Understanding the properties of magmatic plumbing systems beneath active volcanoes is crucial to better characterise volcanic processes at both local and global scales. Locally, this helps identify crustal reservoirs, determine magma supply rates, and map migration processes throughout the eruptive cycle – information that directly informs our scientific understanding of volcanic processes, improves volcanic-hazard mapping, and supports the development and management of geothermal resources. Globally, such insights improve our understanding of how these systems interact within the solid Earth, oceans, and atmosphere.

Despite its importance, directly measuring the Earth’s subsurface remains a challenge. Deformation measurements from Interferometric Synthetic Aperture Radar (InSAR) and subsequent geophysical modelling offer potential solutions, but have limitations related to resolution and uncertainties in estimating the geometry, depth, and volume change of magma sources. In addition, estimates of elastic and rheological properties are often lacking and rely on unverified assumptions.

To overcome these challenges, this study introduces an interdisciplinary approach, leveraging the integrated strengths of seismic and geodetic space-time metrics and using Icelandic volcanoes as case studies. The objectives of this study are as follows: (i) derive phase velocities from seismic ambient noise using seismic interferometry to enhance 3D shear-wave tomography of volcanic structures; (ii) estimate InSAR-derived time series to model surface deformation and provide estimates for the geometry, depth, and volumechanges ofmagmatic plumbing systems, incorporating seismic or other geodetic constraints whenever possible; and (iii) assess the effectiveness of the above-mentioned methods using real and simulated…

In autumn 2017 a network of 14 broadband seismic stations was deployed at the Theistareykir high temperature geothermal field (NE Iceland). This experiment was conducted as part of the current efforts to characterize the field's main structures, and possible short and long term stress variations due to the ongoing fluid injection and extraction operations which started in autumn 2017. In this work, we use two years of continuous seismic records (October 2017–October 2019) to compute a 3D shear wave velocity model of the geothermal field and to detect possible crustal stress changes related to the injection and production activities. From phase cross-correlations of the vertical component recordings, we measure the Rayleigh wave group velocity dispersion curves to obtain 2D group velocity maps between 1 and 5 s. Subsequently, we use a neighborhood algorithm to retrieve the 3D shear wave velocity model of Theistareykir. Mainly, two sets of elongated high and low velocity anomalies can be observed oriented in a NW/WNW direction, parallel to the lineaments of the active Tjörnes fracture zone. Velocity reductions west of Ketilfjall and at Baerjafjall could indicate the location of upflow zones of the magmatic reservoir or hydrothermal system. We analyzed the temporal evolution of phase and amplitude of phase auto-correlations using the stretching technique and discuss their behavior in relation to the geothermal field operations. We notice a slightly stronger long-term velocity decrease in the reservoir region compared to outer regions. This could be related to the mass depletion in that area (higher fluid extraction compared to the water reinjection). In summary, our findings show how a monitoring network can be set up to enable a detailed imaging and monitoring of reservoir behavior in general.

After decades of oil, gas, and coal exploitation, we have learned about some of the unpleasant aftereffects of subsurface resource exploration. Adverse long-term impacts, some known during exploration periods, others only afterwards, may include induced seismicity, land subsidence, or even sinkholes. While geothermal is currently seen as a sustainable source of energy, seismicity induced by inappropriate operational procedures or lack of knowledge of the subsurface may incite doubt and public sensitivity about its future use. A problem frequently posed before and during geothermal exploration is the cost of geophysical measurements for resource assessment, subsurface characterization during the prospection phase, and monitoring accompanying production. In this study, we investigate and discuss the potential of two economic geophysical measurement techniques for geothermal reservoir characterization and monitoring: passive seismic interferometry for better subsurface characterization through seismic imaging (static model), and satellite-based radar interferometry for geodetic imaging (dynamic model). Seismic imaging using passive seismic techniques allows for subsurface characterization via Ambient Noise Tomography, and supports the assessment of geothermal resources without requiring the use of shooting, which reduces the cost compared to active seismics. Geodetic imaging, by measuring the surface displacements during and after production, allows for the monitoring of the effects of production and constrains reservoir modelling, and can be achieved through the use of (freely available) satellite imagery. We discuss the results of both techniques over two high enthalpy geothermal sites in Iceland: Reykjanes Peninsula and Torfajökull volcano. While the Reykjanes Peninsula has geothermal fields that have been producing for decades, Torfajökull’s geothermal field, despite being the largest in Iceland, is not producing. For the subsurface characterization, we use S-wave velocity tomographic images derived from ambient noise seismic interferometry over the two geothermal sites. Within the tomographic images, low- and high-velocity anomalies are used to characterize subsurface structures, which complement current geological models with information at greater depths. From the monitoring point of view, radar satellite deformation measurements over both areas show displacements (subsidence) due to production (Reykjanes) and due to natural phenomena (Torfajökull). Finally, we summarize the lessons learnt and discuss outcomes on each technique.

