Co-seismic surface deformation and Aftershock analysis of the M 7.3, 17 Dec 2024 earthquake near Port Vila, Efate Island, Vanuatu: Insights from InSAR line of sight, coherence analysis & validation through high resolution satellite imagery

Co-seismic surface deformation and Aftershock analysis of the M 7.3, 17 Dec 2024 earthquake near Port Vila, Efate Island, Vanuatu: Insights from InSAR line of sight, coherence analysis & validation through high resolution satellite imagery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Co-seismic surface deformation and Aftershock analysis of the M 7.3, 17 Dec 2024 earthquake near Port Vila, Efate Island, Vanuatu: Insights from InSAR line of sight, coherence analysis & validation through high resolution satellite imagery Upendra Bhatt, Prakash Biswakarma This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7988784/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract M7.3 earthquake on 17 December 2024 occurred 25 Km offshore of Efate Island, Vanuatu, a seismically active region. This study analyses co-seismic ground deformation using Sentinel-1A SAR data and Differential Interferometric SAR (DInSAR) to measure line-of-sight (LOS) displacement, with special emphasis on coherence loss to identify regions of surface deformation. Ground truthing was performed using ground deformation points and high-resolution Pleiades and WorldView-3 imagery from UNOSAT rapid damage assessment report. Strong correlation between ground deformation and coherence loss confirmed its reliability in capturing surface instability and building damage. The line-of-sight displacement maps from November 2024 to February 2025 demonstrate variation in upliftment (upto + 0.084 meters) and subsidence (down to − 0.067 meters) values. Fluctuations in displacement rates were associated with aftershock activity. The aftershock analysis revealed that more than 50 aftershocks occurred in December 2024 following the mainshock, and the frequency of aftershocks gradually reduced through January and February 2025. The temporal analysis explained the importance of aftershocks in co- and post- seismic ground displacement analysis. These outcomes demonstrate the important role of combined geodetic and seismic analyses for assessing the dynamic seismic hazards experienced by the Vanuatu region and offers critical insights into the landscape adjustments following large earthquake events. Continues monitoring and in-depth aftershock analyses are important for reliable disaster risk reduction and infrastructure resilience planning. Seismic Hazard InSAR Co-seismic Deformation Coherence analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. INTRODUCTION For almost a decade, Vanuatu, an archipelago of 83 islands in the southwest Pacific, has led worldwide rankings of nations most vulnerable to natural disasters (Henderson et. al 2025). Earthquakes are primary hazards that trigger secondary hazards such as landslides and tsunamis, leading to mass casualties. On 17 December 2024 (01:47:26 UTC), a M 7.3 earthquake occurred 20 km off the west coast of Efate Island, Vanuatu, at a depth of 57 km, and was followed by numerous aftershocks. The earthquakes occurred along the subduction zone where the Australian plate is subducting beneath the Pacific plate. With a convergence rate of 16–17 cm per year, the Vanuatu subduction zone (formerly the New Hebrides subduction zone) is considered one of the fastest-moving plate boundaries globally (Roger et al. 2023). Various earthquakes of M > 7 that have been reported in and around Efate Island since 1900 are shown in Table-1. These strong earthquakes are often experienced by the population in Vanuatu and New Caledonia. Major earthquakes in and around Efate Island have caused major damage in and around Port Vila in terms of building damage, landslides, and rockslides. Several rockslides/landslides and damage to infrastructure were reported after M6.3 on 03 June 2009, M5.7 on 29 May 2009, and M7.2 on 03 January 2002 (USGS M 6.3; M 5.7; M7.2). These earthquake events highlight the seismic vulnerability of the region and highlight the need for monitoring earthquake-induced ground deformation in the region. Co-seismic deformation takes place after the earthquake occurrence. It is important to study co-seismic deformation in order to understand mechanism and effect of an earthquake. GNSS (Global Navigation Satellite Systems) and remote sensing methods viz. Interferometric Synthetic Aperture Radar (InSAR), are globally used techniques for deformation estimation (Agustan et al., 2019). On the other hand, GNSS provides point-based calculation of deformation, good spatial coverage is given by InSAR technique, making it more effective for deformation monitoring on a large scale. The InSAR (Interferometric Synthetic Aperture Radar) is a widely used method that estimates ground displacement providing higher spatial resolution with mm to cm accuracy (Gabriel et al., 1989; Zhang et al., 2015). The DInSAR (Differential Inteferometric Synthetic Aperture Radar) technique is widely used to provide line-of-sight (LOS) ground displacement over wide large region and recovers phase changes due to earthquakes (Golshadi et al., 2021; Reyes-Carmona et al., 2020; Zeni et al., 2011). But, DInSAR is restricted to a pair of images (2 images) and it is often affected by atmospheric decorrelation and noise. To overcome these limitations, MTInSAR (Multi-temporal Interferometric Synthetic Aperture Radar) techniques have been created such as SBAS (Small Baseline Subset) approach. SBAS approach allows the use of multiple SAR images with shortest spatio-temporal baselines for time-series analysis of ground deformation (Berardino et al., 2002; Lanari et al., 2007; Massonnet et al., 1993). In this study, SBAS is employed in order to investigate Pre-. Co-, and Post-seismic ground deformation corresponding to the December 17, 2024 earthquake of M 7.3, near Efate island, Vanuatu. With the use of Sentinel-1 SAR imagery, the objective is to quantify surface displacement, define spatial deformation patterns, and assess ground motion impacts on Efate Island. Moreover, the observed deformation is compared with the high-resolution optical satellite damage observations and reported landslides to better understand the correlation between seismic activity and surface impacts, ultimately contributing to enhanced seismic hazard assessment in the Vanuatu region. Table 1 Historical earthquakes of M > 7 that have been reported in and around Efate Island since 1900 Date Depth Magnitude Distance from Port Vila (Km) 02-12-1950 30 7.9 99.018 23-07-1961 20 7.3 62.776 17-12-2024 54.37 7.3 25.206 10-08-2010 25 7.3 34.483 20-08-2011 32 7.2 71.541 13-07-1994 33 7.2 150.922 03-01-2002 21 7.2 51.257 20-08-2011 28 7.1 64.004 05-03-1990 20.7 7.1 69.307 02-02-2012 23 7.1 125.597 2. STUDY AREA - TECTONICS & GEOLOGY The Vanuatu (formerly New Hebrides) island arc, situated in the southwestern Pacific, is an intra-oceanic arc formed by the convergence of the Australian Plate and the North Fiji Basin, making it a zone of intense seismic and volcanic activity (Legrand et al., 2024). The Vanuatu islands stretch for about 1200 km, from the Solomon Arc in the North to the Matthew-Hunter Ridge in the south (Sukale et al., 2009). This Archipelago represents a complex tectonic setting shaped by the interplay of several submarine basins and ridges, ongoing subduction, spreading within the North Fiji Basin, and possibly a paleo-subduction zone that ceased activity during the Late Miocene (Coleman, P. J., 1970; Hanuš, V., & Vaněk, J., 1983, 1991; & Sukale et al., 2009). The Vanuatu archipelago can be divided into 3 parts: ( 1 ) The Western part includes Torres islands, Espiritu Santo, and Malekula, with volcanic rocks of Late Eocene to Middle Miocene. ( 2 ) The Eastern part including Maewo and Pentecost, having volcanic rocks from the Late Eocene and basalt intrusion till Pliocene. ( 3 ) The Central chain includes the Banks islands (Vanua Lava, Gaua), Aoba, Ambrym, Lopevi, Epi, Karua, Tongoa, Efate, Erromango, Tanna, and Aneityum. The volcanic rocks range in age from Late Miocene to Early Pliocene to Holocene is present on the Southern Islands - Tanna, Erromango, Efate, and Epi (Coleman 1970; Mitchell & Warden 1971, Colley & Warden 1974). The Efate island group is located at 17°40´S and 168°20´E, between the southern and central zones of the Vanuatu Arc, in the southwestern Pacific. Efate is a sizable island formed by volcano-sedimentary rocks of Plio-Quaternary age. It is composed primarily of ash deposits and volcanic eruptive rocks. Significant tectonic uplifts also influenced its creation, and enormous Quaternary limestone and sedimentary terraces currently surround it (Régnier, M. et al., 2000). The focal mechanism from the United States Geological Survey (USGS) indicates that the 17 December 2024 earthquake is of oblique normal faulting type (Table 1 ). The detailed tectonic framework of entire Vanuatu Arc, its digital elevation model and lithology is shown in the Figure-1. Details of the 17-Jan 2024 earthquake and its moment tensor solution. Date Time (UTC) Epicentre Coordinates Depth (Km) Magnitude Nodal Plane (Fault plane) 1 Nodal Plane (Auxiliary 2 plane) Stress regime Data source Latitude Longitude Strike Dip Rake Strike Dip Rake 17-Dec-24 01:47:25 17.691°S 168.084°E 54.4 7.3 251° 88° 71° 155° 19° 173° Oblique Normal faulting USGS Table.2 Details of the 17 December 2024 earthquake and its moment tensor solution 3. DATASETS & METHODOLOGY 3.1 Seismological analysis The seismological analysis was performed in this study on characterization of the aftershock sequence following the mainshock event of M7.3 on 17 December 2024. The earthquake catalog was homogenized by converting all the magnitudes to moment magnitude (Mw). This was done using established empirical relationships given below. For events reported with surface wave magnitude (Ms), the following relationships were employed (Lolli et. al 2014). For Ms 5.5 : Mw = exp (2.133 + 0.063 Ms) − 6.205 ( 1 ) For Ms > 5.5 Mw = exp (-0.109 + 0.229 Ms) + 2.586 ( 2 ) For events with body wave magnitude (Mb), conversion to Mw was performed (Munafo et. al 2016). Mw = 23 Ml + 1.15 ( 3 ) These equations converted all the magnitudes into a uniform moment magnitude (Mw) which is necessary to perform accurate statistical analysis and interpretation. Magnitude of completeness (Mc) which is the lowest magnitude above which all the earthquake events are accurately identified is important to ensure the completeness and reliability of the earthquake catalog for aftershock analysis. Mc is calculated using Maximum Curvature (MAXC) method, which is globally used, non-parametric method (Wiemer, S et al., 2001). The starting step in Mc estimation involves identification of the point of maximum curvature on the frequency-magnitude distribution (FMD) curve. Maximum curvature identification is done by locating the magnitude interval where the rate of change (the first derivative) of the frequency-magnitude distribution reaches its peak value, indicates the peak counts for the catalog (Chasanah & Handoyo 2020). 