Multi-temporal Interferometry Research Articles

InSAR Monitoring Using Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) Techniques for Ground Deformation Measurement in Metropolitan Area of Concepción, Chile

InSAR capabilities allow us to understand ground deformations in large metropolitan areas, this is key to assessing site conditions in areas in an inherently expanding context. The multi-temporal interferometry of SAR data records ground surface displacement velocities over large metropolitan areas, identifying anomalous and potential geological hazards. The metropolitan city of Concepción, Chile, is an alluvial basin in one of the world’s most seismically active subduction zones, where many subduction earthquakes have occurred throughout history. In this study, we monitored the deformations of the ground surface in the metropolitan area of Concepción using two interferometric techniques, the first being Persistent Scatterer Interferometry (PSI) and the second, the Small Baseline Subset (SBAS) technique. To do this, we have used the same Sentinel-1 dataset, obtaining ground movement rates between 2019 and 2021. The velocities were aligned with the GNSS station available in the area. Ground deformation patterns show local deformations depending on factors such as soil type and heterogeneity, and regional deformations due to geographical location in the subduction area. Our results highlight the similarity of the deformation rates obtained with different processing techniques and have also allowed us to identify areas of deformation and compare them to site conditions. These results are essential to evaluate ground conditions and contribute to urban planning and risk management in highly seismic areas.

Automatic Mapping of Potential Landslides Using Satellite Multitemporal Interferometry

Mapping potential landslides is crucial to mitigating and preventing landslide disasters and understanding mountain landscape evolution. However, the existing methods to map and demonstrate potential landslides in mountainous regions are challenging to use and inefficient. Therefore, herein, we propose a method using hot spot analysis and convolutional neural networks to map potential landslides in mountainous areas at a regional scale based on ground deformation detection using multitemporal interferometry synthetic aperture radar. Ground deformations were detected by processing 76 images acquired from the descending and ascending orbits of the Sentinel-1A satellite. In total, 606 slopes with large ground deformations were automatically detected using hot spot analysis in the study area, and the extraction accuracy rate and the missing rate are 71.02% and 7.89%, respectively. Subsequently, based on the high-deformation areas and potential landslide conditioning factors, we compared the performance of convolutional neural networks with the random forest algorithm and constructed a classification model with the area under the curve (AUC), accuracy, recall, and precision for testing being 0.75, 0.75, 0.82, and 0.75, respectively. Our approach underpins the ability of interferometric synthetic aperture radar (InSAR) to map potential landslides regionally and provide a scientific foundation for landslide risk management. It also enables an accurate and efficient identification of potential landslides within a short period and under extremely hazardous conditions.

The 21 July 2020 Shaziba landslide in China: Results from multi-source satellite remote sensing

A catastrophic landslide occurred on 21 July 2020, 30 km from Enshi city, in Mazhe County of Hubei province, China. In this paper, we aimed to investigate the kinematic evolution and volumetric change related to this landslide using multi-source remote sensing measurements from synthetic aperture radar (SAR) and optical data. C-band Sentinel-1 and X-band TerraSAR-X SAR data are analyzed using several multi-temporal interferometry (MTI) time-series techniques including Persistent Scatterer Interferometry (PSI), Small Baseline subset (SBAS), and Combined eigenvalue maximum likelihood Phase Linking (CPL). The spatial pattern of surface deformation resulting from the interferometric analysis is then statistically analyzed to retrieve the pre-failure and post-failure displacements. Co-failure motions are analyzed using an image correlation technique applied to both the Planetscope and Sentinel-2 images. Moreover, 4 pairs of bistatic TerraSAR-X/TanDEM-X (TDX) data are utilized to generate high-precision digital elevation models (DEMs) and estimate the volumetric change related to the main slope failure.The pre-failure ground deformation analysis results suggest that the landslide was already active before the July 2020 failure, with the seasonality and hydraulic diffusivity being characteristics of a slow-moving landslide. Among the three different MTI methods applied, the CPL method results in a greater measurement points (MPs) density than the PSI and SBAS method when estimating the pre-failure movement of the Shaziba landslide. The July 2020 Shaziba disaster is divided into three main parts: (1) slightly horizontal deformation of 0.5–1.5 m within the northern part with ground and house cracks, (2) less collapse in the eastern part with horizontal motions reaching 30 m and (3) a highly eroded western part where vegetation was wholly lost in the main event, resulting in an collapse volume of approximately 4.98 million m3, out of which approximately around 3.4 million m3 was deposited and approximately 1.58 million m3 was washed away into the Qing River. After the failure, the marginal scrap of the main failure body, above crown of landslide and eastern part showed instability with rates of 20–30 mm/yr, suggesting that the failure zone may continue to expand.