We investigate ground movements induced by the 8 February 2016, Mw=4.2 earthquake at the Los Humeros Geothermal Field (Mexico) using Sentinel-1 radar interferometry. Previous estimated focal mechanism solution based on seismic data with a hypocentral depth of 1900 m could not resolve the measured coseismic surface deformation pattern. In this study, we applied inverse elastic dislocation models to estimate the source parameters of the seismic event. Our models suggest the reverse reactivation of the Los Humeros normal fault at a shallower depth (<1000 m), with a more significant left lateral component below ~400 m depth. The occurrence of such shallow events at Los Humeros pose increased risks for the neighboring communities and infrastructure. Therefore, continuous monitoring of seismicity and cautious planning of field operations are crucial.

A NNW-SSE striking fault swarm, including the Los Humeros fault, acts as a major boundary of the subsiding area observed by InSAR time-series between February 2016 and May 2019. A potential explanation of the reverse reactivation of the Los Humeros fault and following downward movement of the eastern fault block is the depressurization of the whole hydrothermal system. Such depressurization can occur due to the exploitation of the geothermal field and/or due to natural pressure/temperature changes related to magmatic activity.

Integration of results from active seismic, passive seismic and well data reduces the uncertainties of several subsurface parameters that are of interest for cost-effective geothermal production operations in Los Humeros. In this study, we present results from the application of ambient noise seismic interferometry (ANSI) to retrieve zero-offset reflected P-waves from continuous seismic data recorded at the Los Humeros geothermal field, Mexico. This study is inspired by encouraging results from the application of ANSI for body wave reflection retrieval that was reported in 2016 for a geothermal field located at Reykjanes peninsula, Iceland (Verdel et al., 2016). Continuous broadband and short-period seismic recordings provided insightful reflection information that corresponded well, in relevant depth intervals, with reflectivity retrieved from the correlation of coda waves from a distant but very strong earthquake. That work was carried out within the context of EU’s Seventh Framework research and innovation program IMAGE. Encouraged by these findings, it was decided to conduct a new study following a similar approach within the context of the GEMex project, a European-Mexican collaboration. The purpose of GEMex is to gain an improved understanding of the geological structure and geothermal reservoir behaviour for two geothermal fields: Los Humeros and Acoculco. In the following, we address data selection and processing aspects related to the retrieval of reflected P-waves from Los Humeros seismic noise recordings. The retrieved reflections are compared with modelled reflectivities at two station locations at a close distance from the location where the seismic interval velocities that are used in the modelling were available from the literature. The reflected P-wave information provides structural detail about the field at locations directly underneath the employed seismic stations.

On the 8th of February 2016, a Mw 4.2 earthquake was detected inside the Los Humeros caldera, located in the eastern sector of the Trans-Mexican Volcanic Belt. The event occurred after a sharp increase in the injection rate at the Los Humeros Geothermal Field and it was recorded by the seismic monitoring network of the power plant. The earthquake was felt by the local population and it caused damage in the power plant infrastructure. The focal mechanism solution of a previous study based on seismological data shows a reverse movement with a minor left-lateral component: Mw=4.2, depth=1500m, strike=169°, dip=61°, rake=42°. We have performed a geodetic and geomechanical analysis of the seismic source event based on ground deformation inferred from DInSAR. We used ascending and descending Sentinel-1 differential interferograms to retrieve the horizontal and vertical components of the co-seismic deformation. Subsequently, we inverted the estimated deformation to obtain the solution of an activated fault using the Okada model. These results shed light on the geomechanical aspects of the event and can help to understand the effects of field operations interacting with pre-existing structural features and active tectonic processes in the Los Humeros caldera.

