Interferometric Synthetic Aperture Radar Models Research Articles

Refined and dynamic susceptibility assessment of landslides using InSAR and machine learning models

Landslide susceptibility assessment is crucial in predicting landslide occurrence and potential risks. However, traditional methods usually emphasize on larger regions of landsliding and rely on relatively static environmental conditions, which exposes the hysteresis of landslide susceptibility assessment in refined-scale and temporal dynamic changes. This study presents an improved landslide susceptibility assessment approach by integrating machine learning models based on random forest (RF), logical regression (LR), and gradient boosting decision tree (GBDT) with interferometric synthetic aperture radar (InSAR) technology and comparing them to their respective original models. The results demonstrated that the combined approach improves prediction accuracy and reduces the false negative and false positive errors. The LR-InSAR model showed the best performance in dynamic landslide susceptibility assessment at both regional and smaller scale, particularly when identifying areas of high and very high susceptibility. Modeling results were verified using data from field investigations including unmanned aerial vehicle (UAV) flights. This study is of great significance to accurately assess dynamic landslide susceptibility and to help reduce and prevent landslide risk.

Subsurface deformation monitoring with InSAR and elastic inversion modeling in west Texas

Recent Interferometric Synthetic Aperture Radar (InSAR) observations depict centimeter-level surface uplift/subsidence signals in west Texas that correlate spatially and temporally with increased fluid extraction and injection activities over the past decade. Linear subsidence features from InSAR data near the Pecos area, that align well with maximum horizontal stress orientations and recent clusters of seismic events, suggest fault motion is also associated with this deformation. In this study, we investigate the relationship between observed surface displacement and inferred subsurface fault slip and reservoir compaction/inflation by inversely solving a combined model of elastic dislocation (Okada, 1985, 1992) and poroelastic reservoir compaction/inflation model (Geertsma, 1973).Our geomechanical analysis coupled with InSAR observations are consistent with the idea that both fault slip and reservoir inflation/compaction are occurring associated with fluid injection and withdrawal in the Pecos area. Numerical results show that the linear surface displacement patterns can be accurately reproduced using clusters of finite slip on multiple elastic dislocations in the subsurface, but also matching the broader areal subsidence and uplift signals requires the addition of poroelastic subsurface inflation and depletion. The inverted areal reservoir pressure distribution correlates well with known injection and withdrawal operations in the area. The best-fit surface deformation locates most fault slips patches at depths of 1–3 km, which is shallower than most reported earthquakes in this area. The difference in the estimation of depth suggests there could be aseismic fault slippages.

Co-seismic slip of the 18 April 2021 Mw 5.9 Genaveh earthquake in the South Dezful Embayment of Zagros (Iran) and its aftershock sequence

On 2021 April 18, an Mw 5.9 earthquake struck the Genaveh region in the south Dezful embayment of the Zagros, Iran. Here, we investigate the active tectonics of the region, the geometry and slip distribution of the causative fault plane, and its aftershock behavior. We applied a combination of different geodetic and seismological methods (slip distribution inversion of the mainshock using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR), relocation, and moment tensor inversion of aftershocks and background seismicity of the region). Co-seismic InSAR modeling shows that the slip is confined to the sedimentary cover at depths of 4-7 km with a maximum slip of 1 m and highlights the influence of lithology in the rupture propagation. Moment tensors and centroid depths of aftershocks down to Mw 4 show that the distributed aftershocks sequence is dominated by reverse faulting at centroid depths of 4-10 km. The causative fault is compatible and parallel to the trend of the Gulkhari anticline and the coseismic uplift of the Genaveh earthquake implies that the growth of this particular fold is linked to the fault(s). However, still, due to the absence of surface rupture, the clear relationship between buried faulting and surface folding remains unclear.