3.2 InSAR Processing InSAR time series analysis is known as a powerful method for estimating deformation rates in both space and time (Berardino et al., 2002). Multiple methods are used for this purpose, including the Persistent Scatterer (PS) approach (Ferretti, Prati, & Rocca, 2000) and the Small Baseline Subset (SBAS) (Berardino et al., 2002), the SBAS method is utilized in this study. In order to assess surface displacement that occurred in Port Vila due to the M 7.3 earthquake on 17 December 2024, Sentinel-1 ascending orbit single look complex imagery was used. Only ascending orbit imagery could be utilized for this study since descending imagery was not available for the area during the required time period. The InSAR products used for this work were obtained by selecting single-look complex (SLC) scenes with interferometric wide (IW) beam mode through the Alaska Satellite Facility (ASF) InSAR on demand service (InSAR Product guide), which implements the GAMMA software package for the processing. A total of seven Sentinel-1 IW SLC images spanning 11 November 2024 to 22 January 2025 were processed. Among these, the 05 December 2024 image was selected as the pre-seismic reference, the 17 December 2024 image captured the co-seismic event, and the 29 December 2024 image represented the immediate post-seismic state. The pre-processing steps include selection of appropriate imagery, radiometric calibration, generation of a suitable digital elevation model (Copernicus GLO-30 meter resolution) and determination of burst overlaps. The digital elevation model tiles were geoid-corrected and resampled to match the resolution of the InSAR product. InSAR processing in ASF InSAR on Demand is completed using Interferometric Wide Swath Single Look Complex (IW SLC) as input. The older SLC image is always used as a reference imager, and the younger image is treated as a secondary image. Thus, the motion directed away from the SAR sensor is represented by negative values, whereas positive values indicate motion towards the satellite. DInSAR products captures ground deformation, the first step is to estimate topographic phase which is subtracted from the interferogram. Copernicus GLO-30 digital elevation model (DEM) with 30 meter resolution is used to estimate topographic phase. Once estimated, this phase component is subtracted, leaving only the deformation signal along with atmospheric noise and effects. The DEM tiles are selected to cover the input scenes and a geoid correction is applied, and DEM is resampled to match the resolution of the interferometry products (Hogenson, K et al., 2024). The precise co-registration of the SLC images is an important process for accurate estimation of phase. It is required for Sentinel-1 Interferometric Wide Swath (IW) data; this data is acquired in Terrain Observations with Progressive SAR scans (TOPSAR) mode. TOPSAR makes sure the image quality is consistent in terms of signal-to-noise ratio and distributed target ambiguity. Due to its burst-based acquisition geometry, even minor sub-pixel level misalignments can produce phase discontinuities at burst margins. Therefore, achieving high-accuracy co-registration is of great importance (Prats-Iraola, P et al., 2012 ; Kellndorfer, J et al., 2022). To overcome this, the co-registration process starts with the generation of a lookup table that relates the SLC image coordinates to ground range geometry. The already prepared DEM, a simulated topographic interferogram is generated at this stage. The co-registration process is carried out through a four-step iterative process: The estimated offset polynomial is used to resample the secondary SLC image, Image patches are matched between the master and secondary SLC through intensity cross-correlation, Estimation of azimuth and range offset polynomials from the image-matching results, and Creation of differential Interferogram using the raid of the simulated topographic phase. The offset polynomial is updated at each step by involving the newly estimated offsets during the iterative process. This process is repeated four times, and if the final offset remains higher than 0.02 pixels, then co-registration process is considered to be unsuccessful. When convergence is achieved, ESD (Enhanced Spectral Diversity) is applied to refine azimuth co-registration accuracy more than 1/100th of a pixel by analyzing phase mismatches in the overlap zones of nearby bursts. Following the ESD refinement, the co-registration cycle is repeated again using the updated offsets, and produces a wrapped interferogram. Once ESD (Enhanced Spectral Diversity) corrections are applied and the refined offsets are incorporated, the co-registration process produces a wrapped interferogram. The next process is phase unwrapping, which is carried out using the minimum-cost flow (MCF) triangulation algorithm. This process corrects 2 π discontinuities by adding appropriate multiples of 2 π to each pixels, it minimizes phase jumps except in the areas where it naturally occurs, such as radar layover areas or where deformation exceeds half of the radar wavelength along line-of-sight. Discontinuities introduced by decorrelation and thermal noise, also called residues, are also taken into consideration during this step. To improve unwrapping reliability, adaptive interferogram filtering is applied, which minimizes phase noise, enhances phase accuracy, and decreases residue counts. Once phase unwrapping is performed, a validity mask is generated to supervise the unwrapping process. This validity mask is based on thresholds applied to coherence and/or amplitude (backscatter intensity) for each pair of image. The amplitude is set to 0.0, so the coherence threshold primarily governs the masking process. The coherence values ranging from 0 (total decorrelation) to 1.0 (Perfect correlation) is estimated using normalized interferograms. A water mask is applied prior to phase unwrapping in order to prevent unwrapping errors over waterbodies, which excludes water pixels from the analysis. Phase unwrapping requires a reference point, and in ASF InSAR on demand products, the pixels with the highest coherence values are automatically selected for this process. Geocoding is applied to reproject pixels from SAR slant range coordinates into map-projected ground range space. The previously estimated lookup table is used to convert each pixel to the UTM zone of the DEM employed in this process. Nearest-neighbor resampling is performed to preserve the original pixel values, and finally the processed files are exported from GAMMA internal format to GeoTIFF. After geocoding, line-of-sight (LOS) displacement is estimated to quantify ground movement towards or away from the satellite sensor. A single interferogram can provide LOS displacement but it cannot separately resolve vertical and horizontal movement components. Both vertical and horizontal motion can be estimated using a time-series of interferograms. GNSS measurements can also be incorporated to provide displacement along both axes. All line-of-sight displacement values are expressed relative to a reference point, which is chosen automatically on the basis of high coherence values. It should be noted that this reference point is not always be optimal; if it is located within a deformed area or within a coherent pixel patch isolated by incoherent gaps, unwrapping quality can be compromised. Therefore, calculation of displacement using a single interferogram is not recommended, even with manual reference-point selection. The time series method allows for more accurate determination of deformation patterns while mitigating atmospheric artifacts and phase unwrapping errors. Hence, time-series approach is highly recommended (ASF-hyp3). The flowchart showing all the steps to calculate LOS-displacement is shown in Figure-2. 4. RESULTS & DISCUSSION 4.1 Seismic data analysis Aftershock identification Declustering of earthquake catalog is performed using Gardner and Knopoff appraoch and it identifield 87 aftershocks corresponding to M7.3 earthquake occurred during 17 December 2024. The process identified aftershocks using magnitude-dependent spatial and temporal criteria, assuring that the earthquake events analyzed were generated by the mainshock and eliminating background seismicity from the catalog. Spatial Distribution The depth versus longitude plot (Figure-3 Depth vs. Longitude) shows that the majority of aftershocks are spatially clustered between 167.6° and 168.4°, with depths mostly shallower than 40 km, and a few events extending to about 80 km. The location of mainshock event is positioned in center of this cluster, highlighting its role as the primary driver of the observed earthquake sequence observed sequence. Temporal Evolution Temporal distribution of aftershocks identified that highest percentage of aftershocks were struck immediately after mainshock event, with more than 50 + events occurred in December 2024 alone (Figure-3 Monthly aftershock counts). The rate of occurrences of aftershocks decreased rapidly in the month of January and February 2025. Magnitude Distribution Most numbers of aftershocks occurred were within Mw 4.4–5.8 range, which is revealed by magnitude versus depth and cumulative number plot (Figure-3 Magnitude vs. Depth with cumulative number). A sudden increase in event counts was reported after mainshock event. 4.2 Spatio-temporal distribution of ground deformation The pre-seismic, co-seismic & post-seismic deformation maps in the (figure-4) illustrate the spatio-temporal evolution of ground displacement in the study area over consecutive intervals from November 2024 to February 2025. These maps are based on Differential Interferometric Synthetic Aperture Radar (DInSAR), where blue color representing positive line-of-sight (LOS) values (uplift, or move towards the satellite), and brown colors denoting negative LOS values (Subsidence, or movement away from satellite). In the initial period (Figure-4, A-C), deformation is generally moderate across most of the region, with a few localized areas exhibiting higher uplift (blue) or subsidence (brown). After the mainshock on December 17, 2024, a notable increase in both the extent and magnitude of ground displacement is observed (Figure-X, D), especially in the central and northern part of Efate Island. The increased activity continues into the following interval (Figure-4, E), indicating that the ground is still adjusting after the mainshock event. After the mainshock event occurred (Fig. 4 , F-H), displacement is noticeable but it decreased gradually with spatial concentration and intensity, suggests a stabilization of the ground. As seen in all the maps, the persistent patches of deformation reveal zones of increased seismic impact and response of ground. These results indicate the long-lasting impact of the seismic sequence on the surface processes and the evolution of landscape during and after the mainshock. 