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A key indicator of potential and ongoing volcanic activity is deformation of a volcano's surface due to magma migrating beneath. The European Sentinel-1 radar archive now contains a large number of examples of volcano deformation, yet the vast majority of subaerial volcanoes are not well monitored. We therefore aim to systematically extract all deformation signals at volcanoes globally, including smaller scale signals associated with processes such as landslides and local changes in hydrothermal systems, which can provide a basis for machine learning approaches to automatically classify and potentially forecast deformation.We have developed an approach to automatically derive high-resolution displacement time series centred on each volcano. To avoid the loss of decorrelated signal in areas of glacial coverage, winter snow and heavy vegetation, we build a highly redundant small baseline network of interferograms tailored to each volcano using coherence tests. We implement an improved phase unwrapping algorithm that separately unwraps signals at different spatial scales, to improve results in decorrelating areas. To mitigate the effect of phase propagation through the atmosphere, we provide multiple atmospheric correction methods, including a spatially-varying scaling method that uses interferometric phase to refine the interpolation of a weather model in time and space.The processed products, stored in a database with annotated metadata (VolcNet), are available for the further interpretation. We show here the volcanic unrest at a large number of volcanoes taken from the database, detected using a machine learning algorithm LiCSAlert. We also show a statistical analysis based on the processed time series for the assessment of volcanic risk.

A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 Mw = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike-slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake-induced landslides. In this study we examine the tsunami potential of the co-seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar-derived displacement fields to estimate a 3D co-seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co-seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co-seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co-seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video-derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co-seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike-slip faults in transtensional basins.

Precursors to volcanic eruptions vary widely between volcanic systems and their individual eruptions. Volcanic systems in Iceland undergoing unrest include the Reykjanes, Svartsengi, Fagradalsfjall, and Krísuvík systems on the obliquely spreading Reykjanes Peninsula. Main precursors prior to the Fagradalsfjall eruptions in 2021 and 2022 were signals associated with the formation of dikes releasing stored tectonic stress over weeks and days, respectively. If volcanic activity occurs at Fagradalsfjall in coming years it may be associated with shorter warning time, as less stored tectonic stress remains. In contrast, the nearby Svartsengi system experienced cumulative uplift of about 15 cm in multiple inflation episodes during 2020 to 2022, modeled as repeating sill intrusions. Prior to, in-between, and following the intrusive events, the surface subsided. We find that the onset of diking accompanied by a sudden increase in seismicity and deformation rates is a likely scenario prior to future eruptions on the Reykjanes Peninsula. A decline in seismicity and/or deformation may occur as unrest activity progresses, as experienced prior to the 2021 and 2022 eruptions. In other areas of Iceland, since 2020 magma storage areas with increasing pressure have been identified at the Askja, Grímsvötn, Krafla, and Bárðarbunga calderas, as well as at Hekla volcano. Increasing pressure buildup in the roots of these volcanoes, is expected to a varying degree prior to next eruption, with different amounts of inflation and seismicity. Tectonic stress release as observed during the 2014/15 Bárðarbunga rifting event may occur or not. The largest capacity for pressure increase is expected at the Askja caldera, where the surface over the magma chamber subsided by more than 1 m from 1983 to 2021, but since August 2021 over 45 cm of uplift has occurred and deformation continues. The amount of subsidence prior to present uplift may indicate the scale of further inflation needed to reach critical conditions, assuming that the current inflation is sourced in a similar crustal volume as the deflation, and the strength of the surrounding material remains similar (e.g., no new faulting/fracturing). Examples of intermittent flow of magma to shallow depth, or pressure increase beneath calderas, occurred during 2017-2018 at Öræfajökull, where a slight increase in seismicity has been detected in recent months, and inflation 2018-2019 at Torfajökull caldera. It remains a challenge to promptly identify seismic swarms that may be indicative of formation of magma feeding conduits versus those indicating intermittent increases in seismic activity due to high stress levels, e.g., caused magma recharging, changes in geothermal activity, or glacial retreat. Experience from the Northern Volcanic Zone and the Reykjanes Peninsula oblique rift, suggest precursory activity may take place simultaneously over wide parts of plate boundary areas, indicating to some extent coupled activity of nearby volcanic systems.