The 2020 Mw 6.5 Monte Cristo Range, Nevada, Earthquake: Anatomy of a Crossing-Fault Rupture through a Region of Highly Distributed Deformation

ABSTRACT The 15 May 2020 Mw 6.5 Monte Cristo Range earthquake (MCRE) in Nevada, United States, is the largest instrumental event in the Mina deflection—a zone of east-trending left-lateral faults accommodating a right step between northwest-trending right-lateral faults of the Walker Lane. The MCRE ruptured a highly distributed faulting area with muted geomorphic expressions, motivating us to characterize the behavior of an earthquake on a structurally immature fault system. Inverse modeling of Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) displacements reveals left-lateral slip on an east-striking, eastern fault and left-lateral–normal slip on an east-northeast-striking, western fault. Unusually, the two faults cross one another and ruptured together in the mainshock. The maximum slip of 1 m occurs at 8–10 km depth, but less than 0.1 m of slip reaches the surficial model fault patches, yielding a pronounced shallow slip deficit (SSD) of 91%. Relocated hypocenters indicate that the mainshock initiated at 9 km depth and that aftershocks span depths of 1–11 km, constraining the local seismogenic thickness. Our new field observations of fracturing and pebble-clearing in the western MCRE characterize a third, shorter, northern fault that is at the resolution limit of the InSAR–GNSS modeling. The segmented and intersecting fault geometry, off-fault aftershocks with variable mechanisms, distributed surface fractures, limited long-term geomorphic offsets, and a 600–700 m (cumulative) bedrock offset are all characteristic of a structurally immature fault system. However, the large SSD is not unusual for an earthquake of this magnitude, and a larger compilation of InSAR models (28 Mw≥6.4 strike-slip events) shows that SSDs correlate with magnitude rather than structural maturity. This study demonstrates the importance of integrating geodesy, seismology, and field observations to capture the full complexity of large earthquakes, and further suggests that seismic hazard assessments in shattered crustal regions consider the potential for multi- and cross-fault rupture.

Interactions of magmatic intrusions with the multiyear flank instability at Anak Krakatau volcano, Indonesia: Insights from InSAR and analogue modeling

AbstractVolcano flank collapses have been documented at ocean islands worldwide and are capable of triggering devastating tsunamis, but little is known about the precursory processes and deformation changes prior to flank failure. This makes the 22 December 2018 flank collapse at Anak Krakatau in Indonesia a key event in geosciences. Here, we provide direct insight into the precursory processes of the final collapse. We analyzed interferometric synthetic aperture radar (InSAR) data from 2014 to 2018 and studied the link between the deformation trend and intrusion occurrence through analogue modeling. We found that the flank was already moving at least 4 yr prior to collapse, consistent with slow décollement slip. Movement rates averaged ~27 cm/yr, but they underwent two accelerations coinciding with distinct intrusion events in January/February 2017 and in June 2018. Analogue models suggest that these accelerations occurred by (re)activation of a décollement fault linked to a short episode of magma intrusion. During intrusion, we observed a change in the internal faults, where the outward-directed décollement accelerated while inward faults became partially blocked. These observations suggest that unstable oceanic flanks do not disintegrate abruptly, but their collapse is preceded by observable deformations that can be accelerated by new intrusions.

Volcano‐Magnetic Signal Reveals Rapid Evolution of the Inner Structure of Piton de la Fournaise

AbstractNear‐real time analysis of magnetization can provide important information for the imaging of volcano systems and their spatiotemporal evolution. This study focuses on the contribution of volcano‐magnetic signals from reiterations of ground magnetic measurements to investigate the evolution of active structures at the Piton de la Fournaise volcano from 2017 to 2020. Changes are demonstrated by magnetic anomalies along a reference profile by means of the reiteration periods. These variations are first modeled qualitatively in 2D using electrical resistivity constraints in order to investigate the evolution of magnetization at depth through time, and the model is subsequently compared with the 3D intrusive activity from depth up to the surface from Interferometric Synthetic Aperture Radar (InSAR) inverse modeling. The shallow areas of demagnetization modeled from one reiteration to another are consistent with the geometry and location of the underlying intrusions revealed by the 3D InSAR models, suggesting strong thermal, stress, and electrokinetic effects due to magmatic activity not only at the surface but also at depth, along the main magmatic paths. It also raises a question as to the extent of the associated thermal diffusion processes at the scale of individual magma injections. This study confirms that detecting resistivity and magnetization anomalies, and quantifying their spatiotemporal evolution, can provide powerful tools for imaging volcanic systems at various scales and for providing warning of associated hazards. It also highlights the necessity for 4D monitoring of volcanic edifices using this method to provide greater precision, an important issue that is now made possible by the use of Unmanned Aerial Vehicle measurements.