4.3 Interferogram and Coherence Analysis The interferogram analysis of the earthquake that occurred on 17 December 2024 of M 7.3 near Efate Island, Vanuatu, is conducted using Sentinel-1 datasets. The generated wrapped interferogram does not show well-defined fringes across most of Efate Island, primarily due to low coherence in vegetated areas. The tropical forests, water bodies, and changes in land cover contribute to temporal decorrelation and volume scattering, resulting in a loss of interferometric phase (Luckman, A et al., 2000; Caduff, R et al., 2015 & Doblas, J et al., 2020). Figure-5 showing coherence was stable over urban areas during the pre-seismic period but significantly reduced in the co-seismic period, indicating possible surface displacement and structural disturbances. As a result, accurate deformation measurements are confined to coastal and urban areas, where infrastructure and bare land surfaces possess higher coherence values. The coastal and urban areas with limited vegetation maintain a consistent interferometric phase (Bovenga, F et al., 2006; Floris, M et al., 2019). This means that line-of-sight (LOS) estimates of deformation based on displacement are only correct in these high-coherence areas. Low-coherence regions were masked out in order to reduce uncertainty; only areas with high coherence were taken into consideration. 4.4 Line of sight displacement and ground verification This section represents the combined analysis of line-of-sight surface displacement estimated using InSAR with high-resolution optical satellite imagery to assess the severity of the 17 December 2024 earthquake in Port Vila, Vanuatu. Post-event imagery and damage reports were taken from the UNOSAT preliminary Assessment Report (M7.3, Dec. 17, 2024 Vanuatu earthquake), which includes datasets from Pleiades (20 December 2024) and WorldView-3 (18 December 2024) satellites. The locations assessed includes a collapsed building and two landslide-affected zone and their corresponding LOS displacement maps for the pre-seismic, co-seismic and post-seismic periods are analyzed in conjunction with these observations. SITE 1 : Collapsed Building - Structural Damage and Low Coherence At 17°44'11.2"S, 168°18'46.5"E, a collapsed building was observed to have blocked Kumul Highway and Rue Pasteur. This damage was captured by Pleiades imagery acquired on 20 December 2024, as reported in the UNOSAT assessment (Figure-6). LOS displacement analysis shows: Pre-seismic LOS : A almost uniform displacement of approximately − 0.55 cm, indicating stable conditions prior to the earthquake. Co-seismic LOS : No data available at the site due to the low coherence, likely caused by the structural damage and surface disturbance, which interfered with radar signal consistency. Post-seismic LOS : A moderate displacement of about + 1.6 cm is observed near the collapsed area. Although the site observed structural damage, the LOS signal is either weak or missing. This is attributed to temporal decorrelation and the limitations of radar in capturing vertical or sudden ground deformation, particularly in urban settings. SITE 2 : Possible Co-seismic Landslide - Ground Movement near Built up At 17°43'59"S, 168°19'3"E, a possible landslide damaged buildings in the vicinity (Figure-7), as captured by the Pleiades imagery (UNOSAT, 2024). Los data indicates: Pre-seismic LOS : Approximately − 0.50 cm, possibly reflecting slow slope movement. Co-seismic LOS : Ranges from + 0.13 to + 1.41 cm, suggesting ground uplift or horizontal displacement during the mainshock. Post–seismic LOS : Increases to + 2.19 cm to + 2.51 cm, indicating continued displacement, possibly due to afterslip or delayed slope readjustments. Here, the radar based deformation correlated well with the observed damage, confirming the landslide activity and ground instability following the earthquake. SITE 3 : Road Blockage from Landslide At 17°45'23.0"S, 168°18'24.0"E, a road near Ifira Shipping company was blocked due to a landslide (Figure-8), as reported by WorldView-3 imagery on 18 December 2024, also sourced via UNOSAT 2024 (M7.3, Dec. 17, 2024 Vanuatu earthquake). LOS displacement trends show: Pre-seismic LOS : Displacement ranging from − 0.87 cm to − 1.31 cm, likely reflecting pre-existing slope instability. Co-seismic LOS : Area shows decorrelation, likely due to vegetation or surface disruption. Post-seismic LOS : Positive displacement between + 0.59 to + 2.04 cm, indicating surface movement after the earthquake. This site also demonstrates how slop-related hazards can evolve post-seismically, with optical imagery and InSAR both confirming the ground motion. 5. Discussion This study investigates co-seismic deformation using InSAR line-of-sight displacement for M7.3 earthquake occurred on 17 December 2024 in Efate Island, Vanuatu. A distinct pattern of deformation and behavior of coherence is revealed by interferometric analysis across the Island. The coherent pixels were located mainly in built-up areas, where stable backscattering provides higher coherence. The temporal and volumetric decorrelation is suffered by densely vegetated mountainous region. Regardless of these constraints, high-resolution optical satellite data like Pleaides and WorldView-3 imagery, as well as UNOSAT rapid damage assessment, verified line-of-sight displacement derived from Sentinel-1 interferograms clearly defining areas of co-seismic and post-seismic displacements, demonstrating ground deformation, infrastructural damage, and slope failure. The integrated InSAR–optical analysis well illustrated that although SAR coherence loss restricted quantitative estimation in certain areas, it was also a qualitative means of assessing damage, particularly over cities where full decorrelation was coincident with building collapse. This research witnessed loss of coherence in the densely vegetated regions is consistent with the earlier InSAR observations undertaken in tropical rain-drenched regions like Dominica, Indonesia, and, Reunion, where phase instability due to high vegetation growth and soil moisture fluctuation can be offered (Pepe, A et al., 2017 & Fobert, M et al., 2021). Similar to the present study in Efate, in those studies, deformation was limited to areas with man-made structures or exposed soils. This illustrates the limitation of C-band Sentinel-1 data under high-density tropical forest cover, where tree canopy scattering prevails over backscattering. But the reliability of deformation mapping over urban areas in Port Vila is consistent with the earlier research on co-seismic deformation by InSAR that indicates that cities and open surfaces generally maintain phase coherence even under adverse atmospheric conditions (Bürgmann, R et al., 2000; Piter, A et al., 2024). The integration of InSAR line-of-sight deformation with optical data and UNOSAT products is an ideal methodology for immediate damage assessment after a significant earthquake. Multi-sensor fusion are strongly recommended for disaster post-analysis due to the fact that optical data yields contextual evidence like building damage and landslides, while InSAR yields quantitative deformations. A similar methodology was successfully applied in recent case histories in Japan, Nepal, and Italy where decorrelation patterns were employed as indicators of surface rupture and accumulated damage (Mondini, A et al., 2021). In this research, it shows a high correlation between areas with increased line-of-sight (LOS) displacement and identified structural damage supporting this integrated methodology. One of the most important results of our research is the post-seismic line-of-sight (LOS) displacement at detected landslide sites increasing, which suggests a reactivation of the slope after the mainshock. Other such post-seismic readjustments have been documented after significant earthquake events in other island or volcanic settings, where steep slopes are destabilized by co-seismic vibrations and subsequent precipitation or aftershock sequences drive ground motion (Tang, X et al., 2022). The present study thus provides a critical overview of the changing landslide dynamics of Efate Island, emphasizing the need for continued post-seismic surveillance in the months following such events. Yet, the weaknesses of this research should be noted. C-band Sentinel-1 data is offered by a good temporal resolution but introduce some challenges through decorrelation in very vegetated zones. L-band SAR data (e.g., ALOS-2/PULSAR-2), could enhance coherence and increase deformation signals in very vegetated zones. In the future, many avenues can be taken for research. A time-series InSAR technique like PSI or SBAS would be used to interpolate pre- and post-seismic deformation patterns so that precursors of slope instability and post-seismic displacement can be discerned. As a form of ground validation, the installation of GNSS stations or corner reflectors on key slopes and city sites would provide phase stability for extended monitoring. The integration with high-resolution optical and UAV-based photogrammetry can provide quantitative landslide estimates and supports InSAR-based displacements. Machine learning techniques could be used to automate co-seismic landsliding and damage to buildings through the incorporation of coherence loss, LOS displacement, and optical change detection. The findings of this research bring into focus the application of combining multi-sensor data sets to record the intricate surface action of small island environments to large earthquakes. Though the current findings lay a good basis for quick damage assessment, they also indicate that the integration of multi-geometry InSAR observations with ground verifications can greatly enhance the accuracy of deformation estimates. This combined strategy of radar time-series interferometry, ground truth, and high-resolution topographic mapping will enhance knowledge on earthquake-induced deformation in Efate Island and enhance the disaster preparedness and response for future seismic and geomorphic hazards in the region. The line-of-sight (LOS) displacement pattern across Efate Island provides valuable information about the fault kinematics and stress field of the 17 December 2024 Mw 7.3 earthquake. From the United States Geological Survey (M 7.3) moment-tensor solution (M7.3), the earthquake was hit by oblique-normal faulting with nodal planes that have a strike of approximately 251° and 155°, dipping at 88° and 19°, and with rakes of 71° and 173°, respectively (Table-2). These values indicate a largely extensional process, consistent with the tectonic environment of the Vanuatu Arc, experiencing active crustal extension behind the main subduction front (Legrand, D et al., 2024 & Bertrand, D et al., 2009). The LOS (line-of-sight) displacement observed from InSAR is negative line-of-sight values in the island interior and positive line-of-sight values on the western coast close to Port Vila. This trend is consistent with the deformation pattern induced by a west-dipping normal fault, with the footwall experiencing upliftment and elastic rebound and the hanging-wall block subsiding (Golshadi, Z et al., 2021 & Massonnet, D et al., 1993). The noted coastal subsidence in the regions surrounding Port Vila reflects downward hanging wall movement during slip on faults, while pressure inland reflects rebound of the footwall east of the rupturing area. These subsidence and uplift activities are typical features of crust-scale normal faulting mechanisms, as noted in earlier studies of deformation using InSAR (Lanari, R et al., 2007 & Bürgmann, R et al., 2000). This account is consistent with the global back-arc extensional setting of the Vanuatu island arc in which the Australian Plate is being