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This study verifies the practicality of using finite element analysis for strain and deformation analysis in regions with sparse GNSS stations. A digital 3D terrain model is constructed using DEM data, and regional rock mass properties are integrated to simulate geological structures, resulting in the development of a 3D geological finite element model (FEM) using the ANSYS Workbench module. Gravity load and thermal constraints are applied to derive directional strain and deformation solutions, and the model results are compared to actual strain and tilt measurements from the Jiujiang Seismic Station (JSS). The results show that temperature variations significantly affect strain and deformation, particularly due to the elevation difference between the mountain base and summit. Higher temperatures increase thermal strain, causing tensile effects, while lower temperatures reduce thermal strain, leading to compressive effects. Strain and deformation patterns are strongly influenced by geological structures, gravity, and topography, with valleys experiencing tensile strain and ridges undergoing compression. The deformation trend indicates a southwestward movement across the study area. A comparison of FEM results with ten years of strain and tiltmeter data from JSS reveals a strong correlation between the model predictions and actual measurements, with correlation coefficients of 0.6 and 0.75 for strain in the NS and EW directions, and 0.8 and 0.9 for deformation in the NS and EW directions, respectively. These findings confirm that the 3D geological FEM is applicable for regional strain and deformation analysis, providing a feasible alternative in areas with limited GNSS monitoring. This method provides valuable insights into crustal deformation in regions with sparse strain and deformation measurement data. [ABSTRACT FROM AUTHOR]

The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data points and challenges with topographical and structural variations. Our approach addresses these issues by analysing displacements from 30 images captured by the X-band SAR satellite, TerraSAR-X, over two years. We tested each InSAR parameter to develop an optimal set of parameters, applying the technique to a post-tensioned PSC (pre-stressed concrete) box bridge. Our findings revealed a recurring arch-shaped elevation along the bridge, attributed to temporal changes and long-term deformation. Further analysis showed a strong correlation between this deformation pattern and average surrounding temperature. This indicates that our technique can effectively identify micro-displacements due to temperature changes and structural deformation. Thus, the technique provides a theoretical foundation for improved SAR monitoring of large-scale social overhead capital (SOC) facilities, ensuring efficient maintenance and management. [ABSTRACT FROM AUTHOR]

The investigation of reactivated landslides in the alpine-canyon areas suffers the difficult accessibility of precipitous terrain. In particular, when reactivated landslides occur along the major roads, efforts are focused on measuring ground surface displacements during road construction. Nevertheless, the ancient landslide deposits may reactivate after several years of road operation, while they show a stable state during the road construction. The characterization of this type of reactivated landslides is challenging, due to their complex mechanism and the limited monitoring data. Appropriate multi-source data can provide insights into deformation fields and enhance the understanding of landslide mechanisms, ensuring the outperformance of remedial works. This paper reports a recent Tangjiawan reactivated landslide along the Wenchuan-Maerkang Highway in Li County, China. The outcomes, including satellite InSAR, in situ real-time monitoring, and detailed ground and UAV investigation, conducted at this landslide are presented. Early deformation of the reactivated landslide began from 2019, with an InSAR-derived velocity of −11.7 mm/year, furthermore, a significant subsidence of about 21.2 mm, which occurred within a span of only 12 days from 3 June 2020 to 15 June 2020, was observed. The deformation characteristics derived from in situ monitoring during the remedial works were likely firstly associated with the initial unreinforced slope condition and the heavy rainfall. Subsequently, the displacement evolution transformed into deformation induced by time-dependent reduction in slope strength under rainfall conditions. The existing of unconsolidated deposits derived from ancient landslides, along with a fragile geo-structure consisting of rock blocks and gravels interlayered with breccias, exacerbated by large relief created a predisposition for landslide reactivation. Furthermore, 13 days of antecedent cumulative rainfall totaling 224.5 mm directly triggered the occurrence of a landslide event. The significance and implications of integrating multiple monitoring techniques are emphasized. [ABSTRACT FROM AUTHOR]

The standard Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique, which is commonly used for surface motion analysis, assumes linear deformation velocities. While effective for monitoring urban subsidence over short periods, it falls short when dealing with non-linear, earthquake-related deformations over extended timeframes. To address this limitation, we use a non-linear PSInSAR technique, which is an enhancement of PSInSAR, to identify non-linear deformation patterns. We processed Sentinel-1A images from ascending and descending orbits in the Islamabad/Rawalpindi region from December 2015 to January 2023 using non-linear PSInSAR. By calculating the differences in deformation, we analyzed surface movements and assessed the impact of the 2017 earthquake on urban areas. Our findings reveal that the earthquake significantly increased the deformation in ascending and descending orbit tracks, with an average deformation of up to 70 mm/yr and a line-of-sight movement of up to 30 mm/yr. Our observations indicate that the deformation is directed towards the line of sight in the north and south of the deformed area, suggesting subsidence between the two uplifting faults, potentially linked to a concealed fault line along the deformation zone boundary. This contradicts previous arguments, suggesting that water extraction is the leading cause of deformation. Our analysis with non-linear PSInSAR demonstrates that tectonics play a significant role in deformation, providing valuable insights into tectonic-activity-induced deformations in urban areas over the long term. [ABSTRACT FROM AUTHOR]