Systematic Comparison of InSAR and Seismic Source Models for Moderate‐Size Earthquakes in Western China: Implication to the Seismogenic Capacity of the Shallow Crust

AbstractEarthquake source parameters are important for understanding earthquake physics and crustal fault properties. However, strong trade‐offs between parameters (e.g., depth and origin time) and a lack of accurate velocity models and near‐field seismic stations could cause large uncertainties of these parameters in seismic catalogs, particularly for shallow events. To further improve the resolution of earthquake source parameters, we use Interferometric Synthetic Aperture Radar (InSAR) images to derive source solutions of 33 moderate‐size (Mw 4.1–6.6) earthquakes that occurred at shallow depths (<20 km) from November 2014 to July 2020 in western China. After evaluating the uncertainties of the InSAR solutions, we systematically compare the location, centroid depth, focal mechanism and magnitude from InSAR models with that from seismic catalogs. We find that all seismic catalogs generally report deeper (4–10 km) hypocenters or centroid depths. The uncertainties of moment tensor solutions are partially related to the percentage of the non‐double‐couple components in the seismic catalogs. The InSAR solutions indicate that considerable seismic moments (i.e., ∼ Nm) were released in the uppermost crust (i.e., <5 km) in a period of ∼6 years, which is not resolvable in the seismic catalogs. The smooth seismic moment distribution along depth indicates a gradual change of the frictional properties from the surface to the middle crust. As most of the studied earthquakes are located on secondary and/or unmapped faults, these findings imply a considerable portion of velocity‐weakening friction in the uppermost crust along immature, secondary fault systems, which should be included in the seismic hazard evaluation.

An integrated InSAR-machine learning approach for ground deformation rate modeling in arid areas

Land subsidence is an increasing human-induced disaster that not only damages building and transportation structures but also diminishes the water storage capacity of the aquifers. Land subsidence is a very complex phenomenon impacted by various geo-environmental and hydrological factors. Application of the interferometric synthetic aperture radar (InSAR) is becoming a common approach to detect land subsidence rates, though, it suffers from the lack of continuity over the spatial surfaces due to the vegetation decorrelation, coverage alterations (cultivation and non-cultivation seasons), in the agricultural areas, and rough topography. The lack of continuity can, however, be resolved using artificial intelligence. In our case study, while InSAR deformation data only covered ∼ 2% of the plain’s surface, we employed boosted regression trees (BRT) and extreme gradient boosting (XGB) algorithms to provide a full coverage map of the groundwater-induced land subsidence based on the InSAR analysis. For this, a set of topographical, hydrological, hydrogeological, and anthropogenic factors was selected. The InSAR and input factors’ resolution data were resampled to a 100-by-100 m to match. The implemented models predicted the long-term deformation rate with the acceptable performances of the BRT (RMSE = 3.3 mm/year, MAE = 2.0 mm/year, R2 = 0.985) and the XGB with linear booster (RMSE = 3.5 mm/year, MAE = 2.1 mm/year, R2 = 0.983). Considering the substantial ground deformation in the studied area (from −216 to 49 mm/year), RMSE values of 3.3, and 3.5 mm/year between the InSAR measurement and model predictions show great potential for combined InSAR-machine learning technique for pumping-driven land subsidence studies. Thus, the introduced approach is suggested for other areas being damaged by excessive pumping and agricultural development to produce an accurate full coverage map of subsidence.

Development of InSAR Neutral Atmospheric Delay Correction Model by Use of GNSS ZTD and Its Horizontal Gradient

Interferometric Synthetic Aperture Radar (InSAR) often suffers from atmospheric disturbances due to the microwave propagation delay effect, which limits the surface displacement detection accuracy to an order of centimeters or more. Here I developed a new neutral atmospheric delay correction model for InSAR by using the global navigation satellite system (GNSS) zenith total delay (ZTD) and its horizontal gradient data. The proposed model at first retrieves the regularly gridded ZTD distribution at sea level and the linear height dependence from GNSS ZTD and gradient observations by the least squares method. Then, the gridded ZTD is projected onto the InSAR coordinate to correct the neutral atmospheric delay. I evaluated the correction model performance by applying it to L-band ALOS-2/PALSAR-2 ScanSAR interferograms over the Kanto plain in Japan. The correction result showed that by applying the proposed delay correction the phase standard deviation decreased by 33.87 % on average. By comparing it with the generic atmospheric correction online service for InSAR (GACOS) model and the correction by the Japanese regional mesoscale weather model (MSM), the proposed GNSS-based model outperformed others in my test case. The sensitivity test indicated that including the delay gradient could improve delay reproducibility under situations with fewer available GNSS stations. Although the proposed correction model’s applicability depends on the number of available GNSS stations at the area of interest, the proposed model has a potential to effectively mitigate the neutral atmospheric delay and to improve the detection ability for smallamplitude surface displacements.

