Our ability to measure the deformation at the Earth's surface over a range of spatial and temporal scales is vital for understanding seismic hazard, detecting volcanic unrest and assessing the impacts of vertical land movements (VLM) on sea level rise. Here, we combine 9-years of Sentinel-1 InSAR observations and continuous GNSS timeseries to build a high-resolution (1-km) national timeseries and velocity field of New Zealand from 2017 to January 2026. Utilising the higher spatial and temporal observations provided by Sentinel-1, we provide an updated estimate of the coastal VLM following the Kaikōura earthquake at 50–100 m resolution including updated estimates of the uncertainty and temporal variability.

Surface velocities and strain rates from satellite geodesy have become essential tools for understanding the dis tribution of tectonic deformation, faulting and seismic hazard. However, across large regions of distributed continental deformation, such as the Alpine-Himalayan Belt, data are only sparsely available. While previous studies have mainly used spatially sparse GNSS to measure deformation at such large scales, these approaches cannot characterize shorter wavelength features of deformation in many places. We use Sentinel-1 radar images acquired during 2016-2024 to provide trans-national average surface velocities and time series at 1 km spa tial resolution stretching a distance of over 11,000 km from south-western Europe to eastern China, covering an area more than 20 million square kilometres. We produce the velocity field by combining data from over 222,000 Sentinel-1 SAR images with a new belt-wide compilation of GNSS velocities, all combined in a consistent Eurasian reference frame. Horizontal strain rates are derived from gradients of the velocity field, yielding near-continuous spatial deformation information over the entirety of the largest deforming region on the planet. The horizontal velocities and strains are dominated by tectonic deformation, which has a bimodal behaviour-focused on major faults but distributed elsewhere. Shorter-wavelength vertical velocities are dominated by non-tectonic processes, in particular the widespread over-exploitation of groundwater. Our new velocity and strain rates are foundational data sets that reveal the details of how the continents deform for the first time at trans-continental scale.

Earthquakes release strain energy that has accumulated between seismic events. Measuring strain accumulation rates is critical for understanding earthquake cycle and assessing earthquake potential, with fault slip rates serving as essential inputs for seismic hazard models. However, the Tibetan Plateau has been lacking comprehensive estimates of geologic slip rates on numerous faults. To address this gap, geodetic data have been invoked to derive fault slip (or slip deficit) rates using various methodologies. These include the commonly adopted classic and deformable block modelling approaches (Meade & Loveless, 2009) and the newly developed direct inversion of geodetic strain rates (Johnson et al., 2022), which has the advantage of not requiring blocks to be defined. A comprehensive comparison of slip rates obtained from these different geodetic methods has been notably absent.In this study, we focus on the southeastern Tibetan Plateau, utilising Sentinel-1 satellite data from 35 ascending and 32 descending frames spanning the period between 2014 and 2023, along with published GNSS velocities. We constructed high-resolution (1 km) maps of velocity and strain rate fields covering 1.3 million km2. Using these maps, we derived slip rates on newly mapped faults (Styron, 2022) using classic block modelling, “deformable block” modelling, and by the direct inversion of strain rates. Our strain rate fields reveal a partition through focused shear on the Kunlun fault, the Xianshuihe-Xiaojiang fault system, the Longriba fault, the Longmenshan fault possibly influenced by the ongoing postseismic deformation of the 2008 Mw 7.9 Wenchuan earthquake, and the Lijiang-Xiaojinhe fault. On the deforming plateau there is diffuse deformation away from the major faults, with average shear strain and dilatation rates of 14.3 and 13.1 nanostrain/year, compared to 9.4 and 11.1 nanostrain/year in the Sichuan basin (which likely reflects the noise floor in the data). The geodetically-determined slip rates from the three methods generally align with available geologic rates, particularly along-strike variations on the Kunlun fault and the Xianshuihe-Xiaojiang fault system. Our block model consists of 103 blocks bounded by 326 fault sections in the southeastern Tibetan Plateau. The model is constrained by the combined geodetic horizontal velocities from 6617 observation points. Classic block modelling without considering internal strain tends to overestimate slip rates on faults that slip faster than 5 mm/yr, compared to deformable block model that accounts for homogeneous intrablock strain, constituting 5% of the total. The two block models explain approximately 45-50% of the geodetic strain, predicting focused strain on block boundaries even in the absence of observed strain concentrations. By directly inverting strain rates, we suggest that 40-50% of the geodetic strain is attributable to elastic coupling (back slip) on faults, while the remaining can be explained by off-fault distributed moment sources (body forces) in a thin elastic plate. We discuss limitations of different geodetic approaches in modelling deformation (velocities or strain rates) and implications for seismic hazard by comparing the seismic moment release rate from earthquakes and the geodetic moment accumulation rate from our geodetic models.