subducted into the Pacific Plate at a convergent rate of approximately 16–17 cm yr⁻¹ (Roger, J et al., 2023). The inclined path of this convergence results in transtensional deformation of the upper plate (Hanuš, V & Vaněk, J 1983, 1991), promoting normal-faulting events that are conducive to extension of the upper plate rather than interplate thrusting (Coleman, P. J 1970; Mitchell, A.H.G & Warden, A.J 1971 & Colley, H. & Warden, A.J 1974). The 2024 earthquake is thus an intra-arc fault along a west-dipping normal fault in the overlying plate consistent with regional stress direction and back-arc tectonic setting (Legrand, D et al., 2024 & Regnier, M et al., 2000). Small-scale deformations in the pattern of deformation i.e., patches of small-scale subsidence and uplift in vegetated or steep terrain are attributed to slope instability, post-seismic relaxation, or radar decorrelation artifacts (Caduff, R et al., 2015; Pepe, A & Calò, F 2017; Fobert, M et al., 2021 & Tang, X et al., 2022). Nonetheless, overall geometry of the displacement, testified to by both seismological and InSAR data, favors a west-dipping normal fault as the dominant structure fitting crustal extension in the back-arc zone of central Vanuatu. Limitations This case study demonstrates both the utility and the limitations of LOS displacement data for analyzing earthquake-induced damage. While LOS measurements correspond well with observed ground deformation in landslide-affected areas, sites of collapsed buildings often lack strong LOS signals due to radar coherence loss and directional constraints. The following observations were made: InSAR-based line-of-sight displacements may not entirely capture vertical or sudden collapses. Low coherence areas can limit deformation signals where major deformation occurs. Fine-resolution optical datasets, as provided by UNOSAT rapid damage assessment, are important for field verification and validation of deformation patterns. These results demonstrate the significance of a multi-sensor approach that uses both radar and optical datasets. Future research could benefit from the integration of both ascending and descending orbit acquisitions and applying 3-dimensional displacement decompositions to accurately monitor deformation. RECOMMENDATIONS FOR FUTURE WORK Incorporate descending-orbit Sentinel-1 data to enable 3D displacement decomposition. Utilize GNSS or ground markers for validation and reference point verification. Analyze terrain factors, including slope, lithology, and land cover, to contextualize landslide triggers. Apply statistical coherence and unwrapping quality metrics to assess data reliability. Develop deformation hazard maps to inform infrastructure planning and risk mitigation. 6. Conclusion The Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) approach was applied successfully to capture surface deformation corresponding to the December 17, 2024 earthquake in the Vanuatu region. The analysis observed co-seismic and post-seismic displacement and associated landslide activity effectively. The temporal and spatial decorrelation in highly vegetated areas with low coherence is a limitation. However, integration of high-resolution optical data significantly improved the interpretation of displacement patterns and landslide identification. The combination of optical and SAR data does not only explain the coherence gap but also improves our understanding about the extent and nature of terrain disturbances. Future research should include both ascending and descending orbit SAR acquisitions and integration of in-situ validation datasets to further improve deformation measurements and the reliability of hazard assessment. Overall, SBAS-InSAR effectively analyzed earthquake-induced deformation and associated landslide hazard assessment in Vanuatu and other tectonically active regions. Declarations Competing Interests “The authors have no relevant financial or non-financial interests to disclose.” Funding “The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.” Author Contributions Conceptualization: [Upendra Bhatt]; Methodology: [Upendra Bhatt]; Formal analysis and investigation: [Upendra Bhatt]; Writing - original draft preparation: [Upendra Bhatt]; Writing - review and editing: [Prakash Biswakarma]; Funding acquisition: [NA]; Resources: [Upendra Bhatt, Prakash Biswakarma]; Supervision: [Prakash Biswakarma] ACKNOWLEDGEMENT The author(s) declare that no specific funding or external support was received for this research. 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mechanism.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/d3fc33f91711234003381352.png"},{"id":98053562,"identity":"70591740-a4bf-4679-a548-cb93018068f2","added_by":"auto","created_at":"2025-12-12 09:33:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79120,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFlowchart of InSAR framework to compute line of sight displacement.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/7cc9b4f83e3feac547645fc4.png"},{"id":98428223,"identity":"0127d9a5-a66c-4300-a808-15a11f4cfb36","added_by":"auto","created_at":"2025-12-17 16:41:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98632,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSeismic data analysis showing depth vs longitude, magnitude vs month with cumulative number of events, and monthly aftershock counts.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/bb5c8c04577287b16533c0a8.png"},{"id":98053570,"identity":"df153317-0ab4-482e-a896-783a5b84ac3f","added_by":"auto","created_at":"2025-12-12 09:33:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1033498,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePre-seismic, Co-seismic, and Post-seismic Line of sight (LOS) displacements from 2024/11/11 to 2025/02/16.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/a020de94ade062d9a970ac8f.png"},{"id":98427495,"identity":"b8e0da92-1669-40ee-80ee-092fc3bebdd0","added_by":"auto","created_at":"2025-12-17 16:40:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":833750,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePre-seismic, Co-seismic and Post-seismic Coherence variation\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/ee07a2cd435a33f34f298c2f.png"},{"id":98053568,"identity":"54fc2b18-fc21-456f-9736-40483d1b5d26","added_by":"auto","created_at":"2025-12-12 09:33:18","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2016243,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSite-1 showing the structural damage and corresponding low coherence.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/d5f7c1b44fe36877ca0f9895.png"},{"id":98053566,"identity":"091b6a49-cd2f-4fc8-8171-78fbc5b1385e","added_by":"auto","created_at":"2025-12-12 09:33:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1683833,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSite-2 showing landslide activities and its corresponding coherence.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/bc9ac17a11c52929564682d5.png"},{"id":98428238,"identity":"2f8412d9-187c-484f-9381-d06b58d71086","added_by":"auto","created_at":"2025-12-17 16:41:50","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1522837,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSite-3 showing road blockage by landslide activity and its corresponding coherence.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/02adec8f0d0468a19f973c57.png"},{"id":109249678,"identity":"4f9f7842-a186-454f-a865-20c7f027ecb5","added_by":"auto","created_at":"2026-05-14 08:58:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9637573,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7988784/v1/d93a0d51-7514-4770-b25d-8959a3d4860a.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eCo-seismic surface deformation and Aftershock analysis of the M 7.3, 17 Dec 2024 earthquake near Port Vila, Efate Island, Vanuatu: Insights from InSAR line of sight, coherence analysis \u0026amp; validation through high resolution satellite imagery\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eFor almost a decade, Vanuatu, an archipelago of 83 islands in the southwest Pacific, has led worldwide rankings of nations most vulnerable to natural disasters (Henderson et. al 2025). Earthquakes are primary hazards that trigger secondary hazards such as landslides and tsunamis, leading to mass casualties.\u003c/p\u003e\u003cp\u003eOn 17 December 2024 (01:47:26 UTC), a M 7.3 earthquake occurred 20 km off the west coast of Efate Island, Vanuatu, at a depth of 57 km, and was followed by numerous aftershocks. The earthquakes occurred along the subduction zone where the Australian plate is subducting beneath the Pacific plate. With a convergence rate of 16\u0026ndash;17 cm per year, the Vanuatu subduction zone (formerly the New Hebrides subduction zone) is considered one of the fastest-moving plate boundaries globally (Roger et al. 2023).\u003c/p\u003e\u003cp\u003eVarious earthquakes of M\u0026thinsp;\u0026gt;\u0026thinsp;7 that have been reported in and around Efate Island since 1900 are shown in Table-1. These strong earthquakes are often experienced by the population in Vanuatu and New Caledonia. Major earthquakes in and around Efate Island have caused major damage in and around Port Vila in terms of building damage, landslides, and rockslides. Several rockslides/landslides and damage to infrastructure were reported after M6.3 on 03 June 2009, M5.7 on 29 May 2009, and M7.2 on 03 January 2002 (USGS M 6.3; M 5.7; M7.2). These earthquake events highlight the seismic vulnerability of the region and highlight the need for monitoring earthquake-induced ground deformation in the region.\u003c/p\u003e\u003cp\u003eCo-seismic deformation takes place after the earthquake occurrence. It is important to study co-seismic deformation in order to understand mechanism and effect of an earthquake. GNSS (Global Navigation Satellite Systems) and remote sensing methods viz. Interferometric Synthetic Aperture Radar (InSAR), are globally used techniques for deformation estimation (Agustan et al., 2019). On the other hand, GNSS provides point-based calculation of deformation, good spatial coverage is given by InSAR technique, making it more effective for deformation monitoring on a large scale.\u003c/p\u003e\u003cp\u003eThe InSAR (Interferometric Synthetic Aperture Radar) is a widely used method that estimates ground displacement providing higher spatial resolution with mm to cm accuracy (Gabriel et al., 1989; Zhang et al., 2015). The DInSAR (Differential Inteferometric Synthetic Aperture Radar) technique is widely used to provide line-of-sight (LOS) ground displacement over wide large region and recovers phase changes due to earthquakes (Golshadi et al., 2021; Reyes-Carmona et al., 2020; Zeni et al., 2011). But, DInSAR is restricted to a pair of images (2 images) and it is often affected by atmospheric decorrelation and noise. To overcome these limitations, MTInSAR (Multi-temporal Interferometric Synthetic Aperture Radar) techniques have been created such as SBAS (Small Baseline Subset) approach. SBAS approach allows the use of multiple SAR images with shortest spatio-temporal baselines for time-series analysis of ground deformation (Berardino et al., 2002; Lanari et al., 2007; Massonnet et al., 1993).