This study verifies the practicality of using finite element analysis for strain and deformation analysis in regions with sparse GNSS stations. A digital 3D terrain model is constructed using DEM data, and regional rock mass properties are integrated to simulate geological structures, resulting in the development of a 3D geological finite element model (FEM) using the ANSYS Workbench module. Gravity load and thermal constraints are applied to derive directional strain and deformation solutions, and the model results are compared to actual strain and tilt measurements from the Jiujiang Seismic Station (JSS). The results show that temperature variations significantly affect strain and deformation, particularly due to the elevation difference between the mountain base and summit. Higher temperatures increase thermal strain, causing tensile effects, while lower temperatures reduce thermal strain, leading to compressive effects. Strain and deformation patterns are strongly influenced by geological structures, gravity, and topography, with valleys experiencing tensile strain and ridges undergoing compression. The deformation trend indicates a southwestward movement across the study area. A comparison of FEM results with ten years of strain and tiltmeter data from JSS reveals a strong correlation between the model predictions and actual measurements, with correlation coefficients of 0.6 and 0.75 for strain in the NS and EW directions, and 0.8 and 0.9 for deformation in the NS and EW directions, respectively. These findings confirm that the 3D geological FEM is applicable for regional strain and deformation analysis, providing a feasible alternative in areas with limited GNSS monitoring. This method provides valuable insights into crustal deformation in regions with sparse strain and deformation measurement data.

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

Catastrophic landslides occur frequently in Guizhou Province, China, and the landslides in this area have special geomorphological, geological, and anthropogenic features. In order to detect and explore the distribution pattern and control factors of active landslides in Guizhou, firstly, a total of 693 active landslides throughout Guizhou Province were mapped based on the deformation rate, which was obtained by spatiotemporal filtering and Intermittent Small Baseline Subset (ISBAS) Interferometric Synthetic Aperture Radar (InSAR) techniques. Then, the relationships between the detected landslides and elevation, aspect, slope gradient, and stratigraphic lithology were analysed. Moreover, it was found that the landslides were mainly concentrated in three stratigraphic combinations, that is T 1 f ~ P 2 l − d , T 1 f ~ T 1 y n , and T 2 g ~ T 1 y n . Thereafter, the correlation coefficients between the landslide density and elevation and distance to the stratigraphic boundary were 0.54 and −0.19, indicating that the distribution of landslides was significantly controlled by the elevation and the boundary of specific stratigraphic combinations. Finally, we chose a typical landslide to explore how landslide development was controlled by the combined effects of elevation and stratigraphy by using ascending and descending InSAR results. We revealed that landslides occurred primarily in areas with a steep slope and a stratigraphy characterized by mudstone and sandstone. [ABSTRACT FROM AUTHOR]

The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data points and challenges with topographical and structural variations. Our approach addresses these issues by analysing displacements from 30 images captured by the X-band SAR satellite, TerraSAR-X, over two years. We tested each InSAR parameter to develop an optimal set of parameters, applying the technique to a post-tensioned PSC (pre-stressed concrete) box bridge. Our findings revealed a recurring arch-shaped elevation along the bridge, attributed to temporal changes and long-term deformation. Further analysis showed a strong correlation between this deformation pattern and average surrounding temperature. This indicates that our technique can effectively identify micro-displacements due to temperature changes and structural deformation. Thus, the technique provides a theoretical foundation for improved SAR monitoring of large-scale social overhead capital (SOC) facilities, ensuring efficient maintenance and management.

The analysis of deformation dynamics in Guatemala city and its surrounding region presented in this paper holds significant relevance due to the high vulnerability of this area to natural disasters, combined with its rapid urbanization, similar to most Central American cities, contrasting with a lack of InSAR and deformation studies in the region. A total of 226 SAR images from Sentinel-1 A and B satellites in both ascending and descending geometries were processed with the Persistent Scatterer Interferometry (PSI) technique employing the SNAP-StaMPS integrated processing chain. The study area encompasses the Metropolitan Region of Guatemala, which is characterized by a diverse and active geological framework, with a historical record of earthquakes, intense groundwater extraction, and local subsidence phenomena, causing fissures and sinkholes. Four active areas were identified in the study area, each covering more than 50 hectares, with subsidence velocities greater than 10 mm/yr. This study provides valuable insights into fostering the sustainable development of this region by identifying deformation patterns, characterizing main active areas, and evaluating associated risks for disaster management and prevention. The results can also aid informed decision-making processes and guide urban planning and resource management strategies in other Central American countries. The application of InSAR studies is crucial for improving safety and sustainability in urban environments and natural resource management in vulnerable regions. [ABSTRACT FROM AUTHOR]

The investigation of reactivated landslides in the alpine-canyon areas suffers the difficult accessibility of precipitous terrain. In particular, when reactivated landslides occur along the major roads, efforts are focused on measuring ground surface displacements during road construction. Nevertheless, the ancient landslide deposits may reactivate after several years of road operation, while they show a stable state during the road construction. The characterization of this type of reactivated landslides is challenging, due to their complex mechanism and the limited monitoring data. Appropriate multi-source data can provide insights into deformation fields and enhance the understanding of landslide mechanisms, ensuring the outperformance of remedial works. This paper reports a recent Tangjiawan reactivated landslide along the Wenchuan-Maerkang Highway in Li County, China. The outcomes, including satellite InSAR, in situ real-time monitoring, and detailed ground and UAV investigation, conducted at this landslide are presented. Early deformation of the reactivated landslide began from 2019, with an InSAR-derived velocity of −11.7 mm/year, furthermore, a significant subsidence of about 21.2 mm, which occurred within a span of only 12 days from 3 June 2020 to 15 June 2020, was observed. The deformation characteristics derived from in situ monitoring during the remedial works were likely firstly associated with the initial unreinforced slope condition and the heavy rainfall. Subsequently, the displacement evolution transformed into deformation induced by time-dependent reduction in slope strength under rainfall conditions. The existing of unconsolidated deposits derived from ancient landslides, along with a fragile geo-structure consisting of rock blocks and gravels interlayered with breccias, exacerbated by large relief created a predisposition for landslide reactivation. Furthermore, 13 days of antecedent cumulative rainfall totaling 224.5 mm directly triggered the occurrence of a landslide event. The significance and implications of integrating multiple monitoring techniques are emphasized.