The distribution and magnitude of forces driving lithospheric deformation in the India‐Eurasia collision zone have been debated over many decades. Here we test a two‐dimensional (2‐D) Thin Viscous Shell approach that has been adapted to explicitly account for displacement on major faults and investigate the impact of lateral variations in depth‐averaged lithospheric strength. We present a suite of dynamic models to explain the key features from new high‐resolution Sentinel‐1 Interferometric Synthetic Aperture Radar as well as Global Navigation Satellite System velocities. Comparisons between calculated and geodetically observed velocity and strain rate fields indicate: (a) internal buoyancy forces from Gravitational Potential Energy acting on a relatively weak region of highest topography (>2,000 m) contribute to dilatation of the high plateau and contraction on the margins; (b) a weak central Tibetan Plateau (∼1021 Pa s compared to far‐field depth‐averaged effective viscosity of at least 1022–1023 Pa s) is required to explain the observed long‐wavelength eastward velocity variation; (c) localized displacement on fault systems enables strain concentration and clockwise rotation around the Eastern Himalayan Syntaxis. We discuss the tectonic implications for rheology of the lithosphere, distribution of geodetic strain, and partitioning of active faulting and seismicity.

The dynamics of lithospheric deformation in the India-Eurasia collision zone has been debated over many decades. Here we test a two-dimensional (2-D) Thin Viscous Shell (TVS) approach that has been adapted to explicitly account for displacement on major faults and investigate the impact of lateral variations in depth-averaged lithospheric strength. We present a suite of dynamic models to explain the key features from new high-resolution Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) as well as Global Navigation Satellite System (GNSS) velocities. Comparisons between calculated and geodetically observed velocity and strain rate fields indicate: (a) internal buoyancy forces from Gravitational Potential Energy (GPE) acting on a relatively weak region of highest topography (>2,000 m) contribute to dilatation of the high plateau and contraction on the margins; (b) a weak central Tibetan Plateau ~10^21 Pa s compared to far-field depth-averaged effective viscosity of 10^22 to 10^23 Pa s) is required to explain the observed long-wavelength eastward velocity variation away from major faults; (c) resisted slip on faults produces strain localization and clockwise rotation around the Eastern Himalayan Syntaxis (EHS). We discuss the tectonic implications for the rheology of the lithosphere, distribution of geodetic strain, and partitioning of active faulting and seismicity.

In August 2021, Askja volcano in Iceland experienced a sudden onset of rapid uplift that followed decades of continuous subsidence. We review the extensive microgravity record from Askja, revisiting data recorded between 1988 and 2017, and presenting new microgravity data from 2021 and 2022 that were collected after the uplift had started. Based on our findings, we provide a comprehensive set of recommendations that should be followed for optimal microgravity data collection and treatment in volcano monitoring. Without such standards, it becomes increasingly challenging to interpret the microgravity results in terms of volcanic processes. At Askja, from 1988 – 2016, exponentially decaying surface subsidence was accompanied by a microgravity decrease, potentially signaling the contraction of its magma chamber, eviction of magma to deeper levels, or other density-decreasing processes. Following this, between 2016 and 2021, a gravity increase occurred in the center of the caldera which effectively annuls the microgravity decrease detected between 1988 and 2016. This increase took place either during subsidence or leading up to and during the uplift, and may potentially be explained by mass accumulation below the caldera. After August 2021, gravity changes follow the free-air gradient, despite continuing deformation with a total uplift of up to 40 cm, suggesting subsurface density decreases as a driving process. Such a process could be envisaged as the previously emplaced intrusion before 2021 that is now undergoing magma vesiculation, is causing a change in the hydrothermal system, or represents the replacement of dense basaltic magma with less dense rhyolitic magma. However, uncertainties for these data are large (50μGal) and small mass intrusions contributing to the uplift may remain undetected. The driving mechanism for the uplift remains enigmatic and future microgravity campaigns will help shed light on its nature.