The 2019-2020 Khalili (Iran) Earthquake Sequence-Anthropogenic Seismicity in the Zagros Simply Folded Belt?

We investigate the origin of a long‐lived earthquake cluster in the Fars arc of the Zagros Simply Folded Belt that is colocated with the major Shanul natural gas field. The cluster emerged in January 2019 and initially comprised small events of M n ∼ 3–4. It culminated on 9 June 2020 with a pair of M w 5.4 and 5.7 earthquakes, which was followed by >100 aftershocks. We assess the spatiotemporal evolution of the earthquake sequence using multiple event hypocenter relocations, waveform inversions, and Sentinel‐1 Interferometric Synthetic Aperture Radar (InSAR) measurements and models. We find that the early part of the sequence is spatially distinct from the 9 June 2020 earthquakes and their aftershocks. Moment tensors, centroid depths, and source parameter uncertainties of 15 of the largest (M n ≥ 4.0) events show that the sequence is dominated by reverse faulting at shallow depths (mostly ≤4 km) within the sedimentary cover. InSAR modeling shows that the M w 5.7 mainshock occurred at depths of 2–8 km with a rupture length and maximum slip of ∼20 km and ∼0.5 m, respectively. Our results suggest that the 2019–2020 Khalili earthquake sequence was likely influenced by operation of the Shanul field, though elevated natural seismicity in the Zagros makes the association difficult to prove. Understanding how to distinguish man‐made from natural seismicity is helpful for hazard and risk assessment, notably in the Zagros, which is both seismically active and rich in oil and gas reserves.

Geodetic Model of the March 2021 Thessaly Seismic Sequence Inferred from Seismological and InSAR Data

In this work, we propose a geodetic model for the March 2021 Thessaly seismic sequence (TSS). We used the interferometric synthetic aperture radar (InSAR) technique and exploited a dataset of Sentinel-1 images to successfully detect the surface deformation caused by three major events of the sequence and constrain their kinematics, further strengthened by seismic data analysis. Our geodetic inversions are consistent with the activation of distinct blind faults previously unknown in this region: three belonging to the NE-dipping normal fault associated with the Mw 6.3 and Mw 6.0 events, and one belonging to the SW-dipping normal fault associated with the Mw 5.6, the last TSS major event. We performed a Coulomb stress transfer analysis and a 1D pore pressure diffusivity modeling to investigate the space–time evolution of the sequence; our results indicate that the seismic sequence developed in a sort of domino effect. The combination of the lack of historical records of large earthquakes in this area and the absence of mapped surface features produced by past faulting make seismic hazard estimation difficult for this area: InSAR data analysis and modeling have proven to be an extremely useful tool in helping to constrain the rupture characteristics.

Comparison of TanDEM-X InSAR data and high-density ALS for the prediction of forest inventory attributes in plantation forests with steep terrain