The standard Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique, which is commonly used for surface motion analysis, assumes linear deformation velocities. While effective for monitoring urban subsidence over short periods, it falls short when dealing with non-linear, earthquake-related deformations over extended timeframes. To address this limitation, we use a non-linear PSInSAR technique, which is an enhancement of PSInSAR, to identify non-linear deformation patterns. We processed Sentinel-1A images from ascending and descending orbits in the Islamabad/Rawalpindi region from December 2015 to January 2023 using non-linear PSInSAR. By calculating the differences in deformation, we analyzed surface movements and assessed the impact of the 2017 earthquake on urban areas. Our findings reveal that the earthquake significantly increased the deformation in ascending and descending orbit tracks, with an average deformation of up to 70 mm/yr and a line-of-sight movement of up to 30 mm/yr. Our observations indicate that the deformation is directed towards the line of sight in the north and south of the deformed area, suggesting subsidence between the two uplifting faults, potentially linked to a concealed fault line along the deformation zone boundary. This contradicts previous arguments, suggesting that water extraction is the leading cause of deformation. Our analysis with non-linear PSInSAR demonstrates that tectonics play a significant role in deformation, providing valuable insights into tectonic-activity-induced deformations in urban areas over the long term.

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas.

The deformation characteristics and instability patterns of rotational landslides are complicated. Such landslides are large and occur continuously, seriously threatening people's lives. We used interferometry synthetic aperture radar (InSAR), digital elevation models of difference (DODs), numerical simulations, and other techniques for analyzing the topographic changes, surface deformation and movement process before, during and after a landslide. Based on the high-resolution terrain data before and after the landslide, the topographic changes were analyzed, and the active zone of the landslide was identified. The areas of the topographic changes were mainly located on the main scarp, toe and secondary landslides. The topographic changes were influenced by rainfall and rill erosion. The geomorphologically-guided InSAR interpretation method was applied to explore the displacement pattern. The deformation area in the middle of the landslide coincided with the secondary landslides. A time-series InSAR analysis revealed the dynamic evolution of the deformation before and after the landslide. Based on its evolution, the simulated landslide process included the main landslide and three secondary landslides. Based on the displacement of the longitudinal ground surface profiles, the displacement characteristics and kinematic behavior were summarized and compared with those of a single rotational landslide and multiple rotational landslides. The single rotational landslide had obvious secondary and progressive characteristics, developing into multiple rotational landslides triggered by conditions such as rainfall. [ABSTRACT FROM AUTHOR]

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021. [ABSTRACT FROM AUTHOR]

Catastrophic landslides occur frequently in Guizhou Province, China, and the landslides in this area have special geomorphological, geological, and anthropogenic features. In order to detect and explore the distribution pattern and control factors of active landslides in Guizhou, firstly, a total of 693 active landslides throughout Guizhou Province were mapped based on the deformation rate, which was obtained by spatiotemporal filtering and Intermittent Small Baseline Subset (ISBAS) Interferometric Synthetic Aperture Radar (InSAR) techniques. Then, the relationships between the detected landslides and elevation, aspect, slope gradient, and stratigraphic lithology were analysed. Moreover, it was found that the landslides were mainly concentrated in three stratigraphic combinations, that is T1f~P2l−d, T1f~T1yn, and T2g~T1yn. Thereafter, the correlation coefficients between the landslide density and elevation and distance to the stratigraphic boundary were 0.54 and −0.19, indicating that the distribution of landslides was significantly controlled by the elevation and the boundary of specific stratigraphic combinations. Finally, we chose a typical landslide to explore how landslide development was controlled by the combined effects of elevation and stratigraphy by using ascending and descending InSAR results. We revealed that landslides occurred primarily in areas with a steep slope and a stratigraphy characterized by mudstone and sandstone.

Despite the profound roles of surface deformation monitoring techniques in observing permafrost surface stability, predetermining the approximate location and time of possibly occurring severe permafrost degradation before applying these techniques is extremely necessary, but has received little attention. Taking the oil tank collapse accident in the Norilsk region as a case, we explored this concern by analyzing the permafrost deformation mechanisms and determining early surface deformation signals. Regarding this case, we firstly applied the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to obtain its permafrost surface deformation rate, then utilized a sine model to decompose its interannual deformation and seasonal deformation, and finally compared the relationship between the topographic slope and deformation rate. Based on experimental results, we reveal that when the annual average temperature continuously increases at a rate of 2 ° C/year for 2∼3 consecutive years, permafrost areas with relatively large topographic slopes (>15 ° ) are more prone to severe surface deformation during the summer thaw period. Therefore, this paper suggests that permafrost areas with large topographic slopes (>15 ° ) should be taken as the key surveillance areas, and that the appropriate monitoring time for employing surface deformation monitoring techniques should be the summer thawing period after a continuous increase in annual average temperature at a rate of 2 ° C/year for 2∼3 years. [ABSTRACT FROM AUTHOR]