Surface deformation due to fluid extraction can be detected by satellite-based geodetic sensors, providing important insights on subsurface geomechanical properties. In this study, we use Differential Interferometric Synthetic Aperture Radar (DInSAR) observations to measure ground deformation due to fluid extraction at the Los Humeros Geothermal Field (Puebla, Mexico). Our main goal is to reveal the pressure distribution in the reservoir and to identify reservoir compartmentalization, which can be important aspects for optimizing the production of the field. The result of the PS-InSAR (Persistent Scatterer by Synthetic Aperture Radar Interferometry) analysis shows that the subsidence at the LHGF was up to 8 mm/year between April 2003 and March 2007, which is small relative to the produced volume of 5×106 m3/year. The subsidence pattern indicates that the geothermal field is controlled by sealing faults separating the reservoir into several blocks. To assess if this is the case, we relate surface movements with volume changes in the reservoir through analytical solutions for different types of nuclei of strain. We constrain our models with the movements of the PS points as target observations. Our models imply small volume changes in the reservoir, and the different nuclei of strain solutions differ only slightly. These findings suggest that the pressure within the reservoir is well supported and that reservoir recharge is taking place.

Tomographic imaging based on ambient seismic noise measurements has shown to be a powerful tool, especially in areas like Iceland, where the microseism illumination is excellent. In this paper, we produce a 3D S-wave tomographic image over the western Reykjanes Peninsula high-enthalpy geothermal fields and evaluate the reliability of the tomographic results for different resolutions through simulated and real data. We use 30 broadband stations operating for approximately one-and-a-half year and apply ambient noise seismic interferometry for each station-pair. This results in empirical Green's functions in which especially the ballistic surface waves (BSW) are well resolved. The retrieved BSW exhibit a high signal-to-noise ratio between 0.1 and 0.5 Hz, and the beamforming analysis indicates an apparent surface-wave velocity of 3 km/s over a broad azimuthal range. For the tomographic inversion, we invert the estimated phase velocities between all station pairs to frequency-dependent phase velocity maps in four different resolutions (1, 2, 3, and 4 km) using a Tikhonov regularisation. With the estimated regularisation parameter per frequency per resolution, we invert simulated data for checkerboard sensitivity tests per frequency for different combinations of velocity anomaly sizes and resolutions.

Finally, after the inversion to depth, we detect S-wave velocity anomalies with variations between −15% and 15% with reference to an estimated average velocity using 1 km and 3 km of lateral resolutions and 1 km of vertical resolution. This study shows the potential of ambient noise tomography as complementary seismological tool for reservoir characterization.

Torfajökull volcano, Iceland, has not erupted since 1477. However, intense geothermal activity, deformation, and seismicity suggest a long‐lasting magmatic system. In this paper, we use ambient noise tomography to image the magmatic system beneath Torfajökull volcano. One hundred days of ambient noise data from 23 broadband seismometers show the consistent presence of double‐frequency microseism noise with significant power between ∼0.1 and 0.5 Hz. Beamforming results indicate microseism noise with persistent higher energy propagating from west and SE directions and apparent velocities below 3 km/s. We use ambient noise seismic interferometry to retrieve Rayleigh waves, and we introduce a method to estimate the reliability of the retrieved surface waves. We find stable estimation of surface wave phase velocities between 0.16 and 0.38 Hz. Azimuthal velocity variations show a trend of higher velocities in the NE/SW direction, the strike of the rift zone intersecting Torfajökull, and orientation of erupted lavas on a NE‐SW fissure swarm. Tomographic results indicate low‐velocity anomalies beneath the volcano caldera (between −5% and −10%) and even lower velocity variations in the southeast and southwest study area (below −10%), outside the volcano caldera. Low anomalies may indicate the existence of hot material, more prominent outside the caldera outskirts. High‐velocity variations (between 5% and 10%) outline the volcano caldera between 4‐ and 5‐km depth and more pronounced velocities (between 10% and 15%) up to 5‐km depth in the north of the volcano caldera. We interpret the former as possible caldera collapse structure and the latest as solidified intrusive magma from the old preferred magma paths.