In the continents, the importance of earthquakes that occur away from major block-bounding faults is still debated. The 21 May 2021 M-W similar to 7.4 Maduo earthquake occurred on a secondary fault away from previously-identified major block boundaries. Here we use 7 years of Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) time series (between October 2014 and November 2021) to determine the distribution of coseismic slip and early postseismic afterslip following the Maduo earthquake, and the preceding interseismic strain accumulation. We devised a 13-segment 3-D fault geometry constrained by the SAR range offsets and the distribution of relocated aftershocks and used a Bayesian method incorporating von Karman regularization to solve for coseismic slip and afterslip models. We also used teleseismic waveforms as a standalone inversion to show the rupture evolution in space and time during the earthquake, finding that it propagates bilaterally with three notable rupture episodes. Our preferred coseismic self-similar slip model shows a moderate shallow slip deficit, with the majority of moment release occurring in the depth interval of 1-10 km. The coseismic slip deficit is taken up in part by afterslip at shallow (< 4 km) depths that grows linearly with time during the first similar to 6 months, and at > 10 km depths where afterslip grows logarithmically with time. We suggest that this heterogeneity is likely controlled by spatial variations in fault friction related to lithology. We discuss the implications for seismic hazard away from major tectonic block boundaries in light of our observations of the earthquake cycle on this intrablock fault.

The European Commission’s Sentinel-1 constellation, operated by ESA, has been a game changer for operational monitoring of our hazardous planet. When fully operational, the Sentinel-1 mission is a two-satellite constellation; currently consisting of Sentinel-1A (launched in 2014) and Sentinel-1B (launched in 2016), the mission provides at least one SAR image for the whole land surface every 12 days, with both ascending and descending data acquired in tectonic/volcanic areas globally every 12 days, and images acquired in both geometries every 6 days over all of Europe. The narrow orbital tube, consistent imaging geometry, and long time series are optimised for ground deformation measurements with InSAR. Sentinel-1C and -1D have been built and will replace the existing satellites in due course. Perhaps the most important game changer has been the Copernicus data policy, which mandates fully free and open distribution of Sentinel-1 products for all applications, whether they are for research or commercial purposes. Sentinel-1 InSAR data has quickly become the primary data set for monitoring ground movement in our hazardous planet. Several research organisations/collaborations now process enormous quantities of Sentinel-1 data to produce deformation products that are made freely available through organisations like COMET in the UK, EPOS and the new European Ground Motion Service in Europe, and the Alaska SAR Facility in the US. Commercial providers are processing data at scales ranging from individual bridges/dams through to whole countries. In this presentation we will focus on Sentinel-1 results produced academically by COMET and commercially by SatSense Ltd. COMET now responds routinely to all continental earthquakes bigger than M5.5 and provides interactive tools and machine-learning-based alerting for global volcanoes. COMET is combining Sentinel-1 InSAR with GNSS to map tectonic strain at high spatial resolution on a continental scale, in areas including Anatolia, Tibet and Iran, and using the results to improve our understanding of seismic hazard. SatSense have demonstrated the value of Sentinel-1 InSAR for applications including dam monitoring, water pipe failures and railway infrastructure. The SatSense processing approach allows InSAR ground movement data to be kept continuously up to date for entire countries. We conclude the presentation by discussing prospects for the future of InSAR beyond Sentinel-1.

This article contains description of an improved tool for phase unwrapping, as developed and to be applied routinely within COMET LiCSAR system producing Sentinel-1 interferograms in 0.001° resolution (WGS-84). We apply existing standard methods on routinely available data in a way to improve reliability of the standard phase unwrapping procedure and increase coverage of unwrapped pixels. The primary idea is to reduce high phase gradients, causing both decorrelation and zonal unwrapping errors, by extracting and unwrapping long-wave spatial signal (extracted by a combination of multilooking and Gaussian filtering) and signal related to atmosphere that can be modeled (e.g. using COMET GACOS data or by correlation of phase with a DEM). We show the effect of the improved approach is significant in standard time series processing (here using LiCSBAS).

In August 2021 Askja caldera in Iceland started to show uplift after decades of subsidence. The uplift signal is centered at the northwestern edge of lake Ӧskjuvatn and an order of magnitude larger than the subsidence in the last decade. In September 2021 a geodesy campaign was carried out at Askja, including relative microgravity measurements acquired with the use of two Scintrex CG-5 instruments. Relative microgravity campaigns at Askja are not straightforward due to the long walking distances between sites, which makes a “double loop” procedure impossible. We revisit existing Scintrex relative microgravity data sets (2015 onward) and analyse data using the same joint weighted least squares inversion routine. We define recommendations for future relative microgravity campaigns at Askja which will be important to establish the cause of the ongoing uplift. The density of subsurface magma is only identifiable with microgravity data. Knowledge of the type of magma accumulating under Askja is vital to assess possible hazard implications.