The analysis of deformation dynamics in Guatemala city and its surrounding region presented in this paper holds significant relevance due to the high vulnerability of this area to natural disasters, combined with its rapid urbanization, similar to most Central American cities, contrasting with a lack of InSAR and deformation studies in the region. A total of 226 SAR images from Sentinel-1 A and B satellites in both ascending and descending geometries were processed with the Persistent Scatterer Interferometry (PSI) technique employing the SNAP-StaMPS integrated processing chain. The study area encompasses the Metropolitan Region of Guatemala, which is characterized by a diverse and active geological framework, with a historical record of earthquakes, intense groundwater extraction, and local subsidence phenomena, causing fissures and sinkholes. Four active areas were identified in the study area, each covering more than 50 hectares, with subsidence velocities greater than 10 mm/yr. This study provides valuable insights into fostering the sustainable development of this region by identifying deformation patterns, characterizing main active areas, and evaluating associated risks for disaster management and prevention. The results can also aid informed decision-making processes and guide urban planning and resource management strategies in other Central American countries. The application of InSAR studies is crucial for improving safety and sustainability in urban environments and natural resource management in vulnerable regions.

The deformation characteristics and instability patterns of rotational landslides are complicated. Such landslides are large and occur continuously, seriously threatening people’s lives. We used interferometry synthetic aperture radar (InSAR), digital elevation models of difference (DODs), numerical simulations, and other techniques for analyzing the topographic changes, surface deformation and movement process before, during and after a landslide. Based on the high-resolution terrain data before and after the landslide, the topographic changes were analyzed, and the active zone of the landslide was identified. The areas of the topographic changes were mainly located on the main scarp, toe and secondary landslides. The topographic changes were influenced by rainfall and rill erosion. The geomorphologically-guided InSAR interpretation method was applied to explore the displacement pattern. The deformation area in the middle of the landslide coincided with the secondary landslides. A time-series InSAR analysis revealed the dynamic evolution of the deformation before and after the landslide. Based on its evolution, the simulated landslide process included the main landslide and three secondary landslides. Based on the displacement of the longitudinal ground surface profiles, the displacement characteristics and kinematic behavior were summarized and compared with those of a single rotational landslide and multiple rotational landslides. The single rotational landslide had obvious secondary and progressive characteristics, developing into multiple rotational landslides triggered by conditions such as rainfall.

The ancient Aniangzhai (ANZ) landslide in Danba County, Sichuan Province of southwest China was reactivated after a series of complex hazard events that occurred in June 2020. Since then, and until June 2021, emergency engineering work was carried out to prevent the further failure of the reactivated landslide. This study investigates the potential of joint use of time series Interferometric Synthetic Aperture Radar (InSAR) and optical pixel offset tracking (POT) to assess deformation characteristic and spatial-temporal evolution of the reactivated ANZ landslide during the post-failure stage. The relationships between sun illumination differences, temporal baseline of correlation pairs and the uncertainties were deeply explored. Surface deformation along the line-of-sight (LoS) direction was retrieved by the time series InSAR processing with the two Sentinel-1 datasets, revealing a maximum deformation rate up to 190 mm/year. The large horizontal displacements were also detected from the POT processing using 11 optical images acquired by the PlanetScope satellite (3 m spatial resolution), showing a significant increase of about 24 m between 24 June 2020 and 11 June 2021. The time series analysis from the InSAR and optical POT results revealed that the reactivated ANZ landslide body is gradually slowing down to a steady deformation status since its occurrence in August 2020, indicating the effectiveness of engineering work on the prevention of further landslide. A slight acceleration was detected from both InSAR and optical POT time series analysis between May 2021 and June 2021, which could be caused by the increased rainfall in May 2021.

Despite the profound roles of surface deformation monitoring techniques in observing permafrost surface stability, predetermining the approximate location and time of possibly occurring severe permafrost degradation before applying these techniques is extremely necessary, but has received little attention. Taking the oil tank collapse accident in the Norilsk region as a case, we explored this concern by analyzing the permafrost deformation mechanisms and determining early surface deformation signals. Regarding this case, we firstly applied the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to obtain its permafrost surface deformation rate, then utilized a sine model to decompose its interannual deformation and seasonal deformation, and finally compared the relationship between the topographic slope and deformation rate. Based on experimental results, we reveal that when the annual average temperature continuously increases at a rate of 2 °C/year for 2∼3 consecutive years, permafrost areas with relatively large topographic slopes (>15°) are more prone to severe surface deformation during the summer thaw period. Therefore, this paper suggests that permafrost areas with large topographic slopes (>15°) should be taken as the key surveillance areas, and that the appropriate monitoring time for employing surface deformation monitoring techniques should be the summer thawing period after a continuous increase in annual average temperature at a rate of 2 °C/year for 2∼3 years.

