to which gravitational and magmatic forces can drive motion of an unstable flank (and possibly the level of faulting of that flank), while the volcano's structural setting governs whether or not a plane of weakness exists beneath or within the edifice and can facilitate flank slip. Considering persistent flank instability using this conceptual model is an alternative to using a single volcano as a “type example”—especially given that the example is usually Kīlauea, which defines an extreme end of the spectrum—and can provide a basis for understanding why flank motion may or may not exist on other large basaltic volcanoes worldwide.

During the past few decades, time-variable volcano gravimetry has shown great potential for imaging subsurface processes at active volcanoes (including some processes that might otherwise remain “hidden”), especially when combined with other methods (e.g., ground deformation, seismicity, and gas emissions). By supplying information on changes in the distribution of bulk mass over time, gravimetry can provide information regarding processes such as magma accumulation in void space, gas segregation at shallow depths, and mechanisms driving volcanic uplift and subsidence. Despite its potential, time-variable volcano gravimetry is an underexploited method, not widely adopted by volcano researchers or observatories. The cost of instrumentation and the difficulty in using it under harsh environmental conditions is a significant impediment to the exploitation of gravimetry at many volcanoes. In addition, retrieving useful information from gravity changes in noisy volcanic environments is a major challenge. While these difficulties are not trivial, neither are they insurmountable; indeed, creative efforts in a variety of volcanic settings highlight the value of time-variable gravimetry for understanding hazards as well as revealing fundamental insights into how volcanoes work. Building on previous work, we provide a comprehensive review of time-variable volcano gravimetry, including discussions of instrumentation, modeling and analysis techniques, and case studies that emphasize what can be learned from campaign, continuous, and hybrid gravity observations. We are hopeful that this exploration of time-variable volcano gravimetry will excite more scientists about the potential of the method, spurring further application, development, and innovation.

Caldera collapse and flank eruption Real-time monitoring of volcanic eruptions involving caldera-forming events are rare (see the Perspective by Sigmundsson). Anderson et al. used several types of geophysical observations to track the caldera-forming collapse at the top of Kīlauea Volcano, Hawai'i, during the 2018 eruption. Gansecki et al. used near–real-time lava composition analysis to determine when magma shifted from highly viscous, slow-moving lava to low-viscosity, fast-moving lava. Patrick et al. used a range of geophysical tools to connect processes at the summit to lava rates coming out of far-away fissures. Together, the three studies improve caldera-collapse models and may help improve real-time hazard responses. Science , this issue p. eaaz0147 , p. eaay9070 ; p. eaaz1822 ; see also p. 1200

Globally, 800 million people live within 100 km of a volcano thought to have been active in the last 10,000 years. The basis of forecasting the short term progression of volcanic unrest or onset of eruption is high quality monitoring data, ideally analysed in near real time consistently over long time periods. Volcanic deformation – the displacement of the Earth's surface in response to magmatic or volcanic processes – forms the foundation of many monitoring streams in combination with measurements of seismicity and gas emission. At present, < 10% of Holocene volcanoes are monitored routinely, while up to 45% are not monitored at all.

Volcanoes are hazardous to local and global populations, but only a fraction are continuously monitored by ground‐based sensors. For example, in Latin America, more than 60% of Holocene volcanoes are unmonitored, meaning long‐term multiparameter data sets of volcanic activity are rare and sparse. We use satellite observations of degassing, thermal anomalies, and surface deformation spanning 17 years at 47 of the most active volcanoes in Latin America and compare these data sets to ground‐based observations archived by the Global Volcanism Program. This first comparison of multisatellite time series on a regional scale provides information regarding volcanic behavior during, noneruptive, pre‐eruptive, syneruptive, and posteruptive periods. For example, at Copahue volcano, deviations from background activity in all three types of satellite measurements were manifested months to years in advance of renewed eruptive activity in 2012. By quantifying the amount of degassing, thermal output, and deformation measured at each of these volcanoes, we test the classification of these volcanoes as open or closed volcanic systems. We find that ~28% of the volcanoes do not fall into either classification, and the rest show elements of both, demonstrating a dynamic range of behavior that can change over time. Finally, we recommend how volcano monitoring could be improved through better coordination of available satellite‐based capabilities and new instruments.