The Alpine-Himalayan Belt (AHB) includes 75 percent of all earthquakes that have killed more than 10,000 people in the past century. Geodetic measurements of crustal deformation provide important information for studying earthquake hazards, indicating how the strain is accumulating and illuminating the mechanics of large-scale continental deformation. The COMET-LiCSAR InSAR processor was designed to automatically produce InSAR products on a global scale [1]. Processed data are made freely available to the community (https://comet.nerc.ac.uk/comet-lics-portal/). With the recent expansion of the system, we aim at generating high-resolution velocity field for the entire AHB. The area is covered by 644 ascending and descending frames. We have processed 130,000 Sentinel-1 epochs in this region and generated more than half a million interferograms. The average length of the connected small baseline network is 6 years. In some sub-regions such as the Anatolia, Caucuses, Iran, Tibet and Tianshan, more than 80 percent of all Sentinel-1 acquisitions are processed. In this study, we first used the LiCBSAS approach [2] to invert for the LOS displacement time-series and velocities. Next, following the VELMAP approach [3], we used the LOS velocities and the GNSS data to solve for the velocities in nodes of a spherical triangle mesh as well as the InSAR reference frame adjustment parameters. This results in the InSAR LOS velocities in a Eurasian reference frame. We finally decomposed these referenced LOS velocities into the east-west and vertical velocities. While the vertical velocities are mainly dominated by the anthropogenic displacements such as water pumping, or any other environmental parameters such as permafrost, the east-west velocity field exhibits the features of the long-wavelength deformation along the major faults in central, east and west of the AHB. References: [1] Lacecky et al., 2020 https://doi.org/10.3390/rs12152430 [2] Morishita et al., 2020 https://doi.org/10.3390/rs12030424 [3] Wang and Wright, 2012 https://doi.org/10.1029/2012GL051222

Forecasting eruption is the ultimate challenge for volcanology. While there has been some success in forecasting eruptions hours to days beforehand1, reliable forecasting on a longer timescale remains elusive. Here we show that magma inflow rate, derived from surface deformation, is an indicator of the probability of magma transfer towards the surface, and thus eruption, for basaltic calderas. Inflow rates ≥0.1 km3/year promote magma propagation and eruption within 1 year in all assessed case studies, whereas rates less than 0.01 km3/year do not lead to magma propagation in 89% of cases. We explain these behaviours with a viscoelastic model where the relaxation timescale controls whether the critical overpressure for dike propagation is reached or not. Therefore, while surface deformation alone is a weak precursor of eruption, estimating magma inflow rates at basaltic calderas provides improved forecasting, substantially enhancing our capacity of forecasting weeks to months ahead of a possible eruption.

Long-term magma storage as a cooler, predominantly crystalline mush provides a reasonable model to represent an inherently complex and heterogeneous overall system. The proposed mush consists of a crystalline framework holding large volumes of interstitial melt and volatiles throughout, whose phase, temperature and geochemistry can vary widely within a single system. This magma mush introduces new complexities to the mechanical response following injection or extraction of melt within a system, especially when directly compared against classical solutions for magma reservoir models. These solutions, such as Mogi (1958), Yang et al. (1988) and McTigue (1987) – represent a simple melt pressure source held within an elastic crust. Accounting for a mush’s crystalline framework introduces poro-elastic rheology into the system, whilst the interstitial melt movement throughout this framework causes visco-elastic behaviour (Dragoni & Magnanensi, 1989; Segall, 2016; Liao et al., 2018, 2021). Physical properties such as melt viscosity, melt and mush compressibility, reservoir and injection depth and reservoir geometry can each affect a system’s dynamic response to perturbation, and consequently how it may present as surface deformation (Segall, 2016; Mullet & Segall, 2022; Alshembari et al., 2022). Using finite element modelling, this research investigates the roles of magma and mush properties, such as compressibility/porosity, viscosity, and injection volume, on post-perturbation deformation. Similarly, the influence of the structure of the magmatic system, in terms of geometry, size and thermal distribution, on any subsequent surface deformation will be explored. These results will be applied against geodetic deformation patterns from regions of suspected existing mush zones globally, to examine any potentially identifiable patterns that may result from subsurface magma migration.