Satellite interferometric synthetic aperture radar (InSAR) is emerging as a viable low-cost alternative method to airborne laser scanning (ALS) for forest inventory though little research has examined its efficacy for plantation forests located in temperate regions on steep terrain. InSAR and ALS data were collected from Geraldine Forest which is located on rolling to very steep topography in the southeast of New Zealand. These data were combined with an extensive set of plot measurements from which mean top height (H), basal area (G), stem density (N), and total stem volume (TSV) were calculated. InSAR and ALS-based Random Forest models of each variable were developed and compared.Using the ALS data as a reference, the mean RMSE of the InSAR DSM and DTM surfaces were, respectively, 4.58 and 8.09 m and these errors increased to mean values of, respectively, 6.02 and 10.17 m for slopes of 40–50°.ALS-based models were substantially more precise than those developed from InSAR for H (R2 = 0.86 vs. 0.60; RMSE% = 5.47 vs. 10.8%), G (R2 = 0.56 vs. 0.32; RMSE% = 21.5 vs. 30.4%), N (R2 = 0.47 vs. 0.09; RMSE% = 32.3 vs. 43.2%), and TSV (R2 = 0.70 vs. 0.41; RMSE% = 19.4 vs. 30.7%). The base metrics (i.e. ALS height and canopy cover variables) accounted for most of the variance in the ALS models with addition of further metrics providing ≤ 1% reduction in the RMSE%. Base metrics (i.e. InSAR observables) also accounted for most of the variation in InSAR models. Addition of metrics from a mixed Canopy Height Model (CHM), derived from InSAR Digital Surface Model (DSM) and ALS Digital Terrain Model (DTM), resulted in reductions in RMSE% of 3.1–5.4% for H, G, and TSV models with addition of textural metrics providing further reductions of 0.2–0.3% for H and G models. Addition of metrics from the radar CHM, derived from the InSAR DTM and DSM, and texture metrics reduced the RMSE% of the base model for N by 2.3% and 0.5%, respectively.The results were generated using a SAR image pair with a height of ambiguity (HOA) that was higher than ideal, which reduced the sensitivity of results to changes in terrain. Despite this limitation, and the steep slopes throughout the forest, the InSAR models described here had comparable precision to developed InSAR models for key inventory metrics from previous studies.

Landslide detection in mountainous forest areas using polarimetry and interferometric coherence

The cloud-free, wide-swath, day-and-night observation capability of synthetic aperture radar (SAR) has an important role in rapid landslide monitoring to reduce economic and human losses. Although interferometric SAR (InSAR) analysis is widely used to monitor landslides, it is difficult to use that for rapid landslide detection in mountainous forest areas because of significant decorrelation. We combined polarimetric SAR (PolSAR), InSAR, and digital elevation model (DEM) analysis to detect landslides induced by the July 2017 Heavy Rain in Northern Kyushu and by the 2018 Hokkaido Eastern Iburi Earthquake. This study uses fully polarimetric L-band SAR data from the ALOS-2 PALSAR-2 satellite. The simple thresholding of polarimetric parameters (alpha angle and Pauli components) was found to be effective. The study also found that supervised classification using PolSAR, InSAR, and DEM parameters provided high accuracy, although this method should be used carefully because its accuracy depends on the geological characteristics of the training data. Regarding polarimetric configurations, at least dual-polarimetry (e.g., HH and HV) is required for landslide detection, and quad-polarimetry is recommended. These results demonstrate the feasibility of rapid landslide detection using L-band SAR images.

The 2016 Mw 6.0 Hutubi earthquake: A blind thrust event along the northern Tian Shan front

The Tian Shan Range, which trends E-W along the southern margin of the Junggar Basin, is one of the longest and most active intracontinental orogenic belts in central Asia. On 8 December 2016 (05:15:04 UTC), a Mw 6.0 earthquake ruptured the northern Tian Shan front. Here, we use Sentinel-1 radar imagery to investigate the deformation and source parameters related to this event. The co-seismic surface deformation was predominated by uplift without surface rupture. Ascending and descending interferograms indicate that the event triggered small co-seismic deformations with maximum line-of-sight displacements of 22 mm and 24 mm, respectively. Although the north-dipping and south-dipping plane solutions can both fit the observations well, the north-dipping solution with a dip of 58° is preferred in consideration of the relocated aftershocks and regional geological structure. Significant slip is located between depths of 12 km and 17 km, suggesting that the event was caused by a completely blind thrust fault. This blind rupture is characterized largely by a compact thrusting patch with a peak slip of 56 cm at a depth of 13 km. The source model generates a geodetic moment of 6.678 × 1017 N m corresponding to a Mw 5.85 event. Both the interferometric synthetic aperture radar modeling and the aftershock locations indicate that the rupture plane is linked to the Huoerguosi-Manas-Tugulu fault at a depth of ∼16 km, a typical locking depth in the Tian Shan. We suggest that the 2016 Hutubi earthquake more likely occurred on a back-thrust of the Huoerguosi-Manas-Tugulu fault, and the back-thrust is interpreted to represent a preexisting normal fault beneath the Qigu anticline belt that was tectonically inverted during the Cenozoic.