\u003c/p\u003e\u003cp\u003eIn this study, SBAS is employed in order to investigate Pre-. Co-, and Post-seismic ground deformation corresponding to the December 17, 2024 earthquake of M 7.3, near Efate island, Vanuatu. With the use of Sentinel-1 SAR imagery, the objective is to quantify surface displacement, define spatial deformation patterns, and assess ground motion impacts on Efate Island. Moreover, the observed deformation is compared with the high-resolution optical satellite damage observations and reported landslides to better understand the correlation between seismic activity and surface impacts, ultimately contributing to enhanced seismic hazard assessment in the Vanuatu region.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eHistorical earthquakes of M\u0026thinsp;\u0026gt;\u0026thinsp;7 that have been reported in and around Efate Island since 1900\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepth\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMagnitude\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDistance from Port Vila (Km)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e02-12-1950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e99.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e23-07-1961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e62.776\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17-12-2024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.206\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10-08-2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.483\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20-08-2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e71.541\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13-07-1994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e150.922\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e03-01-2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.257\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20-08-2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e64.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e05-03-1990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.307\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e02-02-2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e125.597\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"2. STUDY AREA - TECTONICS \u0026 GEOLOGY","content":"\u003cp\u003eThe Vanuatu (formerly New Hebrides) island arc, situated in the southwestern Pacific, is an intra-oceanic arc formed by the convergence of the Australian Plate and the North Fiji Basin, making it a zone of intense seismic and volcanic activity (Legrand et al., 2024). The Vanuatu islands stretch for about 1200 km, from the Solomon Arc in the North to the Matthew-Hunter Ridge in the south (Sukale et al., 2009). This Archipelago represents a complex tectonic setting shaped by the interplay of several submarine basins and ridges, ongoing subduction, spreading within the North Fiji Basin, and possibly a paleo-subduction zone that ceased activity during the Late Miocene (Coleman, P. J., 1970; Hanuš, V., \u0026amp; Vaněk, J., 1983, 1991; \u0026amp; Sukale et al., 2009). The Vanuatu archipelago can be divided into 3 parts: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) The Western part includes Torres islands, Espiritu Santo, and Malekula, with volcanic rocks of Late Eocene to Middle Miocene. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) The Eastern part including Maewo and Pentecost, having volcanic rocks from the Late Eocene and basalt intrusion till Pliocene. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) The Central chain includes the Banks islands (Vanua Lava, Gaua), Aoba, Ambrym, Lopevi, Epi, Karua, Tongoa, Efate, Erromango, Tanna, and Aneityum. The volcanic rocks range in age from Late Miocene to Early Pliocene to Holocene is present on the Southern Islands - Tanna, Erromango, Efate, and Epi (Coleman 1970; Mitchell \u0026amp; Warden 1971, Colley \u0026amp; Warden 1974).\u003c/p\u003e\u003cp\u003eThe Efate island group is located at 17\u0026deg;40\u0026acute;S and 168\u0026deg;20\u0026acute;E, between the southern and central zones of the Vanuatu Arc, in the southwestern Pacific. Efate is a sizable island formed by volcano-sedimentary rocks of Plio-Quaternary age. It is composed primarily of ash deposits and volcanic eruptive rocks. Significant tectonic uplifts also influenced its creation, and enormous Quaternary limestone and sedimentary terraces currently surround it (R\u0026eacute;gnier, M. et al., 2000). The focal mechanism from the United States Geological Survey (USGS) indicates that the 17 December 2024 earthquake is of oblique normal faulting type (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The detailed tectonic framework of entire Vanuatu Arc, its digital elevation model and lithology is shown in the Figure-1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"14\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDetails\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eof the\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17-Jan\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eearthquake and\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eits\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003emoment tensor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003esolution.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTime (UTC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEpicentre Coordinates\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDepth (Km)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMagnitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNodal Plane (Fault plane)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eNodal Plane (Auxiliary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e2 plane)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eStress regime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eData source\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLatitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLongitude\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eStrike\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eDip\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRake\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eStrike\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eDip\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eRake\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e17-Dec-24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e01:47:25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.691\u0026deg;S\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e168.084\u0026deg;E\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e251\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e88\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e71\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e155\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e19\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003e173\u0026deg;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u003cp\u003eOblique Normal faulting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c14\"\u003e\u003cp\u003eUSGS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eTable.2 Details of the 17 December 2024 earthquake and its moment tensor solution\u003c/span\u003e\u003c/p\u003e"},{"header":"3. DATASETS \u0026 METHODOLOGY","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Seismological analysis\u003c/h2\u003e\u003cp\u003eThe seismological analysis was performed in this study on characterization of the aftershock sequence following the mainshock event of M7.3 on 17 December 2024. The earthquake catalog was homogenized by converting all the magnitudes to moment magnitude (Mw). This was done using established empirical relationships given below.\u003c/p\u003e\u003cp\u003eFor events reported with surface wave magnitude (Ms), the following relationships were employed (Lolli et. al 2014).\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFor Ms 5.5 :\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMw\u0026thinsp;=\u0026thinsp;exp (2.133\u0026thinsp;+\u0026thinsp;0.063 Ms) \u0026minus;\u0026thinsp;6.205 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eFor Ms\u0026thinsp;\u0026gt;\u0026thinsp;5.5\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMw\u0026thinsp;=\u0026thinsp;exp (-0.109\u0026thinsp;+\u0026thinsp;0.229 Ms)\u0026thinsp;+\u0026thinsp;2.586 (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFor events with body wave magnitude (Mb), conversion to Mw was performed (Munafo et. al 2016).\u003c/p\u003e\u003cp\u003eMw\u0026thinsp;=\u0026thinsp;23 Ml\u0026thinsp;+\u0026thinsp;1.15 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThese equations converted all the magnitudes into a uniform moment magnitude (Mw) which is necessary to perform accurate statistical analysis and interpretation.\u003c/p\u003e\u003cp\u003eMagnitude of completeness (Mc) which is the lowest magnitude above which all the earthquake events are accurately identified is important to ensure the completeness and reliability of the earthquake catalog for aftershock analysis. Mc is calculated using Maximum Curvature (MAXC) method, which is globally used, non-parametric method (Wiemer, S et al., 2001). The starting step in Mc estimation involves identification of the point of maximum curvature on the frequency-magnitude distribution (FMD) curve. Maximum curvature identification is done by locating the magnitude interval where the rate of change (the first derivative) of the frequency-magnitude distribution reaches its peak value, indicates the peak counts for the catalog (Chasanah \u0026amp; Handoyo 2020).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.2 InSAR Processing\u003c/h2\u003e\u003cp\u003eInSAR time series analysis is known as a powerful method for estimating deformation rates in both space and time (Berardino et al., 2002). Multiple methods are used for this purpose, including the Persistent Scatterer (PS) approach (Ferretti, Prati, \u0026amp; Rocca, 2000) and the Small Baseline Subset (SBAS) (Berardino et al., 2002), the SBAS method is utilized in this study.\u003c/p\u003e\u003cp\u003eIn order to assess surface displacement that occurred in Port Vila due to the M 7.3 earthquake on 17 December 2024, Sentinel-1 ascending orbit single look complex imagery was used. Only ascending orbit imagery could be utilized for this study since descending imagery was not available for the area during the required time period. The InSAR products used for this work were obtained by selecting single-look complex (SLC) scenes with interferometric wide (IW) beam mode through the Alaska Satellite Facility (ASF) InSAR on demand service (InSAR Product guide), which implements the GAMMA software package for the processing. A total of seven Sentinel-1 IW SLC images spanning 11 November 2024 to 22 January 2025 were processed. Among these, the 05 December 2024 image was selected as the pre-seismic reference, the 17 December 2024 image captured the co-seismic event, and the 29 December 2024 image represented the immediate post-seismic state.