Satellite-based earth observation sensors are increasingly able to monitor geophysical signals related to natural hazards, and many groups are working on rapid data acquisition, processing, and dissemination to data users with a wide range of expertise and goals. A particular challenge in the meaningful dissemination of Interferometric Synthetic Aperture Radar (InSAR) data to non-expert users is its unique differential data structure and sometimes low signal to noise ratio. In this study, we evaluate the online dissemination of ground deformation measurements from InSAR through Twitter, alongside the provision of open access InSAR data from the Centre for Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET) Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR) processing system. Our aim is to evaluate (1) who interacts with disseminated InSAR data, (2) how the data are used and (3) to discuss strategies for meaningful communication and dissemination of open InSAR data. We found that InSAR Twitter activity was primarily associated with natural hazard response, specifically following earthquakes and volcanic activity, where InSAR measurements of ground deformation were disseminated, often using wrapped and unwrapped interferograms. For earthquake events, Sentinel-1 data were acquired, processed, and tweeted within 4.7±2.8 days (shortest was one day). Open access Sentinel-1 data dominated the InSAR tweets and were applied to volcanic and earthquake events in the most engaged with (retweeted) content. Open access InSAR data provided by LiCSAR was widely accessed, including automatically processed and tweeted interferograms and interactive event pages revealing ground deformation following earthquake events. The further work required to integrate dissemination of InSAR data into longer-term disaster risk reduction strategies is highly specific, both to hazard-type, international community of practice, and local political setting and civil protection mandates. Notably, communication of uncertainties and processing methodologies are still lacking. We conclude by outlining the future direction of COMET LiCSAR products to maximise their useability.

We report the first detection of unrest at Socompa, Northern Chile, a stratovolcano which has recorded no eruptions since ~7,200 years ago. We measure deformation at and around Socompa using Interferometric Synthetic Aperture Radar (InSAR) observations between Jan 2018 and Oct 2021. We find that, whilst initially inactive, Socompa shows a steady uplift (17.5 mm/yr) from Dec 2019, independently recorded by near-field continuous Global Positioning System (GPS) data. The data can be fit with pressure increase in an ellipsoidal source region stretching from 1.9 to 9.5 km, with a volume change rate of ~5.8×106 m3/yr. Our observations of the onset of uplift preclude the possibility that a nearby Mw 6.8 deep intraslab earthquake on 3rd June 2020 triggered the unrest. The deformation signal we detect indicates the initiation of unrest at Socompa, after at least two decades without measurable deformation, and many thousands of years without volcanic activity.

Satellite geodesy is capable of observing glacier height changes and most recent studies focus on the decadal scale due to limitations of data acquisition and precision. Glaciers at the Mt. Everest (Qomolangma), locating at the central Himalaya, have been studied from the 1970s to 2015. Here we obtained TerraSAR-X/TanDEM-X images observed in two epochs, a group around 2013 and another in 2017. Together with SRTM observed in 2000, we derived geodetic glacier mass balance between 2000 and 2013 and 2013 and 2017. We proposed two InSAR procedures for deriving the second period, which yields with basically identical results of geodetic glacier mass balance. The differencing between DEMs derived by TerraSAR-X/TanDEM-X shows better precision than that between TerraSAR-X/TanDEM-X formed DEM and SRTM, and it can capable of providing geodetic glacier mass balance at a sub-decadal scale. Glaciers at the Mt. Everest (Qomolangma) and its surroundings present obvious speeding up in mass loss rates before and after 2013 for both the Chinese and the Nepalese sides. The previous obtained spatial heterogeneous pattern for glacier downwasting between 2000 and 2013 generally kept the same after 2013. Glaciers with lacustrine terminus present the most rapid lost rates.