The North China Craton (NCC) has experienced strong tectonic deformation and lithospheric thinning since the Cenozoic. To better constrain the geodynamic processes and mechanisms of the lithospheric deformation, we used a linear damped least squares method to invert simultaneously Rayleigh wave phase velocity and azimuthal anisotropy at periods of 10–80 s with teleseismic data recorded by 388 permanent stations in the NCC and its adjacent areas. The results reveal that the anomalies of Rayleigh wave phase velocity and azimuthal anisotropy are in good agreement with the tectonic domains in the study area. Low-phase velocities appear in the rift grabens and sedimentary basins at short periods. A rotation pattern of the fast axis direction of the Rayleigh wave together with a distinct low-velocity anomaly occurs around the Datong volcano. A NW–SE trending azimuthal anisotropy and a low-velocity anomaly at periods of 60–80 s are observed subparallel to the Zhangbo fault zone. The whole lithosphere domain of the Ordos block shows a high-phase velocity and counterclockwise rotated fast axis. The northeastern margin of the Tibetan plateau is dominated by a low-velocity and coherent NW–SE fast axis direction. We infer that the subduction of the Paleo-Pacific plate and eastward material escape of the Tibetan plateau mainly contribute to the deformation of the crust and upper mantle in the NCC.

Arctic amplification is accelerating changes in sea ice regimes in the Canadian Arctic with later freeze-up and earlier melt events, adversely affecting Arctic wildlife and communities that depend on the stability of sea ice conditions. To monitor both the rate and impact of such change, there is a need to accurately measure sea ice deformation, an important component for understanding ice motion and polar climate. The objective of this study is to determine the spatial-temporal pattern of deformation over landfast ice in the Arctic using time series SAR imagery. We present Interferometric Synthetic Aperture Radar (InSAR) monitoring of Arctic landfast sea ice deformation using C-band Radarsat-2, Sentinel-1 and L-band ALOS-2 in this paper. The small baseline subset (SBAS) approach was explored to process time series observations for retrieval of temporal deformation changes along a line-of-sight direction (LOS) over the winter. It was found that temporal and spatial patterns of deformation observed from different sensors were generally consistent. Horizontal and vertical deformations were also retrieved by a multi-dimensional SBAS technique using both ascending and descending Sentinel-1 observations. Results showed a horizontal deformation in the range of −95–85 cm, and vertical deformation in the range of −41–63 cm in Cambridge Bay, Nunavut, Canada during February-April 2019. High coherence over ice from C-band was maintained over a shorter time interval of acquisitions than L-band due to temporal decorrelation.

The Coherent Pixels Technique Interferometry Synthetic Aperture Radar (CPT-InSAR) method of inverting surface deformation parameters by using high-quality measuring points possesses the flaw inducing sparse measuring points in non-urban areas. In this paper, we propose the Adaptive Coherent Distributed Pixel InSAR (ACDP-InSAR) method, which is an adaptive method used to extract Distributed Scattering Pixel (DSP) based on statistically homogeneous pixel (SHP) cluster tests and improves the phase quality of DSP through phase optimization, which cooperates with Coherent Pixel (CP) for the retrieval of ground surface deformation parameters. For a region with sparse CPs, DSPs and its SHPs are detected by double-layer windows in two steps, i.e., multilook windows and spatial filtering windows, respectively. After counting the pixel number of maximum SHP cluster (MSHPC) in the multilook window based on the Anderson–Darling (AD) test and filtering out unsuitable pixels, the candidate DSPs are selected. For the filtering window, the SHPs of MSHPC’ pixels within the new window, which is different compared with multilook windows, were detected, and the SHPs of DSPs were obtained, which were used for coherent estimation. In phase-linking, the results of Eigen decomposition-based Maximum likelihood estimator of Interferometric phase (EMI) results are used as the initial values of the phase triangle algorithm (PTA) for the purpose of phase estimation (hereafter called as PTA-EMI). The DSPs and estimated phase are then combined with CPs in order to retrievesurface deformation parameters. The method was validated by two cases. The results show that the density of measuring points increased approximately 6–10 times compared with CPT-InSAR, and the quality of the interferometric phase significantly improved after phase optimization. It was demonstrated that the method is effective in increasing measuring point density and improving phase quality, which increases significantly the detectability of the low coherence region. Compared with the Distributed Scatterer InSAR (DS-InSAR) technique, ACDP-InSAR possesses faster processing speed at the cost of resolution loss, which is crucial for Earth surface movement monitoring at large spatial scales.

Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine mountain environments. Rock glacier activity represents a critical indicator of water reserves state, permafrost distribution, and landslide disaster susceptibility. The dynamics of rock glacier activity in alpine periglacial environments are poorly quantified, especially in the central Himalayas. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been shown to be a useful technique for rock glacier deformation detection. In this study, we developed a multi-baseline persistent scatterer (PS) and distributed scatterer (DS) combined MT-InSAR method to monitor the activity of rock glaciers in the central Himalayas. In periglacial landforms, the application of the PS interferometry (PSI) method is restricted by insufficient PS due to large temporal baseline intervals and temporal decorrelation, which hinder comprehensive measurements of rock glaciers. Thus, we first evaluated the rock glacier interferometric coherence of all possible interferometric combinations and determined a multi-baseline network based on rock glacier coherence; then, we constructed a Delaunay triangulation network (DTN) by exploiting both PS and DS points. To improve the robustness of deformation parameters estimation in the DTN, we combined the Nelder–Mead algorithm with the M-estimator method to estimate the deformation rate variation at the arcs of the DTN and introduced a ridge-estimator-based weighted least square (WLR) method for the inversion of the deformation rate from the deformation rate variation. We applied our method to Sentinel-1A ascending and descending geometry data (May 2018 to January 2019) and obtained measurements of rock glacier deformation for 4327 rock glaciers over the central Himalayas, at least more than 15% detecting with single geometry data. The line-of-sight (LOS) deformation of rock glaciers in the central Himalayas ranged from −150 mm to 150 mm. We classified the active deformation area (ADA) of all individual rock glaciers with the threshold determined by the standard deviation of the deformation map. The results show that 49% of the detected rock glaciers (monitoring rate greater than 30%) are highly active, with an ADA ratio greater than 10%. After projecting the LOS deformation to the steep slope direction and classifying the rock glacier activity following the IPA Action Group guideline, 12% of the identified rock glaciers were classified as active and 86% were classified as transitional. This research is the first multi-baseline, PS, and DS network-based MT-InSAR method applied to detecting large-scale rock glaciers activity.