With the advances of ESA’s Sentinel-1 InSAR (Interferometric Synthetic Aperture Radar) mission there are freely available remote sensing ground deformation observations all over the globe that allows continuous monitoring of natural hazards and structural instabilities. The Digital Environment initiative in the UK aims to include these remote sensing data in the effort of forecasting and mitigating hazards across the UK. However, analyses of low coherence areas (e.g. forested and vegetated areas) with conventional InSAR methodologies are difficult to perform due to the limiting factor of temporal and geometric decorrelation. Even the application of the permanent scatterer (PS) technique may not be successful when there is a low density of stable radar targets. Using artificial reflectors with high radar cross section (RCS) can be a way of overcome this limitation and achieve measurements with a good signal-to-clutter ratio (SCR). In order to be able to include Sentinel-1 data in the UK’s Digital Environment it is important to understand the advantages and limitations of these observations and interpret them appropriately. The Hollin Hill landslide observatory in North Yorkshire is used by the British Geological Survey in their efforts to understand landslide processes, and to trial new technologies and methodologies for slope stability characterisation and monitoring. We present InSAR results of the Hollin Hill landslide where a variety of ground-based geophysical measurements (e.g. GPS, Electric resistivity tomography, meteorological observations) are available for comparison with InSAR data. We use Sentinel-1 InSAR data acquired between Oct 2015 and Jan 2021 to study the behaviour of this landslide. We find that the Line of Sight component of the down-slope movement is 2.7 mm/yr in the descending track, and 7.5-7.7 mm/yr in the ascending track. The InSAR measurements also highlight the seasonal behaviour of this landslide. In July 2019 six corner reflectors were installed to improve the coherence of the InSAR measurements, especially in the ascending acquisition mode. We present comparison with ground-based measurements such as the movement recorded by the GPS measurements of the pegs of the ERT survey or the moisture recorded by the various instruments at the site, and show the improvement introduced by the corner reflectors. In addition we present results of an experiment that explores the use of smaller corner reflectors for potential urban applications of infrastructure monitoring. A single corner reflector needs to be at least ~67cm wide and tall to be seen by the Sentinel-1 satellites. We show that by placing 4 reflectors with 33cm dimensions in the same pixel coherent signal can be acquired. It is feasible to install small reflectors on bridges, tall buildings, or incorporate “corner-like” features in newly built structures,but care needs to be taken on the precise spacing of the reflectors to avoid destructive interference. Continuous monitoring of infrastructure with remote sensing and machine learning can alert to potential failures where further investigation is needed.

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.

For the past five years, the 2-satellite Sentinel-1 constellation has provided abundant and useful Synthetic Aperture Radar (SAR) data, which have the potential to reveal global ground surface deformation at high spatial and temporal resolutions. However, for most users, fully exploiting the large amount of associated data is challenging, especially over wide areas. To help address this challenge, we have developed LiCSBAS, an open-source SAR interferometry (InSAR) time series analysis package that integrates with the automated Sentinel-1 InSAR processor (LiCSAR). LiCSBAS utilizes freely available LiCSAR products, and users can save processing time and disk space while obtaining the results of InSAR time series analysis. In the LiCSBAS processing scheme, interferograms with many unwrapping errors are automatically identified by loop closure and removed. Reliable time series and velocities are derived with the aid of masking using several noise indices. The easy implementation of atmospheric corrections to reduce noise is achieved with the Generic Atmospheric Correction Online Service for InSAR (GACOS). Using case studies in southern Tohoku and the Echigo Plain, Japan, we demonstrate that LiCSBAS applied to LiCSAR products can detect both large-scale (>100 km) and localized (~km) relative displacements with an accuracy of <1 cm/epoch and ~2 mm/yr. We detect displacements with different temporal characteristics, including linear, periodic, and episodic, in Niigata, Ojiya, and Sanjo City, respectively. LiCSBAS and LiCSAR products facilitate greater exploitation of globally available and abundant SAR datasets and enhance their applications for scientific research and societal benefit.

Improving our understanding of volcanic hazards requires better knowledge of the location, volume and properties of magma bodies in the roots of active volcanoes, as well as information on melt supply and magma transfer. This requires a good understanding of both the geometric structure of the volcanic and igneous plumbing system, as well as observations of sub-surface magma movements and their interpretation. Arrival of new magma in volcano roots often causes volcanic unrest expressed by one or more of the following: increased seismicity, ground deformation, volcanic gas release and ground temperature changes. Recent eruptions and magmatic events in Iceland have provided opportunities to apply repeated geodetic observations at volcanoes to measure ground deformation and interpret these measurements together with seismic observations in terms of subsurface magmatic processes.