One main challenge in detecting built-up land cover changes using synthetic aperture radar (SAR) instruments is that complicated backscattering behaviours and the superimposition of speckles on rich textures cause a large number of false alarms. Using trajectory-based analyses from time-series SAR imagery can mitigate false alarms since the temporal variability in backscattering during construction improves discrimination capability. This paper presents an approach towards the detection of built-up land change based on a single-channel SAR stack. The proposed methodology includes the generation of a change indicator, the Markov modelling procedure and the delineation of changes over built-up areas. The generation of the change indicator aims to provide a feature with abundant contrast between changed and stable areas, a high signal-to-noise ratio and detail preservation. To this end, all temporal information is converted into a map of the coefficient of variation. After error removal, this change detector is combined with a Markov random field (MRF) criterion function. Rather than MRF modelling by iteration with very complex stochastic models, we propose using SAR temporal trajectory under a hypothesis test framework and interferometric coherence series to establish conditional density for each class. Then, the Graph-cuts theory is applied to delineate the boundary between changed and stable areas, followed by a binary classification procedure based on speckle divergence to exclude natural areas. The technique is tested on both synthetic data and two TerraSAR-X datasets covering representative areas with rich texture. We found that in a complex built environment that is challenging for classical change indicators and state-of-the-art techniques, the presented method can provide smaller overall error with better detail preservation.

There are potentially dangerous areas where InSAR technology cannot be applied routinely in the absence of proper persistent or distributed scatterers. Here, we planned and investigated the use of truncated trihedral triangle corner reflectors (CRs) oriented to ascending and descending directions for Sentinel-1 orbit, which were mounted on the optimal concrete basement including an additional global navigation satellite system (GNSS) adapter. These integrated benchmarks were designed to produce a signal-to-clutter ratio of about 100 (i.e., 20 dB). The mechanical design allows optimal orientation of the reflectors and resistance against dynamic effects. We investigated 1:5 models of the CRs and integrated benchmarks in an anechoic chamber to estimate the effects of truncation and the interference of the twin reflectors. The main effect of the interference is the asymmetric monostatic radar cross section, which can be neglected. The integrated benchmarks were also investigated in two recent landslide areas in Hungary using Sentinel-1 single look complex (SLC) scenes, which confirmed that the preliminary requirements can be met.

SUMMARY We consider the viscoelastic rheology of the solid Earth under the Antarctic Peninsula due to ice mass loss that commenced after the breakup of the Larsen-B ice shelf. We extend the previous analysis of nearby continuous GPS time-series to include five additional years and the additional consideration of the horizontal components of deformation. They show strong uplift from ∼2002 to 2011 followed by reduced uplift rates to 2018. Modelling the GPS-derived uplift as a viscoelastic response to ongoing regional ice unloading from a new ice model confirms earlier estimates of low upper-mantle viscosities of ∼0.3–3 × 1018 Pa s in this region but allows a wide range of elastic lithosphere thickness. The observed and modelled north coordinate component shows little nonlinear variation due to the location of ice mass change to the east of the GPS sites. However, comparison of the observed and modelled east coordinate component constrains the upper-mantle viscosity to be less than ∼9 × 1018 Pa s, consistent with the viscosity range suggested by the uplift rates alone and providing important, largely independent, confirmation of that result. Our horizontal analysis showed only marginal sensitivity to modelled lithospheric thickness. The results for the horizontal components are sensitive to the adopted plate rotation model, with the estimate based on ITRF2014 suggesting that the sum of residual plate motion and pre-2002 glacial isostatic adjustment is likely less than ∼±0.5 mm yr−1 in the east component.