\u003c/p\u003e\u003cp\u003eThe pre-processing steps include selection of appropriate imagery, radiometric calibration, generation of a suitable digital elevation model (Copernicus GLO-30 meter resolution) and determination of burst overlaps. The digital elevation model tiles were geoid-corrected and resampled to match the resolution of the InSAR product. InSAR processing in ASF InSAR on Demand is completed using Interferometric Wide Swath Single Look Complex (IW SLC) as input. The older SLC image is always used as a reference imager, and the younger image is treated as a secondary image. Thus, the motion directed away from the SAR sensor is represented by negative values, whereas positive values indicate motion towards the satellite. DInSAR products captures ground deformation, the first step is to estimate topographic phase which is subtracted from the interferogram. Copernicus GLO-30 digital elevation model (DEM) with 30 meter resolution is used to estimate topographic phase. Once estimated, this phase component is subtracted, leaving only the deformation signal along with atmospheric noise and effects. The DEM tiles are selected to cover the input scenes and a geoid correction is applied, and DEM is resampled to match the resolution of the interferometry products (Hogenson, K et al., 2024).\u003c/p\u003e\u003cp\u003eThe precise co-registration of the SLC images is an important process for accurate estimation of phase. It is required for Sentinel-1 Interferometric Wide Swath (IW) data; this data is acquired in Terrain Observations with Progressive SAR scans (TOPSAR) mode. TOPSAR makes sure the image quality is consistent in terms of signal-to-noise ratio and distributed target ambiguity. Due to its burst-based acquisition geometry, even minor sub-pixel level misalignments can produce phase discontinuities at burst margins. Therefore, achieving high-accuracy co-registration is of great importance (Prats-Iraola, P et al., 2012 ; Kellndorfer, J et al., 2022).\u003c/p\u003e\u003cp\u003eTo overcome this, the co-registration process starts with the generation of a lookup table that relates the SLC image coordinates to ground range geometry. The already prepared DEM, a simulated topographic interferogram is generated at this stage. The co-registration process is carried out through a four-step iterative process:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe estimated offset polynomial is used to resample the secondary SLC image,\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eImage patches are matched between the master and secondary SLC through intensity cross-correlation,\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eEstimation of azimuth and range offset polynomials from the image-matching results, and\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCreation of differential Interferogram using the raid of the simulated topographic phase.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThe offset polynomial is updated at each step by involving the newly estimated offsets during the iterative process. This process is repeated four times, and if the final offset remains higher than 0.02 pixels, then co-registration process is considered to be unsuccessful. When convergence is achieved, ESD (Enhanced Spectral Diversity) is applied to refine azimuth co-registration accuracy more than 1/100th of a pixel by analyzing phase mismatches in the overlap zones of nearby bursts. Following the ESD refinement, the co-registration cycle is repeated again using the updated offsets, and produces a wrapped interferogram.\u003c/p\u003e\u003cp\u003eOnce ESD (Enhanced Spectral Diversity) corrections are applied and the refined offsets are incorporated, the co-registration process produces a wrapped interferogram. The next process is phase unwrapping, which is carried out using the minimum-cost flow (MCF) triangulation algorithm. This process corrects 2 π discontinuities by adding appropriate multiples of 2 π to each pixels, it minimizes phase jumps except in the areas where it naturally occurs, such as radar layover areas or where deformation exceeds half of the radar wavelength along line-of-sight. Discontinuities introduced by decorrelation and thermal noise, also called residues, are also taken into consideration during this step. To improve unwrapping reliability, adaptive interferogram filtering is applied, which minimizes phase noise, enhances phase accuracy, and decreases residue counts.\u003c/p\u003e\u003cp\u003eOnce phase unwrapping is performed, a validity mask is generated to supervise the unwrapping process. This validity mask is based on thresholds applied to coherence and/or amplitude (backscatter intensity) for each pair of image. The amplitude is set to 0.0, so the coherence threshold primarily governs the masking process. The coherence values ranging from 0 (total decorrelation) to 1.0 (Perfect correlation) is estimated using normalized interferograms. A water mask is applied prior to phase unwrapping in order to prevent unwrapping errors over waterbodies, which excludes water pixels from the analysis.\u003c/p\u003e\u003cp\u003ePhase unwrapping requires a reference point, and in ASF InSAR on demand products, the pixels with the highest coherence values are automatically selected for this process. Geocoding is applied to reproject pixels from SAR slant range coordinates into map-projected ground range space. The previously estimated lookup table is used to convert each pixel to the UTM zone of the DEM employed in this process. Nearest-neighbor resampling is performed to preserve the original pixel values, and finally the processed files are exported from GAMMA internal format to GeoTIFF.\u003c/p\u003e\u003cp\u003eAfter geocoding, line-of-sight (LOS) displacement is estimated to quantify ground movement towards or away from the satellite sensor. A single interferogram can provide LOS displacement but it cannot separately resolve vertical and horizontal movement components. Both vertical and horizontal motion can be estimated using a time-series of interferograms. GNSS measurements can also be incorporated to provide displacement along both axes. All line-of-sight displacement values are expressed relative to a reference point, which is chosen automatically on the basis of high coherence values. It should be noted that this reference point is not always be optimal; if it is located within a deformed area or within a coherent pixel patch isolated by incoherent gaps, unwrapping quality can be compromised. Therefore, calculation of displacement using a single interferogram is not recommended, even with manual reference-point selection. The time series method allows for more accurate determination of deformation patterns while mitigating atmospheric artifacts and phase unwrapping errors. Hence, time-series approach is highly recommended (ASF-hyp3). The flowchart showing all the steps to calculate LOS-displacement is shown in Figure-2.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. RESULTS \u0026 DISCUSSION","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e4.1 Seismic data analysis\u003c/h2\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eAftershock identification\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eDeclustering of earthquake catalog is performed using Gardner and Knopoff appraoch and it identifield 87 aftershocks corresponding to M7.3 earthquake occurred during 17 December 2024. The process identified aftershocks using magnitude-dependent spatial and temporal criteria, assuring that the earthquake events analyzed were generated by the mainshock and eliminating background seismicity from the catalog.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eSpatial Distribution\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe depth versus longitude plot (Figure-3 Depth vs. Longitude) shows that the majority of aftershocks are spatially clustered between 167.6\u0026deg; and 168.4\u0026deg;, with depths mostly shallower than 40 km, and a few events extending to about 80 km. The location of mainshock event is positioned in center of this cluster, highlighting its role as the primary driver of the observed earthquake sequence observed sequence.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eTemporal Evolution\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTemporal distribution of aftershocks identified that highest percentage of aftershocks were struck immediately after mainshock event, with more than 50\u0026thinsp;+\u0026thinsp;events occurred in December 2024 alone (Figure-3 Monthly aftershock counts). The rate of occurrences of aftershocks decreased rapidly in the month of January and February 2025.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eMagnitude Distribution\u003c/b\u003e\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eMost numbers of aftershocks occurred were within Mw 4.4\u0026ndash;5.8 range, which is revealed by magnitude versus depth and cumulative number plot (Figure-3 Magnitude vs. Depth with cumulative number). A sudden increase in event counts was reported after mainshock event.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e4.2 Spatio-temporal distribution of ground deformation\u003c/h2\u003e\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe pre-seismic, co-seismic \u0026amp; post-seismic deformation maps in the (figure-4) illustrate the spatio-temporal evolution of ground displacement in the study area over consecutive intervals from November 2024 to February 2025. These maps are based on Differential Interferometric Synthetic Aperture Radar (DInSAR), where blue color representing positive line-of-sight (LOS) values (uplift, or move towards the satellite), and brown colors denoting negative LOS values (Subsidence, or movement away from satellite).\u003c/p\u003e\u003cp\u003eIn the initial period (Figure-4, A-C), deformation is generally moderate across most of the region, with a few localized areas exhibiting higher uplift (blue) or subsidence (brown). After the mainshock on December 17, 2024, a notable increase in both the extent and magnitude of ground displacement is observed (Figure-X, D), especially in the central and northern part of Efate Island. The increased activity continues into the following interval (Figure-4, E), indicating that the ground is still adjusting after the mainshock event. After the mainshock event occurred (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, F-H), displacement is noticeable but it decreased gradually with spatial concentration and intensity, suggests a stabilization of the ground. As seen in all the maps, the persistent patches of deformation reveal zones of increased seismic impact and response of ground. These results indicate the long-lasting impact of the seismic sequence on the surface processes and the evolution of landscape during and after the mainshock.