Integration of multi-sensor MTInSAR and ground-based geomatic data for the analysis of non-linear displacements affecting the urban area of Chieuti, Italy

Slow instability phenomena can turn into rapid events, showing sudden accelerations and potentially developing in a threat for structures and people. In such scenarios, an in-depth understanding of the spatial and temporal evolution of the ground surface displacement field becomes essential for preventing potential catastrophes. In this work, Multi-Temporal Interferometry SAR (MTInSAR) technique based on COSMO-SkyMed and Sentinel-1 SAR acquisitions and ground measurements have been used to study an ongoing instability occurrence, affecting the urban area of Chieuti, a town located in the Southern Italy. Archives of C and X-band SAR data and geomatic monitoring observations spanning seven, five and one year, respectively, have been analyzed exploiting the complementary characteristics of these datasets. This enabled the accurate spatial-temporal characterization of the ground displacement field in the study area, the identification of sectors evidencing instability problems and a comprehensive reliability assessment of the detected displacements trends, characterized by strong non-linearities. Moreover, the multi-geometry DInSAR analysis allowed to evaluate the horizontal and vertical components of the detected motion, confirming the nature of the instability process, related to a deep landslide mechanism affecting the western slope of the town.

Evaluating Permafrost Degradation in the Tuotuo River Basin by MT-InSAR and LSTM Methods.

Permafrost degradation can significantly affect vegetation, infrastructure, and sustainable development on the Qinghai-Tibet Plateau (QTP). The permafrost on the QTP faces a risk of widespread degradation due to climate change and ecosystem disturbances; thus, monitoring its changes is critical. In this study, we conducted a permafrost surface deformation prediction over the Tuotuo River tributary watershed in the southwestern part of the QTP using the Long Short-Term Memory model (LSTM). The LSTM model was applied to the deformation information derived from a time series of Multi-Temporal Interferometry Synthetic Aperture Radar (MT-InSAR). First, we designed a quadtree segmentation-based Small BAseline Subset (SBAS) to monitor the seasonal permafrost deformation from March 2017 to April 2022. Then, the types of frozen soil were classified using the spatio-temporal deformation information and the temperature at the top of the permafrost. Finally, the time-series deformation trends of different types of permafrost were predicted using the LSTM model. The results showed that the deformation rates in the Tuotuo River Basin ranged between -80 to 60 mm/yr. Permafrost, seasonally frozen ground, and potentially degraded permafrost covered 7572.23, 900.87, and 921.70 km2, respectively. The LSTM model achieved high precision for frozen soil deformation prediction at the point scale, with a root mean square error of 4.457 mm and mean absolute error of 3.421 mm. The results demonstrated that deformation monitoring and prediction using MT-InSAR technology integrated with the LSTM model can be used to accurately identify types of permafrost over a large region and quantitatively evaluate its degradation trends.