Harmonic tremor, ground vibrations captured by seismometers oscillating in different frequencies, has been widely identified as a result of distinct physical processes. In volcanic areas, the physical processes to explain the gliding spectral lines are usually identified preceding/accompanying eruptions. Less is known about harmonic tremor that occurs in active volcanic areas but does not end in an eruption. In this study we analyse a harmonic tremor signal with a spectral behaviour that, to our knowledge, has not previously been observed. We observed the harmonic signal in the vertical component spectrogram of 22 out of the 24 broad-band seismometers placed around and within Torfajökull caldera, in Iceland. The discovery was made while estimating a tomographic image of the volcano using a network of seismometers operating for nearly 3 months in summer 2005. a function of frequency and time, the detected harmonic signal has a parabola structure (or a ‘V’ shape) with a fundamental frequency and a few overtones exhibiting higher energy. The fundamental mode glides upward from frequencies below 1Hz up to and above 25 Hz and can take up to 10h from the minimum to the maximum achieved frequency. A few low and high-frequency tremors also occurred during the gliding of the harmonic signal. In an exploratory phase, we ruled out phenomena of anthropogenic (drilling, helicopters) and natural non-volcanic origins (colliding ice structures, tidal, magnetic field, rain, wind, aurora) due to the time and frequency characteristics of the signal. We then analyzed the temporal and spatial distribution of the harmonic tremors (signal of interest). Automatic detection was leading to a large number of false positives and true negatives, therefore we performed a manual classification of daily spectrograms to detect the ‘V’ shaped signal. We select the events where the high amplitude spectra were reaching below 2 Hz. The occurrence and strength of the harmonic signal are variable in time and space. The spatial density of signal occurrence does not correlate with the location of the source of subsidence we estimate from InSAR; the detected subsidence of ~13 mm/year is confined to the caldera outline while the harmonic events were registered mostly at seismometers outside the volcano caldera. The detected signal does correlate well with areas of low topography and identified low-velocity S-wave anomalies from the derived ambient noise seismic tomography model using the same seismic network. While the correlation with low topography may indicate preferred water paths, the low S-wave velocity anomalies may indicate the presence of a heat source, leading to a water-magma interaction hypothesis. Finally, we tested for the hypothesis of a resonance set up in magmatic conduits after magma-water interaction and changes in speed flow through conduits assuming the geometries of dykes, tubes and cracks.

The 2021 effusive eruption at Mt. Fagradalsfjall, on the Reykjanes Peninsula oblique rift in Iceland, was preceded by a 14-month long period of volcano-tectonic unrest (comprising both significant ground deformation and intense seismicity). A seismic swarm was initially detected in the Fagradalsfjall region between the 15th to 20th December 2019. Following a short quiescence, activity re-commenced on the 21st January 2020, with a small cluster of earthquakes near Grindavík (~ 10 km west of Fagradalsfjall). Concurrent deformation was detected on two GNSS stations in this area and on Sentinel-1 interferograms. Geodetic modelling of these observations indicated the deformation most likely resulted from the intrusion of a magmatic sill, directly west of Mt. Thorbjörn, at a depth of about 4 km. This was followed by two additional sill-type intrusions in a similar location, between 6th March - 17th April and 15th May - 22nd July 2020 respectively. The three intrusions comprised a total volume change of about 9 million cubic meters. In mid-July 2020, inflation was again detected on the Reykjanes Peninsula, this time in the Kýsuvík volcanic system to the east of Fagradalsfjall. This episode of inflation lasted several weeks and geodetic inversions indicated the observed signal was produced by the combination of a deflating sill-like source at a depth of ~16 km and inflation of a body at a depth of ~6 km. The latter, corresponding to a volume change of about 5 million cubic meters. During this period of intrusive activity, seismicity shifted along various regions across the Peninsula, in relation to a combination of processes – magma migration, triggered seismicity and tectonic earthquakes. Intense seismic swarms commenced on the 24th February 2021, concentrated at both Fagradalsfjall and also extending across a 20 km segment along the plate boundary – including triggered strike-slip earthquakes up to Mw5.64. At the same time, deformation was detected on local GNSS stations, and subsequent Interferometric Sythethic Aperture Radar Analysis (InSAR) of Sentinel-1 data confirmed the observed deformation was primarily the result of a dike intrusion and slip along the plate boundary. Geodetic inversions indicated a ~9 km long dike with a total intruded volume of around 34 million cubic meters (Sigmundsson et al., in review). During this period, stored tectonic stress was systematically released, resulting in a decline in deformation and seismicity over several days preceding the eruption onset, on 19th March 2021 in Geldingadalir at Mt. Fagradalsfjall. The eruption continued until the 18th September 2021 and produced a lava field covering an area of 4.8 km2 with an extruded bulk volume of 150 ± 3 × 106 m3 (Pedersen et al., in review). ReferencesSigmundsson et al. (in review). Deformation and seismicity decline preceding a rift zone eruption at Fagradalsfjall, Iceland. Pedersen et al. (in review). Volume, effusion rate, and lava transport during the 2021 Fagradalsfjall eruption: Results from near real-time photogrammetric monitoring. DOI:10.1002/essoar.10509177.1.