This paper reports on the activities carried out in the context of “Dragon project 32278: Three- and Four-Dimensional Topographic Measurement and Validation”. The research work was split into three subprojects and encompassed several activities to deliver accurate characterization of targets on land surfaces and deepen the current knowledge on the exploitation of Synthetic Aperture Radar (SAR) data. The goal of Subproject 1 was to validate topographic mapping accuracy of various ESA, TPM, and Chinese satellite system on test sites in the EU and China; define and improve validation methodologies for topographic mapping; and develop and setup test sites for the validation of different surface motion estimation techniques. Subproject 2 focused on the specific case of spatially and temporally decorrelating targets by using multi-baseline interferometric (InSAR) and tomographic (TomoSAR) SAR processing. Research on InSAR led to the development of robust retrieval techniques to estimate target displacement over time. Research on TomoSAR was focused on testing or defining new processing methods for high-resolution 3D imaging of the interior of forests and glaciers and the characterization of their temporal behavior. Subproject 3 was focused on near-real-time motion estimation, considering efficient algorithms for the digestion of new acquisitions and for changes in problem parameterization.

The goafs caused by coal mining cause great harm to the surface farmland, buildings, and personal safety. The existing monitoring methods cost a lot of workforce and material resources. Therefore, this paper proposes an inversion approach for establishing the locations of underground goafs and the parameters of the probability integral method (PIM), thus integrating distributed scatter interferometric synthetic aperture radar (DS-InSAR) data and the PIM. Firstly, a large amount of surface deformation observation data above the goaf are obtained by DS-InSAR, and the line-of-sight deformation is regarded as the true value. Secondly, according to the obtained surface deformations, the ranges of eight goaf location parameters and three PIM parameters are set. Thirdly, a correlation function between the surface deformation and the underground goaf location is constructed. Finally, a particle swarm optimization algorithm is used to search for the optimal parameters in the range of the set parameters to meet the requirement for minimum error between the surface deformation calculated by PIM and the line-of-sight deformation obtained by DS-InSAR. These optimal parameters are thus regarded as the real values of the position of the underground goaf and the PIM parameters. The simulation results show that the maximum relative error between the position of the goaf and the PIM parameters is 2.11%. Taking the 93,604 working face of the Zhangshuanglou coal mine in the Peibei mining area as the research object and 12 Sentinel-1A images as the data source, the goaf location and PIM parameters of the working face were successfully inverted. The inversion results show that the maximum relative error in the goaf location parameters was 16.61%, and the maximum relative error in the PIM parameters was 26.67%.

Lombok Island in Indonesia was hit by four major earthquakes (6.4 Mw to 7 Mw) and by at least 818 earthquakes between 29 July and 31 August 2018. The aims of this study are to measure ground deformation due to the 2018 Lombok earthquake series and to map its spatio-temporal distribution. The application of DinSAR was performed to produce an interferogram and deformation map. Time series Sentinel-1 satellite imageries were used as master and slave for each of these four major earthquakes. The spatio-temporal distribution of the ground deformation was analyzed using a zonal statistics algorithm in GIS. It focused on the overlapping area between the raster layer of the deformation map and the polygon layer of six observation sites (Mataram City, Pamenang, Tampes, Sukadana, Sembalun, and Belanting). The results showed that the deformation includes uplift and subsidence. The first 6.4 Mw foreshock hitting on 29 July 2018 produces a minimum uplift effect on the island. The 7.0 Mw mainshock on 5 August 2018 causes extreme uplift at the northern shore. The 6.2 Mw Aftershock on 9 August 2018 generates subsidence throughout the study area. The final earthquake of 6.9 Mw on 19 August 2018 initiates massive uplift in the study area and extreme uplift at the northeastern shore. The highest uplift reaches 0.713 m at the northern shore, while the deepest subsidence is measured −0.338 m at the northwestern shore. Dominant deformation on the northern area of Lombok Island indicates movement of Back Arc Trust in the north of the island. The output of this study would be valuable to local authorities to evaluate existing earthquake’s impacts and to design mitigation strategies to face earthquake-induced ground displacement.

Image registration is among the most popular and important problems of remote sensing. In this paper we propose a fully unsupervised, deep learning based multistep deformable registration scheme for aligning pairs of satellite imagery. The presented method is based on the expression power of deep fully convolutional networks, regressing directly the spatial gradients of the deformation and employing a 2D transformer layer to efficiently warp one image to the other, in an end-to-end fashion. The displacements are calculated with an iterative way, utilizing different time steps to refine and regress them. Our formulation can be integrated into any kind of fully convolutional architecture, providing at the same time fast inference performances. The developed methodology has been evaluated in two different datasets depicting urban and periurban areas; i.e., the very high-resolution dataset of the East Prefecture of Attica, Greece, as well as the high resolution ISPRS Ikonos dataset. Quantitative and qualitative results demonstrated the high potentials of our method.