Mapping of Mean Deformation Rates Based on APS-Corrected InSAR Data Using Unsupervised Clustering Algorithms

Different interferometric approaches have been developed over the past few decades to process SAR data and recover surface deformation, and each approach has advantages and limitations. Finding an accurate and reliable interval for preparing mean deformation rate maps (MDRMs) remains challenging. The primary purpose of this paper is to implement an application consisting of three unsupervised clustering algorithms (UCAs) for determining the best interval from SAR-derived deformation data, which can be used to interpret long-term deformation processes, such as subsidence, and identify displacement patterns. Considering Port Harcourt (in the Niger Delta) as the study area, it was essential to remove the sources of error in extracting deformation signals from SAR data, spatially ionospheric and tropospheric delays, before using UCAs to obtain its characteristics and real deformation data. Moreover, another purpose of this paper is to implement the advanced integration method (AIM) for atmospheric phase screen (APS) correction to enhance deformation signals obtained through different SAR processing approaches, including interferometric SARs (two-pass interferometry, InSAR) and multitemporal interferometry SARs (n-pass interferometry, DInSAR; permanent scatterer interferometry (PSI); and small baseline subset (SBAS)). Two methods were chosen to evaluate and find the best technique with which to create an MDRM: The first one was to compare the signals corrected by the AIM and the vertical component of the GPS station, which showed the AIM providing 58%, 42%, and 28% of the matching with GNSS station outputs for InSAR, PSI, and SBAS, respectively. Secondly, similarity measures and Davies–Bouldin index scores were implemented to find an accurate and reliable interval in which the SBAS technique with the unsupervised K-medians method has been chosen. Based on GNSS vertical deformation in a 500 m radius around the station, the SBAS K-medians technique expressed up to 5.5% better deformation patterns than the map of SAR processing techniques.

An Adaptive Multilook Approach of Multitemporal Interferometry Based on Complex Covariance Matrix for SAR Small Datasets

An Adaptive Multilook Approach of Multitemporal Interferometry Based on Complex Covariance Matrix for SAR Small Datasets

Machine Learning for Defining the Probability of Sentinel-1 Based Deformation Trend Changes Occurrence

The continuous monitoring of displacements occurring on the Earth surface by exploiting MTInSAR (Multi Temporal Interferometry SAR) Sentinel-1 data is a solid reality, as testified by the ongoing operational ground motion service in the Tuscany region (Central Italy). In this framework, anomalies of movement, i.e., accelerations or deceleration as seen by the time series of displacement of radar targets, are identified. In this work, a Machine Learning algorithm such as the Random Forest has been used to assess the probability of occurrence of the anomalies induced by slope instability and subsidence. About 20,000 anomalies (about 7000 and 13,000 for the slope instability and the subsidence, respectively) were collected between 2018 and 2020 and were used as input, while ten different variables were selected, five related to the morphological and geological setting of the study area and five to the radar characteristics of the data. The resulting maps may provide useful indications of where a sudden change of displacement trend may occur, analyzing the contribution of each factor. The cross-validation with the anomalies collected in a following timespan (2020–2021) and with official landslide and subsidence inventories provided by the regional authority has confirmed the reliability of the final maps. The adoption of a map for assessing the probability of the occurrence of MTInSAR anomalies may serve as an enhanced geohazard prevention measurement, to be periodically updated and refined in order to have the most precise knowledge possible of the territory.

Inferring subsidence characteristics in Wuhan (China) through multitemporal InSAR and hydrogeological analysis