Geodetic observations during volcanic eruptions are important to constrain from where the eruptive products originate in the sub-surface. Some eruptions are sourced from magma reservoirs shallow in the crust, whereas others may tap magma directly from the mantle. The 2021 Fagradalsfjall eruption took place on the Reykjanes Peninsula, Iceland, during March 19 to September 18, resulting in approximately 0.15 km3 of erupted basaltic lava. A wide-spread crustal subsidence and inward horizontal motion, centered on the eruptive site, was observed during the eruption. Nearest to the emplaced lava flows, additional localized subsidence is observed due to the loading of the lavas. The regional subsidence rate varied during the eruption: it was low in the beginning and then increased, in broad agreement with changes in the bulk effusive rate. In this study we use GNSS and InSAR data to model the deformation source(s) during different periods of the eruption, primarily aiming to resolve the depth and volume change of the magma source. We furthermore calculate crustal stress changes during the eruption and compare to the regional seismicity.

At the beginning of August 2021, inflation was detected at Askja volcano, on a continuous GNSS station located to the west of Öskjuvatn and on interferograms generated using data from four separate Sentinel-1 tracks. Ground deformation measurements at Askja commenced in 1966 with levelling observations and since this time additional ground monitoring techniques have been employed, including GNSS and Satellite interferometry (InSAR) to detect long-term changes. Ground levelling measurements undertaken between 1966-1972 revealed alternating periods of deflation and inflation. Measurements from 1983-2020 detailed persistent subsidence of the Askja caldera, initially at an inferred rate of 7 cm/yr, decaying in an exponential manner. Suggested explanations for the long-term subsidence include magma cooling and contraction, or withdrawal of magma – eventually facilitated by an extensive magma-rich plumbing system, with an open conduit between the uppermost and the deeper parts of the magmatic system. This presentation will focus on the recent period of uplift and provide an overview of the GNSS and InSAR observations to date and present the latest geodetic modelling results which describe the best-fit source for the observed deformation.