Persistent scatterer interferometry (PSI) is a group of advanced interferometric synthetic aperture radar (SAR) techniques used to measure and monitor terrain deformation. Sentinel-1 has improved the data acquisition throughout and, compared to previous sensors, increased considerably the differential interferometric SAR (DInSAR) and PSI deformation monitoring potential. The low density of persistent scatterer (PS) in non-urban areas is a critical issue in DInSAR and has inspired the development of alternative approaches and refinement of the PS chains. This paper proposes two different and complementary data-driven procedures to obtain terrain deformation maps. These approaches aim to exploit Sentinel-1 highly coherent interferograms and their short revisit time. The first approach, called direct integration (DI), aims at providing a very fast and straightforward approach to screen-wide areas and easily detects active areas. This approach fully exploits the coherent interferograms from consecutive images provided by Sentinel-1, resulting in a very high sampling density. However, it lacks robustness and its usability lays on the operator experience. The second method, called persistent scatterer interferometry geomatics (PSIG) short temporal baseline, provides a constrained application of the PSIG chain, the CTTC approach to the PSI. It uses short temporal baseline interferograms and does not assume any deformation model for point selection. It is also quite a straightforward approach, which improves the performances of the standard PSIG approach, increasing the PS density and providing robust measurements. The effectiveness of the approaches is illustrated through analyses performed on different test sites.

In light of recent Arctic change, there is a need to better understand sea ice dynamic processes at the floe scale to evaluate sea ice stability, deformation, and fracturing. This work investigates the use of the Gamma portable radar interferometer (GPRI) to characterize sea ice displacement and surface topography. We find that the GPRI is best suited to derive lateral surface deformation due to mm-scale horizontal accuracy. We model interferometric phase signatures from sea ice displacement and evaluate possible errors related to noise and antenna motion. We compare the analysis with observations acquired during a drifting ice camp in the Beaufort Sea. We used repeat-scan and stare-mode interferometry to identify two-dimensional shear and to track continuous uni-directional convergence. This paper demonstrates the capacity of the GPRI to derive surface strain on the order of 10−7 and identify different dynamic regions based on sub-mm changes in displacement. The GPRI is thus a promising tool for sea ice applications due to its high accuracy that can potentially resolve pre- and post-fracture deformation relevant to sea ice stability and modeling.

Among different sets of constraints and hazards that have to be considered in the management of cities and land use, land surface subsidence is one of the important issues that can lead to many problems, and its economic consequences cannot be ignored. In this study, the ground surface deformation of Gävle city in Sweden is investigated using the Persistent Scatterer Interferometry (PSI) technique as well as analyzing the historical leveling data. The PSI technique is used to map the location of hazard zones and their ongoing subsidence rate. Two ascending and descending Sentinel-1 datasets, collected between January 2015 and May 2020, covering the Gävle city, were processed and analyzed. In addition, a long record of a leveling dataset, covering the period from 1974 to 2019, was used to detect the rate of subsidence in some locations which were not reported before. Our PSI analysis reveals that the center of Gävle is relatively stable with minor deformation ranged between −2 ± 0.5 mm/yr to +2 ± 0.5 mm/yr in vertical and east–west components. However, the land surface toward the northeast of the city is relatively subsiding with a higher annual rate of up to −6 ± 0.46 mm/yr. The comparison at sparse locations shows a close agreement between the subsidence rates obtained from precise leveling and PSI results. The regional quaternary deposits map was overlaid with PSI results and it shows the subsidence areas are mostly located in zones where the subsurface layer is marked by artificial fill materials. The knowledge of the spatio-temporal extents of land surface subsidence for undergoing urban areas can help to develop and establish models to mitigate hazards associated with such land settlement.

We studied the broader area of Thessaloniki in northern Greece and Chalkidiki and performed an InSAR campaign to study the surface deformation phenomena that have been known to exist for at least two decades. Sentinel-1 data (2015–2019) together with drill measurements were exploited to focus on specific sites of interest. Our results indicate an ongoing displacement field. At the region of Kalochori and Sindos—where intense subsidence in the 1990s was previously found to have had a natural surface rebound in the 2000s—a new period of subsidence, caused by the enlivenment of the groundwater overexploitation, was reported. The uplifting trend of Oreokastro is still active and subsidence in Anthemountas graben is ongoing; special focus was set on the Makedonia Airport, where significant displacement is occurring. The study also reveals a new area at Nea Moudania, that was not known previously to deform; another case corresponding to anthropogenic-induced surface displacement. Thessaloniki is surrounded by different persistent displacement phenomena, whose main driving mechanisms are anthropogenic. The sensitivity of the surface displacements to the water trends is highlighted in parts of the study area. Results highlight the plan of a water resources management as a high priority for the area.

The choice of an appropriate metric is mandatory to perform deformation analysis between two point clouds (PC)—the distance has to be trustworthy and, simultaneously, robust against measurement noise, which may be correlated and heteroscedastic. The Hausdorff distance (HD) or its averaged derivation (AHD) are widely used to compute local distances between two PC and are implemented in nearly all commercial software. Unfortunately, they are affected by measurement noise, particularly when correlations are present. In this contribution, we focus on terrestrial laser scanner (TLS) observations and assess the impact of neglecting correlations on the distance computation when a mathematical approximation is performed. The results of the simulations are extended to real observations from a bridge under load. Highly accurate laser tracker (LT) measurements were available for this experiment: they allow the comparison of the HD and AHD between two raw PC or between their mathematical approximations regarding reference values. Based on these results, we determine which distance is better suited in the case of heteroscedastic and correlated TLS observations for local deformation analysis. Finally, we set up a novel bootstrap testing procedure for this distance when the PC are approximated with B-spline surfaces.