Wuhan (China) is facing severe consolidation subsidence of soft soil and karst collapse hazards. To quantitatively explore the extent and causes of land subsidence in Wuhan, we performed multitemporal interferometry (MTI) analysis using synthetic aperture radar (SAR) data from the TerraSAR-X satellite from 2013 to 2017 and the Sentinel-1A satellite from 2015 to 2017. MTI results reveal four major subsidence zones in Wuhan, namely, Hankou (exceeding −6 cm/yr), Xudong-Qingshan (−3 cm/yr), Baishazhou-Jiangdi (−3 cm/yr), and Jianshe-Yangluo (−2 cm/yr). Accuracy assessment using 106 levelling benchmarks and cross-validation between the two InSAR-based results indicate an overall root-mean-square error (RMSE) of 2.5 and 3.1 mm/yr, respectively. Geophysical and geological analyses suggest that among the four major subsiding zones, Hankou, Xudong-Qingshan, and Jianshe-Yangluo are located in non-karstic soft soil areas, where shallow groundwater (< 30 m) declines driven by engineering dewatering and industrial water depletion contribute directly to soft soil compaction. Subsidence in the Baishazhou-Jiangdi zone develops in the karst terrain with abundant underground caves and fissures, which are major natural factors for gradual subsidence and karst collapse. Spatial variation analysis of the geological conditions indicates that the stage of karst development plays the most important role in influencing kart subsidence, followed by municipal construction, proximity to major rivers, and overlying soil structure. Moreover, land subsidence in this zone is affected more via coupling effects from multiple factors. Risk zoning analysis integrating subsidence horizontal gradient, InSAR deformation rates, and municipal construction density show that the high-risk areas in Wuhan are mainly distributed in the Tianxingzhou and Baishazhou-Jiangdi zone, and generally spread along the metro lines.

Monitoring Slope Creep Motion using Multi Temporal Interferometry Synthetic Aperture Radar in Semarang, Indonesia

Landslide is one type of slope movement, where the slope movement includes creep. Although creep movement does not have an impact on the risk of loss of life, this creep movement takes place constantly and invisible which has an impact on economic losses. In this study, a time-series monitoring was carried out from 2018 to 2020 to see the movement of the slopes in the study area using the Multi-Temporal Interferometry Synthetic Aperture Radar (MTInSAR). A time series method from Sentinel 1A/B data, which includes Trangkil Sejahtera Housing (PTS), Soegijapranata Catholic University (UNIKA), and 17 August 1945 University (UNTAG) in Semarang City, Indonesia. The results of data processing indicate that there are slope movement in the target location, namely Trangkil Sejahtera and Selorejo Housing (southwest of UNIKA). Based on BPBD 2021 data, landslides occurred in the Trangkil Baru Housing Center (to the north of PTS) and the Garang River landslide channel west of Selorejo. This shows that there is a link between crawling in 2018-2020 and landslides in 2021. Although the use of satellite data has some drawbacks, the results can be taken into consideration in building an early warning system and reducing losses due to landslides.

Seasonal Surface Fluctuation of a Slow-Moving Landslide Detected by Multitemporal Interferometry (MTI) on the Huafan University Campus, Northern Taiwan

A slow-moving landslide on the Huafan University campus, which is located on a dip slope in northern Taiwan, has been observed since 1990. However, reliable monitoring data are difficult to acquire after 2018 due to the lack of continuous maintenance of the field measurement equipment. In this study, the multitemporal interferometry (MTI) technique is applied with Sentinel-1 SAR images to monitor the slow-moving landslide from 2014–2019. The slow-moving areas detected by persistent scatterer (PS) pixels are consistent with the range of previous studies, which are based on in situ monitoring data and field surveys. According to the time series of the PS pixels, a long period gravity-induced deformation of the slow-moving landslide can be clearly observed. Moreover, a short period seasonal surface fluctuation of the slow-moving landslide, which has seldom been discussed before, can also be detected in this study. The seasonal surface fluctuation is in-phase with precipitation, which is inferred to be related to the geological and hydrological conditions of the study area. The MTI technique can compensate for the lack of surface displacement data, in this case, the Huafan University campus, and provide information for evaluating and monitoring slow-moving landslides for possible landslide early warning in the future.