Tomographic studies based on passive seismic measurements have proven to be a powerful tool to image the subsurface. This especially holds in areas like Iceland, where the microseism coverage arriving from the ocean is excellent. In this study, we apply Ambient Noise Seismic Interferometry (ANSI) to generate a tomographic image of Rayleigh-waves velocity anomalies to further invert for S-wave anomalies at two Icelandic locations. We derive a tomographic image over Reykjanes Peninsula geothermal system using 30 Broad-Band (BB) stations deployed under the IMAGE (Integrated Methods for Advanced Geothermal Exploration) project framework and operated for approximately one year and a half. In the other case study, we derive a tomographic image of Torfajökull volcano using 23 BB seismometers that recorded ambient noise for 100 days. The later data were acquired in 2005 by Cambridge University. We retrieve the surface-wave part of the Green’s functions by cross-correlation between station pairs and consecutive stacking of the cross-correlations to obtain coherent ballistic surface waves (BSW). We pick the arrival times of the BSW, which are the input for the tomographic analysis. Both datasets show remarkably high signal-to-noise ratio of surface-wave arrivals between 0.1 and 0.5 Hz, even with only 100 days of recorded ambient noise. A beamforming analysis indicates a broad azimuthal coverage with persistent ambient noise arrivals within three azimuthal quadrants - between 90 and 360 degrees. The highly coherent surface-wave retrieval and the wide azimuthal coverage of the microseisms explain the success of ANSI techniques in Iceland. For the tomographic inversion, we use a Tikhonov and a statistical regularisation to invert the ballistic surface-wave time-arrival to 3D frequency-dependent velocity variations. After further inversion to S-wave velocity variations, we detect low- and high-velocity anomalies with changes between -15% and 15% from an estimated average velocity, we interpret these anomalies as possible old dyke intrusions and heat sources.

Variations of b-values in Gutenberg-Richter’s law has been proven to provide insights on earthquake triggering mechanisms. These b-value variations express changes in the rate of occurrence of small earthquakes relative to large ones. Geophysical processes correlated with b-value variations have been identified using earthquake catalogues over natural tectonically active environments. Not so much is known over anthropogenic exploration sites due to the lack of dedicated seismometers in place and therefore the reduced number of recorded events. In the early 1990's, nearly after 30 years of gas production, small seismic events started to be detected at the Groningen gas field. Several efforts to measure these seismic events let to a unique seismic network and an earthquake catalogue available through KNMI’s website. We perform a temporal, spatial and spatiotemporal b-value analysis for which we use 800 events from early 90’s up to now with a magnitude lower limit of 1.1 (magnitude of completeness).

In recent years, new algorithms have been proposed to retrieve maximum available information in synthetic aperture radar (SAR) interferometric stacks with focus on distributed scatterers. The key step in these algorithms is to optimally estimate single-master (SM) wrapped phases for each pixel from all possible interferometric combinations, preserving useful information and filtering noise. In this paper, we propose a new method for SM-phase estimation based on the integer least squares principle. We model the SM-phase estimation problem in a linear form by introducing additional integer ambiguities and use a bootstrap estimator for joint estimation of SM-phases and the integer unknowns. In addition, a full error propagation scheme is introduced in order to evaluate the precision of the final SM-phase estimates. The main advantages of the proposed method are the flexibility to be applied on any (connected) subset of interferograms and the quality description via the provision of a full covariance matrix of the estimates. Results from both synthetic experiments and a case study over the Torfajökull volcano in Iceland demonstrate that the proposed method can efficiently filter noise from wrapped multibaseline interferometric stacks, resulting in doubling the number of detected coherent pixels with respect to conventional persistent scatterer interferometry.

Torfajökull is the largest silicic volcanic centre in Iceland lying at the intersection of the rift zone (MidAtlantic Ridge) and the transform zone that connects to Reykjanes peninsula. It erupts infrequently,with only two eruptions in the last 1200 years, the latest of which was over 5 centuries ago. Yet, itsactive tectonic setting, persistent high and low frequency seismicity, deformation and geothermalactivity within its large caldera (18x12 km diameter) indicate the continued presence of a long-lasting magma chamber. Here we speculate on possible geometry, size and depth of the Torfajökullmagma chamber by using radar interferometry (InSAR) and seismic interferometry (SI).Using InSAR time series analysis we detect a surface subsidence pattern at rates of up to ~13 mm yr-1in the SW region of Torfajökull ́s caldera, on-going since at least 1993. The subsidence rate isconstant in time, and perhaps due to a cooling magma chamber. The data can be fit reasonably wellusing a model of a NE-SW oriented spheroidal body at ~5 km depth. As the deflating area correlatesspatially with the area of geothermal activity, deflation may also be the surface response due to anactive hydrothermal circulation.To gain more insight into the geometry of Torfajökull’s magmatic system and rock properties of thesubsurface, we apply ambient noise seismic interferometry (SI) by cross-correlation of ambient noise.With this technique we can detect velocity variations, which can correspond to the edges of dikes ormolten magma bodies. Our tomographic results give reliable results of velocity variations within adepth range of 2 km to 7.5 km. We find high velocity zones that we interpret as old dike intrusions.Low velocity anomalies (>5%), which usually indicate the presence of warmer material, are locatedon the southeast and southwest part of the volcano, outside the volcano caldera.Finally we compare both InSAR and SI results. The hypothesis of a magma chamber under thesubsidence area detected by InSAR does not seem to fit the tomographic results, as the expectededges of a magma body modelled by InSAR are not clearly identified by the SI results. If there is anestablished magma chamber within Torfajökull caldera this is likely to be bellow 7km depth.