Mapping Pyroclastic Flow Inundation Using Radar and Optical Satellite Images and Lahar Modeling

Sinabung volcano, located above the Sumatra subduction of the Indo-Australian plate under the Eurasian plate, became active in 2010 after about 400 years of quiescence. We use ALOS/PALSAR interferometric synthetic aperture radar (InSAR) images to measure surface deformation from February 2007 to January 2011. We model the observed preeruption inflation and coeruption deflation using Mogi and prolate spheroid sources to infer volume changes of the magma chamber. We interpret that the inflation was due to magma accumulation in a shallow reservoir beneath Mount Sinabung and attribute the deflation due to magma withdrawal from the shallow reservoir during the eruption as well as thermoelastic compaction of erupted material. The pyroclastic flow extent during the eruption is then derived from the LAHARZ model based on the coeruption volume from InSAR modeling and compared to that derived from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image. The pyroclastic flow inundation extents between the two different methods agree at about 86%, suggesting the capability of mapping pyroclastic flow inundation by combing radar and optical imagery as well as flow modeling.

Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model

The seasonal variation of land cover and the large deformation gradients in coal mining areas often give rise to severe temporal and geometrical decorrelation in interferometric synthetic aperture radar (InSAR) interferograms. Consequently, it is common that the available InSAR pairs do not cover the entire time period of SAR acquisitions, i.e., temporal gaps exist in the multi-temporal InSAR observations. In this case, it is very difficult to accurately estimate mining-induced dynamic subsidence using the traditional time-series InSAR techniques. In this investigation, we employ a logistic model which has been widely applied to describe mining-related dynamic subsidence, to bridge the temporal gaps in multi-temporal InSAR observations. More specifically, we first construct a functional relationship between the InSAR observations and the logistic model, and we then develop a method to estimate the model parameters of the logistic model from the InSAR observations with temporal gaps. Having obtained these model parameters, the dynamic subsidence can be estimated with the logistic model. Simulated and real data experiments in the Datong coal mining area, China, were carried out in this study, in order to test the proposed method. The results show that the maximum subsidence in the Datong coal mining area reached about 1.26 m between 1 July 2007 and 28 February 2009, and the accuracy of the estimated dynamic subsidence is about 0.017 m. Compared with the linear and cubic polynomial models of the traditional time-series InSAR techniques, the accuracy of dynamic subsidence derived by the logistic model is increased by about 50.0% and 45.2%, respectively.

Magma Pathways and Their Interactions Inferred from InSAR and Stress Modeling at Nyamulagira Volcano, D.R. Congo

A summit and upper flank eruption occurred at Nyamulagira volcano, Democratic Republic of Congo, from 2–27 January 2010. Eruptions at Nyamulagira during 1996–2010 occurred from eruptive fissures on the upper flanks or within the summit caldera and were distributed along the ~N155E rift zone, whereas the 2011–2012 eruption occurred ~12 km ENE of the summit. 3D numerical modeling of Interferometric Synthetic Aperture Radar (InSAR) geodetic measurements of the co-eruptive deformation in 2010 reveals that magma stored in a shallow (~3.5 km below the summit) reservoir intruded as two subvertical dikes beneath the summit and southeastern flank of the volcano. The northern dike is connected to an ~N45E-trending intra-caldera eruptive fissure, extending to an ~2.5 km maximum depth. The southern dike is connected to an ~N175E-trending flank fissure extending to the depth of the inferred reservoir at ~3.5 km. The inferred reservoir location is coincident with the reservoir that was active during previous eruptions in 1938–1940 and 2006. The volumetric ratio of total emitted magma (intruded in dikes + erupted) to the contraction of the reservoir (rv) is 9.3, consistent with pressure recovery by gas exsolution in the small, shallow modeled magma reservoir. We derive a modified analytical expression for rv, accounting for changes in reservoir volume induced by gas exsolution, as well as eruptive volume. By using the precise magma composition, we estimate a magma compressibility of 1.9–3.2 × 109 Pa−1 and rv of 6.5–10.1. From a normal-stress change analysis, we infer that intrusions in 2010 could have encouraged the ascent of magma from a deeper reservoir along an ~N45E orientation, corresponding to the strike of the rift transfer zone structures and possibly resulting in the 2011–2012 intrusion. The intrusion of magma to greater distances from the summit may be enhanced along the N45E orientation, as it is more favorable to the regional rift extension (compared to the local volcanic rift zone, trending N155E). Repeated dike intrusions beneath Nyamulagira’s SSE flank may encourage intrusions beneath the nearby Nyiragongo volcano.