Time Series InSAR Three-Dimensional Displacement Inversion Model of Coal Mining Areas Based on Symmetrical Features of Mining Subsidence

The three-dimensional (3-D) displacements of mining areas is the basis of studying the mining subsidence law and obtaining surface movement parameters. The traditional multi-temporal interferometry synthetic aperture radar (InSAR) technology can only obtain the surface deformation in line-of-sight (LOS) direction, even if some methods can obtain the 3-D displacements of mining area based on InSAR. However, it has high data requirements for data types, which are not conducive to the inversion of 3-D displacements. In this paper, the symmetry of the surface basin caused by mining subsidence under different mining degrees is analyzed. According to the basic symmetrical features of mining subsidence—that the surface vertical displacement and horizontal displacement in near horizontal coal seam is symmetrical with respect to the main section of the basin, combined with time series InSAR technology (TS-InSAR)—a novel method for retrieving the 3-D displacement results from a single-geometry InSAR dataset based on symmetrical features (hereafter referred to as the SGI-SF method) is proposed. The SGI-SF method first generates multi-temporal observations of LOS displacement from a single-geometry InSAR dataset, and then transforms them into multi-temporal observations of 3-D displacement datasets according to symmetrical features. There is no necessity to obtain the surface movement parameters from the measured data to calculate 3-D displacement fields. Finally, the time series of 3-D displacements are estimated from multi-temporal 3-D displacements using the singular value decomposition (SVD) method. Nine descending Sentinel-1 images from the Yulin mining area of China are used to test the proposed SGI-SF method. The results show that the average root mean square errors (RMSE) in the vertical and horizontal direction of the three-dimensional deformations are approximately 9.28 mm and 13.10 mm, respectively, which are much smaller than mining-induced displacements and can provide support for deformation monitoring in mining areas.

Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements Using Sentinel-1 Data

The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article.

Mechanism of Land Subsidence of Plateau Lakeside Kunming City Cluster (China) by MT-InSAR and Leveling Survey

Li, S.M.; Wang, Z.M.; Yuan, L.W.; Li, X.X.; Huang, Y.Z., and Guo, R., 2020. Mechanism of land subsidence of plateau lakeside Kunming city cluster (China) by MT-InSAR and leveling survey. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 666-675. Coconut Creek (Florida), ISSN 0749-0208.The Kunming city cluster (KCC) is located around the lakeside of Dianchi Lake, a plateau lake in Kunming Basin southwest of China, which is of complex geological structures and evolutionary history, and belongs to an earthquake fault depression area, where faults are developed and crustal stability is poor. Influenced by regional uplift and continuous subsidence of lakeside areas, the land subsidence characteristics of KCC are quite complex. The subsidence mechanism shows multi-inducement and multi-source property. In this paper, the land subsidence ranges, subsidence rate and subsidence spatio-temporal variation pattern of KCC were analyzed, mainly based on multi-temporal interferometry synthetic aperture radar (MT-InSAR), supplemented by leveling survey data, from 1986 to 2018. The effects of various controlling factors on land subsidence were studied respectively, such as geological structure, stratigraphic distribution, groundwater exploitation, and loads on the ground due to infrastructure construction and human activities, and the internal mechanism and response relation between the subsidence and the factors were studied too. The controlling factors and variation pattern of land subsidence in KCC were identified. The results have shown that the land subsidence of KCC is mainly affected by the tectonic activity in this area, fault basin landform sediments provide conditions for the development and speed up of land subsidence, and the previous land subsidence areas were closely related to the excessive exploitation of groundwater. However, in recent years, the subsidence areas expand continuously due to increases of loads from human activities. By analyzing the controlling factors and spatio-temporal variation pattern of land subsidence in the study areas, this paper has preliminarily revealed the land subsidence mechanism, which will provide reasonable theoretical reference and practical guidance for identifying and eliminating the potential land subsidence hazards and urban development planning in the plateau lakeside city cluster.