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.3 Interferogram and Coherence Analysis\u003c/h2\u003e\u003cp\u003eThe interferogram analysis of the earthquake that occurred on 17 December 2024 of M 7.3 near Efate Island, Vanuatu, is conducted using Sentinel-1 datasets. The generated wrapped interferogram does not show well-defined fringes across most of Efate Island, primarily due to low coherence in vegetated areas. The tropical forests, water bodies, and changes in land cover contribute to temporal decorrelation and volume scattering, resulting in a loss of interferometric phase (Luckman, A et al., 2000; Caduff, R et al., 2015 \u0026amp; Doblas, J et al., 2020). Figure-5 showing coherence was stable over urban areas during the pre-seismic period but significantly reduced in the co-seismic period, indicating possible surface displacement and structural disturbances. As a result, accurate deformation measurements are confined to coastal and urban areas, where infrastructure and bare land surfaces possess higher coherence values. The coastal and urban areas with limited vegetation maintain a consistent interferometric phase (Bovenga, F et al., 2006; Floris, M et al., 2019). This means that line-of-sight (LOS) estimates of deformation based on displacement are only correct in these high-coherence areas. Low-coherence regions were masked out in order to reduce uncertainty; only areas with high coherence were taken into consideration.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.4 Line of sight displacement and ground verification\u003c/h2\u003e\u003cp\u003eThis section represents the combined analysis of line-of-sight surface displacement estimated using InSAR with high-resolution optical satellite imagery to assess the severity of the 17 December 2024 earthquake in Port Vila, Vanuatu. Post-event imagery and damage reports were taken from the UNOSAT preliminary Assessment Report (M7.3, Dec. 17, 2024 Vanuatu earthquake), which includes datasets from Pleiades (20 December 2024) and WorldView-3 (18 December 2024) satellites. The locations assessed includes a collapsed building and two landslide-affected zone and their corresponding LOS displacement maps for the pre-seismic, co-seismic and post-seismic periods are analyzed in conjunction with these observations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSITE 1 : Collapsed Building - Structural Damage and Low Coherence\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAt 17\u0026deg;44'11.2\"S, 168\u0026deg;18'46.5\"E, a collapsed building was observed to have blocked Kumul Highway and Rue Pasteur. This damage was captured by Pleiades imagery acquired on 20 December 2024, as reported in the UNOSAT assessment (Figure-6). LOS displacement analysis shows:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePre-seismic LOS\u003c/b\u003e : A almost uniform displacement of approximately \u0026minus;\u0026thinsp;0.55 cm, indicating stable conditions prior to the earthquake.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCo-seismic LOS\u003c/b\u003e : No data available at the site due to the low coherence, likely caused by the structural damage and surface disturbance, which interfered with radar signal consistency.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePost-seismic LOS\u003c/b\u003e : A moderate displacement of about\u0026thinsp;+\u0026thinsp;1.6 cm is observed near the collapsed area.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eAlthough the site observed structural damage, the LOS signal is either weak or missing. This is attributed to temporal decorrelation and the limitations of radar in capturing vertical or sudden ground deformation, particularly in urban settings.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSITE 2 : Possible Co-seismic Landslide - Ground Movement near Built up\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAt 17\u0026deg;43'59\"S, 168\u0026deg;19'3\"E, a possible landslide damaged buildings in the vicinity (Figure-7), as captured by the Pleiades imagery (UNOSAT, 2024). Los data indicates:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePre-seismic LOS\u003c/b\u003e : Approximately \u0026minus;\u0026thinsp;0.50 cm, possibly reflecting slow slope movement.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCo-seismic LOS\u003c/b\u003e : Ranges from +\u0026thinsp;0.13 to +\u0026thinsp;1.41 cm, suggesting ground uplift or horizontal displacement during the mainshock.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePost\u0026ndash;seismic LOS\u003c/b\u003e : Increases to +\u0026thinsp;2.19 cm to +\u0026thinsp;2.51 cm, indicating continued displacement, possibly due to afterslip or delayed slope readjustments.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eHere, the radar based deformation correlated well with the observed damage, confirming the landslide activity and ground instability following the earthquake.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSITE 3 : Road Blockage from Landslide\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAt 17\u0026deg;45'23.0\"S, 168\u0026deg;18'24.0\"E, a road near Ifira Shipping company was blocked due to a landslide (Figure-8), as reported by WorldView-3 imagery on 18 December 2024, also sourced via UNOSAT 2024 (M7.3, Dec. 17, 2024 Vanuatu earthquake). LOS displacement trends show:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePre-seismic LOS\u003c/b\u003e : Displacement ranging from \u0026minus;\u0026thinsp;0.87 cm to \u0026minus;\u0026thinsp;1.31 cm, likely reflecting pre-existing slope instability.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eCo-seismic LOS\u003c/b\u003e : Area shows decorrelation, likely due to vegetation or surface disruption.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePost-seismic LOS\u003c/b\u003e : Positive displacement between +\u0026thinsp;0.59 to +\u0026thinsp;2.04 cm, indicating surface movement after the earthquake.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThis site also demonstrates how slop-related hazards can evolve post-seismically, with optical imagery and InSAR both confirming the ground motion.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThis study investigates co-seismic deformation using InSAR line-of-sight displacement for M7.3 earthquake occurred on 17 December 2024 in Efate Island, Vanuatu. A distinct pattern of deformation and behavior of coherence is revealed by interferometric analysis across the Island. The coherent pixels were located mainly in built-up areas, where stable backscattering provides higher coherence. The temporal and volumetric decorrelation is suffered by densely vegetated mountainous region. Regardless of these constraints, high-resolution optical satellite data like Pleaides and WorldView-3 imagery, as well as UNOSAT rapid damage assessment, verified line-of-sight displacement derived from Sentinel-1 interferograms clearly defining areas of co-seismic and post-seismic displacements, demonstrating ground deformation, infrastructural damage, and slope failure. The integrated InSAR\u0026ndash;optical analysis well illustrated that although SAR coherence loss restricted quantitative estimation in certain areas, it was also a qualitative means of assessing damage, particularly over cities where full decorrelation was coincident with building collapse.\u003c/p\u003e\u003cp\u003eThis research witnessed loss of coherence in the densely vegetated regions is consistent with the earlier InSAR observations undertaken in tropical rain-drenched regions like Dominica, Indonesia, and, Reunion, where phase instability due to high vegetation growth and soil moisture fluctuation can be offered (Pepe, A et al., 2017 \u0026amp; Fobert, M et al., 2021). Similar to the present study in Efate, in those studies, deformation was limited to areas with man-made structures or exposed soils. This illustrates the limitation of C-band Sentinel-1 data under high-density tropical forest cover, where tree canopy scattering prevails over backscattering. But the reliability of deformation mapping over urban areas in Port Vila is consistent with the earlier research on co-seismic deformation by InSAR that indicates that cities and open surfaces generally maintain phase coherence even under adverse atmospheric conditions (B\u0026uuml;rgmann, R et al., 2000; Piter, A et al., 2024).\u003c/p\u003e\u003cp\u003eThe integration of InSAR line-of-sight deformation with optical data and UNOSAT products is an ideal methodology for immediate damage assessment after a significant earthquake. Multi-sensor fusion are strongly recommended for disaster post-analysis due to the fact that optical data yields contextual evidence like building damage and landslides, while InSAR yields quantitative deformations. A similar methodology was successfully applied in recent case histories in Japan, Nepal, and Italy where decorrelation patterns were employed as indicators of surface rupture and accumulated damage (Mondini, A et al., 2021). In this research, it shows a high correlation between areas with increased line-of-sight (LOS) displacement and identified structural damage supporting this integrated methodology.\u003c/p\u003e\u003cp\u003eOne of the most important results of our research is the post-seismic line-of-sight (LOS) displacement at detected landslide sites increasing, which suggests a reactivation of the slope after the mainshock. Other such post-seismic readjustments have been documented after significant earthquake events in other island or volcanic settings, where steep slopes are destabilized by co-seismic vibrations and subsequent precipitation or aftershock sequences drive ground motion (Tang, X et al., 2022). The present study thus provides a critical overview of the changing landslide dynamics of Efate Island, emphasizing the need for continued post-seismic surveillance in the months following such events.\u003c/p\u003e\u003cp\u003eYet, the weaknesses of this research should be noted. C-band Sentinel-1 data is offered by a good temporal resolution but introduce some challenges through decorrelation in very vegetated zones. L-band SAR data (e.g., ALOS-2/PULSAR-2), could enhance coherence and increase deformation signals in very vegetated zones.\u003c/p\u003e\u003cp\u003eIn the future, many avenues can be taken for research. A time-series InSAR technique like PSI or SBAS would be used to interpolate pre- and post-seismic deformation patterns so that precursors of slope instability and post-seismic displacement can be discerned. As a form of ground validation, the installation of GNSS stations or corner reflectors on key slopes and city sites would provide phase stability for extended monitoring. The integration with high-resolution optical and UAV-based photogrammetry can provide quantitative landslide estimates and supports InSAR-based displacements. Machine learning techniques could be used to automate co-seismic landsliding and damage to buildings through the incorporation of coherence loss, LOS displacement, and optical change detection.\u003c/p\u003e\u003cp\u003eThe findings of this research bring into focus the application of combining multi-sensor data sets to record the intricate surface action of small island environments to large earthquakes. Though the current findings lay a good basis for quick damage assessment, they also indicate that the integration of multi-geometry InSAR observations with ground verifications can greatly enhance the accuracy of deformation estimates. This combined strategy of radar time-series interferometry, ground truth, and high-resolution topographic mapping will enhance knowledge on earthquake-induced deformation in Efate Island and enhance the disaster preparedness and response for future seismic and geomorphic hazards in the region.