Geodetic measurements of crustal deformation can provide crucial constraints on a region’s tectonics and seismic hazard. An ideal is for these measurements to be able to directly image deformation well enough (at the surface) that the remaining uncertainty is largely about its depth extent. For this, geodetic measurements need to be five things: spatially dense (on the scale of individual faults), spatially wide-ranging (enough to capture the entirety of strain signals), temporally dense (enough that noise and nuisances can be understood), temporally wide-ranging (enough to bring out gradual interseismic deformation), and accurate. Sentinel-IA InSAR, as processed through large-scale workflows like the COMET-LiCS system and when combined with high-quality GNSS data, is arguably the first geodetic dataset with the potential to be all five. We are using this combination to construct high-resolution maps of crustal deformation and strain across the Alpine-Himalayan Belt. In the Anatolia-Caucasus region, we resolve the large-scale deformation patterns of the North Anatolia and East Anatolian Faults, and a deformation front extending northeastward from their intersection into the Caucasus that is consistent with the locations of large earthquakes. Taking this relationship further, we pair the strain rate map with the Turkish and ISC-GEM seismic catalogues to estimate the recurrence intervals of large, moderate and small earthquakes throughout the Anatolia-Caucasus region assuming conservation of seismic moment. On the North Anatolian Fault, we find that this balance is consistent with the ~250-year recurrence interval between the last two earthquake sequences.

Assessing the distribution of seismic hazard in the continents requires an understanding of how much deformation is accommodated by major faults. In one view, upper-crustal seismogenic faults respond passively to continuous viscous deformation of the underlying lithosphere; the alternative model is that lithospheric-scale faults control the distribution of deformation and hazard. We combine InSAR data derived from automatic (COMET-LiCSAR) processing of Sentinel-1 data (2015-2021) with a compilation of velocities from GNSS stations to produce the first high-resolution surface velocity field for the Tibetan plateau, where the collision of rigid Indian lithosphere with Eurasia has created the largest deforming region on the planet. We tie the reference frame of InSAR line-of-sight velocities to Eurasia using a joint inversion for surface velocities on a triangular mesh and reference frame adjustment parameters following the approach described in Wang and Wright 2012. We use the referenced InSAR data to invert for high-resolution East-West and Vertical velocities. The results show that the internal deformation of the Tibetan plateau can be described as a combination of distributed deformation and focused strain on a few major faults (Altyn Tagh, Kunlun, Haiyuan, Xianshuihe). We also observe continued postseismic transients associated with earthquakes that occurred within 20 years of the observations, including the 2001 Kokoxili and 1997 Manyi earthquakes. The highest elevations of the Tibetan plateau show dilatation, demonstrating the importance of internal buoyancy forces in continental tectonics. We present a new dynamic model that can explain the key features of the observations.

Asset owners responsible for the management and maintenance of bridges value the collection of data that can be processed into useful information to inform decisions about future management of structures. Installing, powering and receiving data from sensors is not always convenient or possible, but satellite monitoring may provide the ability to measure bridge movements and thus provide an indication of potential problems for asset owners to take action on. This study presents the results of satellite monitoring of the Hammersmith flyover, London, UK, using the interferometric synthetic-aperture radar (InSAR) technique. Sentinel-1 (free) and Cosmo-SkyMed (commercial) satellite radar data were processed to provide millimetre-scale measurements of the flyover and surrounding region and validated with in situ sensor measurements. A method was developed for selecting and comparing InSAR measurements with in situ displacement and temperature measurements, making use of bridge geometrical and structural modelling information. The results compare in situ sensor measurements with remote InSAR measurements and show the suitability of such measurements in measuring thermal expansion for some (but not all) bridge assets. The proposed techniques, illustrated with the case study of the Hammersmith flyover, will enable asset owners to collect regular measurements of bridge movements to complement and add value to current inspection methods and potentially give early warning to defective bridge bearings.

Using magma inflow rate improves eruption forecasting on timescales of weeks to months for basaltic caldera systems, compared with using surface deformation alone, according to analysis of 45 unrest case studies and viscoelastic modelling.Forecasting eruption is the ultimate challenge for volcanology. While there has been some success in forecasting eruptions hours to days beforehand, reliable forecasting on a longer timescale remains elusive. Here we show that magma inflow rate, derived from surface deformation, is an indicator of the probability of magma transfer towards the surface, and thus eruption, for basaltic calderas. Inflow rates >= 0.1 km(3) yr(-1) promote magma propagation and eruption within 1 year in all assessed case studies, whereas rates