Magmatic plumbing systems beneath active and moderately active volcanoes are often poorly constrained. A better knowledge of the shape, size and location of the magma bodies would enable us to better predict magma movements preceding an eruption. Surface displacements estimated from radar interferometry (InSAR) can be used in geophysical modelling to constrain location, geometry and pressure changes in magma systems. However, the resolution of the inferred magma chamber is typically poor. More insight into the location and geometry of magmatic systems can be gained using active-source reflection seismic surveys, which allow detection of velocity contrasts at the edges of the magma bodies. The drawback of this technique is that controlled-source surveys are expensive. As an alternative, seismic interferometry (SI) uses cross-correlation of natural signals to generate new seismic records that simulate active sources. Under the premise that both seismic and radar observations would help to narrow down the location, shape and size of a magma system, we present the first results of combined radar and seismic interferometric processing over Torfajökull volcano. Torfajökull is located in the neovolcanic zone, in the south of Iceland. The volcano is characterized by intense thermal manifestations (hot springs forming ground steaming and fumaroles) with higher activity nearby the faults of the active NE-SW fissure swarm. Torfajökull erupts infrequently, with only two eruptions in the last 1200 years, the latest of which was over 5 centuries ago. However, ongoing seismicity, deformation and geothermal activity indicate the continued presence of a long-lasting magma chamber. Although historical eruptions have been relatively small, the large caldera (18x12 km diameter) and high geothermal activity within the caldera is evidence of a massive eruption in the past, and the potential for a further eruption of similar size is unknown. We applied InSAR time series analysis to data acquired by Envisat over the Torfajökull region along 6 different tracks (3 tracks in ascending and 3 tracks in descending mode). The estimated velocity maps show subsidence beneath the SW part of the caldera. This subsidence has been on-going since at least 1993, with rates of up to ~13 mm/yr. This has been interpreted as a cooling magma chamber, shrinking at linear rates. To obtain a rough approximation of the geometry and location of the source of subsidence we ran a forward model. The model suggest an ellipsoidal magma chamber within the volcano caldera with a NE-SW orientation and at ~5km depth. For the SI processing we use two types of natural signals: microseisms and local earthquakes. We use seismic data acquired in 2005 at 30 stations sparsely distributed around the Torfajökull area. Using microseisms, we divide the noise, recorded at two stations in portions of 1h, cross-correlate the corresponding portions and then sum the correlated results. The result is a retrieved surface-wave part of the Green’s function between the two stations. This is repeated between all stations. Careful assessment of the quality of the retrieved Green’s functions for small time windows allows analysis of the microseism noise. The results show that the microseisms are dominant in the NW-SE direction and the resulting retrieved surface waves propagate at ~3 km/s in the double-frequency microseism band. The retrieved surface waves between the stations will be used in tomographic inversion that will allow derivation of the 3D S-wave velocity distribution in the subsurface. We will then use these results to better constrain our magma source model, currently constrained only by InSAR.