\u003c/p\u003e\u003cp\u003eThe line-of-sight (LOS) displacement pattern across Efate Island provides valuable information about the fault kinematics and stress field of the 17 December 2024 Mw 7.3 earthquake. From the United States Geological Survey (M 7.3) moment-tensor solution (M7.3), the earthquake was hit by oblique-normal faulting with nodal planes that have a strike of approximately 251\u0026deg; and 155\u0026deg;, dipping at 88\u0026deg; and 19\u0026deg;, and with rakes of 71\u0026deg; and 173\u0026deg;, respectively (Table-2). These values indicate a largely extensional process, consistent with the tectonic environment of the Vanuatu Arc, experiencing active crustal extension behind the main subduction front (Legrand, D et al., 2024 \u0026amp; Bertrand, D et al., 2009).\u003c/p\u003e\u003cp\u003eThe LOS (line-of-sight) displacement observed from InSAR is negative line-of-sight values in the island interior and positive line-of-sight values on the western coast close to Port Vila. This trend is consistent with the deformation pattern induced by a west-dipping normal fault, with the footwall experiencing upliftment and elastic rebound and the hanging-wall block subsiding (Golshadi, Z et al., 2021 \u0026amp; Massonnet, D et al., 1993). The noted coastal subsidence in the regions surrounding Port Vila reflects downward hanging wall movement during slip on faults, while pressure inland reflects rebound of the footwall east of the rupturing area. These subsidence and uplift activities are typical features of crust-scale normal faulting mechanisms, as noted in earlier studies of deformation using InSAR (Lanari, R et al., 2007 \u0026amp; B\u0026uuml;rgmann, R et al., 2000).\u003c/p\u003e\u003cp\u003eThis account is consistent with the global back-arc extensional setting of the Vanuatu island arc in which the Australian Plate is being subducted into the Pacific Plate at a convergent rate of approximately 16\u0026ndash;17 cm yr⁻\u0026sup1; (Roger, J et al., 2023). The inclined path of this convergence results in transtensional deformation of the upper plate (Hanuš, V \u0026amp; Vaněk, J 1983, 1991), promoting normal-faulting events that are conducive to extension of the upper plate rather than interplate thrusting (Coleman, P. J 1970; Mitchell, A.H.G \u0026amp; Warden, A.J 1971 \u0026amp; Colley, H. \u0026amp; Warden, A.J 1974). The 2024 earthquake is thus an intra-arc fault along a west-dipping normal fault in the overlying plate consistent with regional stress direction and back-arc tectonic setting (Legrand, D et al., 2024 \u0026amp; Regnier, M et al., 2000).\u003c/p\u003e\u003cp\u003eSmall-scale deformations in the pattern of deformation i.e., patches of small-scale subsidence and uplift in vegetated or steep terrain are attributed to slope instability, post-seismic relaxation, or radar decorrelation artifacts (Caduff, R et al., 2015; Pepe, A \u0026amp; Cal\u0026ograve;, F 2017; Fobert, M et al., 2021 \u0026amp; Tang, X et al., 2022). Nonetheless, overall geometry of the displacement, testified to by both seismological and InSAR data, favors a west-dipping normal fault as the dominant structure fitting crustal extension in the back-arc zone of central Vanuatu.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis case study demonstrates both the utility and the limitations of LOS displacement data for analyzing earthquake-induced damage. While LOS measurements correspond well with observed ground deformation in landslide-affected areas, sites of collapsed buildings often lack strong LOS signals due to radar coherence loss and directional constraints. The following observations were made:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInSAR-based line-of-sight displacements may not entirely capture vertical or sudden collapses.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLow coherence areas can limit deformation signals where major deformation occurs.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eFine-resolution optical datasets, as provided by UNOSAT rapid damage assessment, are important for field verification and validation of deformation patterns.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThese results demonstrate the significance of a multi-sensor approach that uses both radar and optical datasets. Future research could benefit from the integration of both ascending and descending orbit acquisitions and applying 3-dimensional displacement decompositions to accurately monitor deformation.\u003c/p\u003e\u003cp\u003e\u003cb\u003eRECOMMENDATIONS FOR FUTURE WORK\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eIncorporate descending-orbit Sentinel-1 data to enable 3D displacement decomposition.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eUtilize GNSS or ground markers for validation and reference point verification.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eAnalyze terrain factors, including slope, lithology, and land cover, to contextualize landslide triggers.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eApply statistical coherence and unwrapping quality metrics to assess data reliability.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eDevelop deformation hazard maps to inform infrastructure planning and risk mitigation.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThe Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) approach was applied successfully to capture surface deformation corresponding to the December 17, 2024 earthquake in the Vanuatu region. The analysis observed co-seismic and post-seismic displacement and associated landslide activity effectively. The temporal and spatial decorrelation in highly vegetated areas with low coherence is a limitation. However, integration of high-resolution optical data significantly improved the interpretation of displacement patterns and landslide identification. The combination of optical and SAR data does not only explain the coherence gap but also improves our understanding about the extent and nature of terrain disturbances.\u003c/p\u003e\u003cp\u003eFuture research should include both ascending and descending orbit SAR acquisitions and integration of in-situ validation datasets to further improve deformation measurements and the reliability of hazard assessment. Overall, SBAS-InSAR effectively analyzed earthquake-induced deformation and associated landslide hazard assessment in Vanuatu and other tectonically active regions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;The authors have no relevant financial or non-financial interests to disclose.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003e\u0026ldquo;The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u0026rdquo;\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\u003cp\u003eConceptualization: [Upendra Bhatt]; Methodology: [Upendra Bhatt]; Formal analysis and investigation: [Upendra Bhatt]; Writing - original draft preparation: [Upendra Bhatt]; Writing - review and editing: [Prakash Biswakarma]; Funding acquisition: [NA]; Resources: [Upendra Bhatt, Prakash Biswakarma]; Supervision: [Prakash Biswakarma]\u003c/p\u003e\u003ch2\u003eACKNOWLEDGEMENT\u003c/h2\u003e\u003cp\u003eThe author(s) declare that no specific funding or external support was received for this research.\u003c/p\u003e\u003ch2\u003eData Availability Statement\u003c/h2\u003e\u003cp\u003eData will be provided upon request.\u003c/p\u003e\u003cp\u003e\u0026ldquo;The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026rdquo;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHenderson R, Bedford S, Spriggs M, Yona S, Phillip I, Shing R, Valentin F, Harvey C (2025) Kuwae, Epi and Tongoa Islands: Transformations of a Volcanic Landscape in Central Vanuatu. 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Indonesia J Phys Conf Ser 1805(1):012009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1088/1742-6596/1805/1/012009\u003c/span\u003e\u003cspan address=\"10.1088/1742-6596/1805/1/012009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWiemer S, Wyss M, Z\u0026uacute;\u0026ntilde;iga F (2001) cookbook. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.seismo.ethz.ch/prod/software/zmap/box_feeder/cookbook.pdf\u003c/span\u003e\u003cspan address=\"http://www.seismo.ethz.ch/prod/software/zmap/box_feeder/cookbook.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Seismic Hazard, InSAR, Co-seismic Deformation, Coherence analysis","lastPublishedDoi":"10.21203/rs.3.rs-7988784/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7988784/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eM7.3 earthquake on 17 December 2024 occurred 25 Km offshore of Efate Island, Vanuatu, a seismically active region. This study analyses co-seismic ground deformation using Sentinel-1A SAR data and Differential Interferometric SAR (DInSAR) to measure line-of-sight (LOS) displacement, with special emphasis on coherence loss to identify regions of surface deformation.\u003c/p\u003e\u003cp\u003eGround truthing was performed using ground deformation points and high-resolution Pleiades and WorldView-3 imagery from UNOSAT rapid damage assessment report. Strong correlation between ground deformation and coherence loss confirmed its reliability in capturing surface instability and building damage.\u003c/p\u003e\u003cp\u003eThe line-of-sight displacement maps from November 2024 to February 2025 demonstrate variation in upliftment (upto\u0026thinsp;+\u0026thinsp;0.084 meters) and subsidence (down to \u0026minus;\u0026thinsp;0.067 meters) values. Fluctuations in displacement rates were associated with aftershock activity. The aftershock analysis revealed that more than 50 aftershocks occurred in December 2024 following the mainshock, and the frequency of aftershocks gradually reduced through January and February 2025. The temporal analysis explained the importance of aftershocks in co- and post- seismic ground displacement analysis.\u003c/p\u003e\u003cp\u003eThese outcomes demonstrate the important role of combined geodetic and seismic analyses for assessing the dynamic seismic hazards experienced by the Vanuatu region and offers critical insights into the landscape adjustments following large earthquake events. Continues monitoring and in-depth aftershock analyses are important for reliable disaster risk reduction and infrastructure resilience planning.\u003c/p\u003e","manuscriptTitle":"Co-seismic surface deformation and Aftershock analysis of the M 7.3, 17 Dec 2024 earthquake near Port Vila, Efate Island, Vanuatu: Insights from InSAR line of sight, coherence analysis \u0026amp; validation through high resolution satellite imagery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-12 09:33:14","doi":"10.21203/rs.3.rs-7988784/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25958ec2-35dd-4eaf-b2d3-4ab76976b39e","owner":[],"postedDate":"December 12th, 2025","published":true,"recentEditorialEvents":[{"type":"decision","content":"Reject after review","date":"2026-05-13T17:10:00+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T21:11:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-12 09:33:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7988784","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7988784","identity":"rs-7988784","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}