InSAR Time-Series Analysis for Monitoring Ground Displacement Trends in the Western Hellenic Arc: The Kythira Island, Greece

Kythira Island is situated at the western Hellenic Arc, which is a region of very high seismicity and tectonic activity. On 8 January 2006, a large seismic event of Mw = 6.7 occurred close to Kythira, in association with the Hellenic subduction zone. We present an extensive multi-temporal interferometry study of ground displacements in Kythira Island exploiting SAR data of a decade, from 2003 to 2009, and from 2015 to 2019. The line-of-sight displacement field for the 2003–2009 time period presents small-scale displacements that do not exceed −3 mm/y, identified to the East of Kythira’s airport, and 3 mm/y in the central part of the island. We exploit then Sentinel-1 data from 2015 to 2019, of both descending and ascending Sentinel-1 SAR imaging modes to decompose the line-of-sight measured deformation to vertical and east–west motion components. Higher vertical displacement rates characterize the central part of the island, with a maximum value of 5 mm/y. This short-term uplift rate exceeds by an order of magnitude the long-term geologic uplift rate of ~0.13 mm/y found in the island during the Quaternary. We discuss possible regional geophysical explanations for this discrepancy. Strike-slip components are detected in the N–E coast of the Potamos village, where horizontal displacements occur, with an east-ward trend and a maximum value of −3 mm/y. These insights are valuable input for the systematic monitoring of this high seismic risk island and the dynamic assessment of its hazard potential.

Monitoring subway construction using Sentinel-1 data: a case study in Bucharest, Romania

ABSTRACTIn Bucharest, new subway tunnels are under construction since 2011. The whole project of extending Bucharest underground infrastructure is due to be finished by 2030. The M-5 artery has been under construction since 2011 and ongoing. In December 2015, dewatering procedures in one of the metro stations caused serious damage to the surface infrastructure above, which subsided and partially collapsed in some locations. This paper relies on multi-temporal interferometry techniques to characterize displacement patterns of the ground surface above M-5 beltway between 2014 and 2018, and presents the capacity of Sentinel-1 satellite imagery to detect potential hazards in urban environments. Two stacks of Synthetic Aperture Radar (SAR) images acquired between October 2014 and October 2018 by the Sentinel-1 A and B satellites on ascending and descending orbits have been processed using the Delft Persistent Scatterer Interferometry algorithm (DePSI). The results indicate atypical acceleration in velocities starting in November 2015, prior to the described events, and manifesting until April 2016, when the ground was completely stabilized. The displacement trends and velocity values in the area of the Eroilor underground station were successfully validated using the ground-based Global Navigation Satellite Systems (GNSS) technique.

PS-InSAR Analysis of Sentinel-1 Data for Detecting Ground Motion in Temperate Oceanic Climate Zones: A Case Study in the Republic of Ireland

Regions of temperate oceanic climate have historically represented a challenge for the application of satellite-based multi-temporal SAR interferometry. The landscapes of such regions are commonly characterized by extensive, seasonally-variable vegetation coverage that can cause low temporal coherence and limit the detection capabilities of SAR imagery as acquired, for instance, by previous ERS-1/2 and ENVISAT missions. In this work, we exploited the enhanced resolution in space and time of the recently deployed Sentinel-1A/B SAR satellites to detect and monitor ground motions occurring in two study areas in the Republic of Ireland. The first, is a ~1800 km2 area spanning the upland karst of the Clare Burren and the adjacent mantled lowland karst of east Galway. The second, is an area of 100 km2 in Co. Meath spanning an active mine site. The available datasets, consisting of more than 100 images acquired in both ascending and descending orbits from April 2015 to March 2018, were processed by using the Permanent Scatterer approach. The obtained results highlight the presence of small-scale ground motions in both urban and natural environments with displacement rates along the satellite line of sight up to −17 mm/year. Localized subsidence was detected in recently built areas, along the infrastructure (both roads and railways), and over the mine site, while zones of subsidence, uplift, or both, have been recorded in a number of peatland areas. Furthermore, several measured target points indicate the presence of unstable areas along the coastline. Many of the detected movements were previously unknown. These results demonstrate the feasibility of adopting multi-temporal interferometry based on Sentinel-1 data for the detection and monitoring of mm-scale ground movements even over small areas (&lt;100 m2) in environments influenced by temperate oceanic climate.