Global compilation of interferometric synthetic aperture radar earthquake source models: 2. Effects of 3-D Earth structure

[1] We carry out long-period surface wave centroid moment tensor (CMT) inversions using various global tomographic models and two different forward modeling techniques for 32 large earthquakes previously studied using interferometric synthetic aperture radar (InSAR) data. Since InSAR methods provide an alternative and independent way of locating and characterizing shallow continental earthquakes, comparisons of our source parameters with those from InSAR are a novel way to assess limitations in the InSAR models as well as the effects of inaccurate wave propagation formulations and/or 3-D Earth structure on earthquake source determinations. We show that comparing InSAR results with our seismic solutions is valuable to identify inaccuracies in the earthquake slip distribution retrieved using InSAR. Moreover, we find that using more accurate formulations, together with the best fitting Earth models, substantially reduces biases and differences between moment magnitude and fault strike determined using InSAR and seismic data. As expected for long-period surface wave source inversions for shallow earthquakes, the fault dip and rake angles are difficult to constrain, but we show that when using the best fitting Earth models, differences to InSAR estimates are reduced. Moreover, spurious deviations from a pure double-couple earthquake mechanism are on average smaller for the best fitting Earth models and the more accurate formulation of wave propagation. There are large differences between InSAR epicentral locations and those obtained in this study and, on average, no clear improvements to the Global CMT locations are achieved. This suggests that higher-resolution Earth models are necessary to further refine long-period CMT epicentral locations.

Evolution of a magma-driven earthquake swarm and triggering of the nearby Oldoinyo Lengai eruption, as resolved by InSAR, ground observations and elastic modeling, East African Rift, 2007

An earthquake swarm struck the North Tanzania Divergence, East African Rift over a 2 month period between July and September 2007. It produced approximately 70 M > 4 earthquakes (peak magnitude Mw 5.9), and extensive surface deformation, concurrent with eruptions at the nearby Oldoinyo Lengai volcano. The spatial and temporal evolution of the entire deformation event was resolved by Interferometric Synthetic Aperture Radar (InSAR) observations, owing to a particularly favorable acquisition programming of the Envisat and ALOS satellites, and was verified by detailed ground observations. Elastic modeling based on the InSAR measurements clearly distinguishes between normal faulting, which dominated during the first week of the event, and intermittent episodes of dike propagation, oblique dike opening and dike-induced faulting during the following month. A gradual decline in the intensity of deformation occurred over the final weeks. Our observations and modeling suggest that the sequence of events was initiated by pressurization of a deep-seated magma chamber below Oldoinyo Lengai which opened the way to lateral dike injection, and dike-induced faulting and seismicity. As dike intrusion terminated, silicate magma ascended the volcano conduit, reacted with the carbonatitic magma, and set off a major episode of explosive ash eruptions producing mixed silicate-carbonatitic ejecta. The rise of the silicate magma within the volcano conduit is attributed to bubble growth and buoyancy increase in the magma chamber either due to a temporary pressure drop after the termination of the diking event, or due to the dynamic effects of seismic wave passage from the earthquake swarm. Similar temporal associations between earthquake swarms and major explosive ash eruptions were observed at Oldoinyo Lengai over the past half century.

Combined GPS and InSAR Models of Postseismic Deformation from the Northridge Earthquake

Models of combined Global Positioning System (GPS) and Interferometric Synthetic Aperture Radar (InSAR) data collected in the region of the Northridge earthquake indicate that significant afterslip on the main fault occurred following the earthquake. Additional shallow deformation occurred to the west of the main rupture plane. Both data sets are consistent with logarithmic time-dependent behavior following the earthquake indicative of afterslip rather than postseismic relaxation. Aftershocks account for only about 10% of the postseismic motion. The two data sets are complimentary in determining the postseismic processes. Fault afterslip and shallow deformation dominate the deformation field in the two years following the earthquake. Lower crustal deformation may play an important role later in the earthquake cycle.