Mapping magmatic plumbing systems beneath active and moderately-active volcanoes contributes to our understanding of how magma spreads up to the crust surface. Additionally, the time that magma takes to accumulate in the earth’s interior before an eruption could be better estimated if we knew in detail the shape, size and depth of the magma chamber. Radar interferometric observations can used to measure displacements associated with crustal deformation and to subsequently infer magma chamber features through geophysical modelling. This is normally applied to highly active volcanoes, or volcanoes with an eruption imminent. However, less is known about long-lasting magma chambers beneath volcanoes that have not erupted for centuries. In this study, we explore the magma systems of two different Icelandic volcanoes using InSAR time series. Eyjafjallajökull, which erupted in April 2010 and caused significant disruption to air traffic, had not erupted prior to that for nearly two centuries, and only three times in total in the previous 1200 years.In 1992 an increase of seismicity signalled a change from its previous low activity. InSAR- and GPS-derived models of Eyjafjallajökull from these last 20 years of unrest, show a complex network of sills and dikes rather than a single established magma chamber. In 1994 and 1999 two deformation episodes were modelled as sill intrusions between 4.5 and 6.5 km depth under the southeastern flank. Prior to the 2010 eruption, further sills intruded at similar depths. Shortly before the onset of eruption, one or more dikes propagated upwards and eventually reached the surface. Curiously, the source of deflation during the explosive eruption has a different location and geometry to the sills modelled in the pre-eruptive phases. Torfajökull, also erupts infrequently, with only two eruptions in the last 1200 years, the latest of which was over 5 centuries ago. However, ongoing seismicity, deformation and geothermal activity indicate the continued presence of a long-lasting magma chamber. InSAR time series show subsidence of the southwestern part of the caldera with rates of up to ~13 mm yr-1, which has been interpreted as a cooling magma chamber. Although historical eruptions have been relatively small, the large caldera (12 km diameter) is evidence of a massive “supervolcano” eruption in the past, and the potential for a further eruption of similar size is unknown. Here we compare and contrast the two volcanoes and explore what we might expect in terms of warning signals in the case of a future eruption of Torfajökull.

After a period of quiescence since a sill intrusion in 1999-2000, a subtle deformation signal was again detected at Eyjafjallajökull, beginning in the summer of 2009, at a continuous GPS station on the southern flank. At our request the German Space Centre (DLR) immediately began tasking the TerraSAR-X satellite to acquire three SAR images every 11 days, giving a time series of SAR images prior to the eruption with unprecedented temporal sampling (although interrupted by snow during the winter).
Previously we modelled individual interferograms that showed that there was a large uplift signal. We modelled this as a series of sills and a dike with a total volume of ~0.05 km3. During the flank eruption, beginning on 20 March, no significant deformation is detected, but coinciding with the start of the explosive eruption on April 14, we detected subsidence centred on the caldera. What we modelled showed us that Eyjafjallajökull was an unusual which we modelled …. This deformation does not relate to pressure changes within a single magma chamber.
Here we extend our analysis InSAR time series covering full eruptive period. After correcting for DEM errors and reduction of atmospheric signal, we have found a number of signals that we interpreted in terms of magma movement. These magma movements are separately analysed in 3 phases: pre-eruptive (inflation), co-eruptive (no deformation) and post-eruptive (deflation).
The displacement time series from June 2009 to 4 February 2010 (pre-eruptive-phase) shows line-of-sight shortening on the southwest flank of about 2 cm. The displacement signal is present in a set of interferograms and it has a consistent behaviour in time, implying that it is not due to atmospheric contamination. We performed atmospheric stratification over the entire Interferogram (4 Feb 2010) to check how much of the signal correlated with the topography would disappear when removed. The correlation coefficient over the southwest flank is very small compared with the signal from the entire interferogram. We can say that in this area not much of the atmospheric effects related with the topography are present, suggesting that the signal could be deformation.
For the co/post-eruptive phases we calculated phase difference between nearby points to check their evolution in time. In the southeast flanks we observe deflation through all analyzed period, while in western flanks of the volcano we observe Inflation during effusive eruption, followed by deflation during explosive eruption, and a new inflation pattern between 05 June and 19 July that we cannot explain. In preliminary modelling we fit this post-eruptive phase with a pressure decrease of an ellipsoidal source, equivalent to a volume reduction of ~0.03 km3.
The limitations when analysing this dataset are mainly concerning the phase unwrapping performance through ice- and ash-covered areas. This is caused by decorrelation owing to ash cover where there is almost complete loss of coherence. We applied new methods to overcome these limitations. To improve point density over the scene, we combined PS (Persistent Scatterers) and SB (Small Baselines) methods. By combining highly coherent interferograms, the increase of distributed scatterers is clear and the phase unwrapping performance improved. To detect and correct non-systematic unwrapping errors, we calculated azimuth and range offsets. Additionally, because of the fact that L band has higher penetration, we processed ALOS images trough single interferogram analysis. By these means we were able to extract more of the deformation signal around decorrelated areas.