Combining persistent scatterers (PS) and distributed scatterers (DS) is important for effective displacement monitoring using time-series of SAR data. However, for large stacks of synthetic aperture radar (SAR) data, the DS analysis using existing algorithms becomes a time-consuming process. Moreover, the whole procedure of DS selection should be repeated as soon as a new SAR acquisition is made, which is challenging considering the short repeat-observation of missions such as Sentinel-1. SqueeSAR is an approach for extracting signals from DS, which first applies a spatiotemporal filter on images and optimizes DS, then incorporates information from both optimized DS and PS points into interferometric SAR (InSAR) time-series analysis. In this study, we followed SqueeSAR and implemented a new approach for DS analysis using two-sample t-test to efficiently identify neighboring pixels with similar behaviour. We evaluated the performance of our approach on 50 Sentinel-1 images acquired over Trondheim in Norway between January 2015 and December 2016. A cross check on the number of the identified neighboring pixels using the Kolmogorov–Smirnov (KS) test, which is employed in the SqueeSAR approach, and the t-test shows that their results are strongly correlated. However, in comparison to KS-test, the t-test is less computationally intensive (98% faster). Moreover, the results obtained by applying the tests under different SAR stack sizes from 40 to 10 show that the t-test is less sensitive to the number of images.

Multitemporal polarimetric synthetic aperture radar (SAR) data can be used to estimate the dominant scattering mechanism of targets in a stack of SAR data and to improve the performance of SAR interferometric methods for deformation studies. In this letter, we developed a polarimetric form of amplitude difference dispersion (ADD) criterion for time-series analysis of pixels in which interferometric noise shows negligible decorrelation in time and space in small baseline algorithm. The polarimetric form of ADD is then optimized in order to find the optimum scattering mechanism of the pixels, which in turn is used to produce new interferograms with better quality than single-pol SAR interferograms. The selected candidates are then combined with temporal coherency criterion for final phase stability analysis in full-resolution interferograms. Our experimental results derived from a data set of 17 dual polarizations X-band SAR images (HH/VV) acquired by TerraSAR-X shows that using optimum scattering mechanism in the small baseline method improves the number of pixel candidates for deformation analysis by about 2.5 times in comparison with the results obtained from single-channel SAR data. The number of final pixels increases by about 1.5 times in comparison with HH and VV in small baseline analysis. Comparison between persistent scatterer (PS) and small baseline methods shows that with regards to the number of pixels with optimum scattering mechanism, the small baseline algorithm detects 10% more pixels than PS in agricultural regions. In urban regions, however, the PS method identifies nearly 8% more coherent pixels than small baseline approach.

Within this study we tested a combination of processing tools in order to overcome certain limitations of Advanced Differential Interferometrie SAR (A-DInSAR) for the detection of intraplate surface motion. The study area is located over the Hyblean Plateau in south-east Sicily, Italy. Instead of usually applied spatio-temporal smoothing of the stacked dataset, we calculated the atmospheric contribution within the interferometrie signal by external data from the global meteorological model ERA-INTERIM. Furthermore we enhanced the coverage of the mean line-of-sight velocity by gap filling and applied a multi-directional filter. For this we used ENVISAT ASAR imagery (49 scenes descending and 58 scenes ascending orbit). The output was then integrated with local GPS data into the SISTEM framework to decompose the measurements into a 3-dimensional velocity field. While in areas of no GPS stations, detected deformation is not precise enough, the results in areas of good GPS coverage look promising with accuracies down to 1 mm/y and various zones of surface deformation could be detected successfully.

The Arctic environment offers the biggest challenge for In-SAR; huge seasonal change, ice and snow cover for much of the year, and large variations in soil moisture. Yet the Arctic is often seen as a barometer for climate change and therefore being able to exploit technologies such as InSAR provides invaluable information not only for the communities involved, but also for climate change science as a whole. Furthermore, InSAR's unmatched spatial coverage make it an obvious choice for covering vast landmasses such as the Canadian Archipelago.

FUTUREVOLC is a collaborative project funded through the FP7 Environment Supersite Concept call encompassing 26 partners in 10 countries. The main objectives of FUTUREVOLC are to establish an integrated volcanological monitoring procedure through European collaboration, develop new methods to evaluate volcanic crises, increase scientific understanding of magmatic processes and improve delivery of relevant information to civil protection and authorities. FUTUREVOLC is in the first of its 3.5 year duration, therefore this paper presents aims and expectations rather than results.