A comparison of multi temporal interferometry techniques for landslide susceptibility assessment in urban area: an example on stigliano (MT), a town of Southern of Italy

In this work, Multi Temporal Interferometry techniques (MTI) based on advanced synthetic aperture radar differential interferometry (A-DInSAR) have been investigated for the monitoring of deformation phenomena in slow kinematics. A-DInSAR methodologies include both Coherence-based type, as well as Small Baseline Subset (SBAS) that Permanent Scatterers (PS). These techniques are capable to provide wide-area coverage and precise, spatially dense information on ground surface deformations. MTI techniques have been applied to the town of Stigliano (MT) in Basilicata Region (Southern Italy), where the social center building has been destroyed after the reactivation of a known landslide. A direct comparison of the results has been shown that PS and SBAS techniques are comparable in terms of obtained coherent areas and displacement patterns, with slightly different velocity values for individual points. In particular, PS furnished a range of velocity between −5/−25 mm/year, while for SBAS we found values around −5/−15 mm/year. Furthermore, on the crown of the landslide body, a Robotics Total Station measuring distance values on 24 points has been installed. The displacement values obtained are in agreement with the results of the MTI analysis, showing as these techniques could be a useful in the case of early-warning situations.

Ground Deformations in the Corinth Rift, Greece, Investigated Through the Means of SAR Multitemporal Interferometry

AbstractThe Corinth Rift is one of the narrowest and fastest extending continental regions worldwide and has one of the highest seismicity rates in the Euro‐Mediterranean region. At its western termination, several active faults are located beneath the city of Patras and the surrounding area, a region of major socioeconomic importance for Greece. Displacement rates for the period 2002–2010 obtained from ascending and descending ASAR/ENVISAT multitemporal interferometry are combined with Global Positioning System measurements from permanent and campaign stations to produce a map of vertical and east‐west ground velocities. Cross sections are produced in order to quantify the deformation rates with higher precision. In the vertical, the motion combines tectonic deformation, urban subsidence, and subsidence due to deltaic sediments compaction. In the city of Patras and through the gulf of Patras, the northern continuation of the 2008 Movri earthquake fault is connected to the oblique transform zone of Rio. Further east, our observations suggest the existence of postseismic deformation at Aigion in the 15 years following the Mw = 6.2, 15 June 1995 Aigion earthquake. The inferred deforming zone, assuming a simple slow slipping model, is located at the western end of the 1995 fault, with radius ~3.5 km, centroid depth ~4 km, and cumulated postseismic moment representing 28% of the coseismic. Alluvial fan deltas subside due to their compaction with a gradient that increases toward the shore. Several of those deltas are located in the hanging‐wall of active faults.

Monitoring of surface instability in tourist zones in Sanya (China) using high-resolution SAR interferometry

ABSTRACTSanya City, in China, is experiencing rapid urbanization and expansion of tourism, followed by various geological hazards. In this letter, 25 spotlight-mode TerraSAR-X images (acquired from March 2010 to November 2011) and Multi-temporal spaceborne Synthetic Aperture Radar (SAR) interferometry were used for the wide-area instability monitoring of a tourist zone in Sanya, China. The Persistent Scatterers (PSs) were first extracted in the settlement region, and then the Distributed Scatterers (DSs) were identified in the suburban and mountain regions to increase the monitoring extent; this was followed by a temporal-spatial filtering to reduce the decorrelation noise. The Small BAseline Subset (SBAS) method was used for the deformation estimation and instability mapping. The results show that several mountain slopes and urban grounds were unstable and subsiding, and potential security risks existed. The main reasons were human activities such as construction, forest harvesting, farming, mining, and even tourism. The findings highlight the effectiveness of PS-DS integrated multi-temporal interferometry in the coastal city and facilitate the hazard prevention, tourism planning and management decisions.