The Pusa landslide, in Guizhou, China, occurred on 28 August 2017, caused 26 deaths with 9 missing. However, few studies about the pre-event surface deformation are provided because of the complex landslide formation and failure mechanism. To retrieve the precursory signal of this landslide, we recovered pre-event deformation with multi-sensor synthetic aperture radar (SAR) imagery. First, we delineated the boundary and source area of the Pusa landslide based on the coherence and SAR intensity maps. Second, we detected the line-of-sight (LOS) deformation rate and time series before the Pusa landslide with ALOS/PALSAR-2 and Sentinel-1A/B SAR imagery data, where we found that the onset of the deformation is four months before landslide event. Finally, we conceptualized the failure mechanism of the Pusa landslide as the joint effects of rainfall and mining activity. This research provides new insights into the failure mechanism and early warning of rock avalanches.

This paper deals with the integration of deformation rates derived from Synthetic Aperture Radar Interferometry (InSAR) and Global Navigation Satellite System (GNSS) data. The proposed approach relies on knowledge of the variance/covariance of both InSAR and GNSS measurements so that they may be combined accounting for the spectral properties of their errors, hence preserving all spatial frequencies of the deformation detected by the two techniques. The variance/covariance description of the output product is also provided. A performance analysis is carried out on realistic simulated scenarios in order to show the boundaries of the technique. The proposed approach is finally applied to real data. Five Sentinel-1A/B stacks acquired over two different areas of interest are processed and discussed. The first example is a merged deformation map of the northern part of the Netherlands for both ascending and descending geometries. The second example shows the deformation at the junction between the North and East Anatolian Fault using three consecutive descending stacks.

We studied two issues to be considered in the calculation of parameters characterizing sea ice deformation: the effect of uncertainties in an automatically retrieved sea ice drift field, and the influence of the type of drift vector grid. Sea ice deformation changes the local ice mass balance and the interaction between atmosphere, ice, and ocean, and constitutes a hazard to marine traffic and operations. Due to numerical effects, the results of deformation retrievals may predict, e.g., openings and closings of the ice cover that do not exist in reality. We focus specifically on fields of ice drift obtained from synthetic aperture radar (SAR) imagery and analyze the Propagated Drift Retrieval Error (PDRE) and the Boundary Definition Error (BDE). From the theory of error propagation, the PDRE for the calculated deformation parameters can be estimated. To quantify the BDE, we devise five different grid types and compare theoretical expectation and numerical results for different deformation parameters assuming three scenarios: pure divergence, pure shear, and a mixture of both. Our findings for both sources of error help to set up optimal deformation retrieval schemes and are also useful for other applications working with vector fields and scalar parameters derived therefrom. [ABSTRACT FROM AUTHOR]

Triggered by earthquakes, rainfall, or anthropogenic activities, landslides represent widespread and problematic geohazards worldwide. In recent years, multiple remote sensing techniques, including synthetic aperture radar, optical, and light detection and ranging measurements from spaceborne, airborne, and ground-based platforms, have been widely applied for the analysis of landslide processes. Current techniques include landslide detection, inventory mapping, surface deformation monitoring, trigger factor analysis and mechanism inversion. In addition, landslide susceptibility modelling, hazard assessment, and risk evaluation can be further analyzed using a synergic fusion of multiple remote sensing data and other factors affecting landslides. We summarize the 19 articles collected in this special issue of Remote Sensing of Landslide, in the terms of data, methods and applications used in the papers. [ABSTRACT FROM AUTHOR]

Landslide is the second most frequent geological disaster after earthquake, which causes a large number of casualties and economic losses every year. China frequently experiences devastating landslides in mountainous areas. Interferometric Synthetic Aperture Radar (InSAR) technology has great potential for detecting potentially unstable landslides across wide areas and can monitor surface displacement of a single landslide. However traditional time series InSAR technology such as persistent scatterer interferometry (PSI) and small-baseline subset (SBAS) cannot identify enough points in mountainous areas because of dense vegetation and steep terrain. In order to improve the accuracy of landslide hazard detection and the reliability of landslide deformation monitoring in areas lacking high coherence stability point targets, this study proposes an adaptive distributed scatterer interferometric synthetic aperture radar (ADS-InSAR) method based on the spatiotemporal coherence of the distributed scatterer (DS), which automatically adjusts its detection threshold to improve the spatial distribution density and reliability of DS detection in the landslide area. After time series network modeling and deformation calculation of the ADS target, the displacement deformation of the landslide area can be accurately extracted. Shuibuya Town in Enshi Prefecture, Hubei Province, China, was used as a case study, along with 18 Sentinal-1A images acquired from March 2016 to April 2017. The ADS-InSAR method was used to obtain regional deformation data. The deformation time series was combined with hydrometeorological and related data to analyze landslide deformation. The results show that the ADS-InSAR method can effectively improve the density of DS distribution, successfully detect existing ancient landslide groups and determine multiple potential landslide areas, enabling early warning for landslide hazards. This study verifies the reliability and accuracy of ADS-InSAR for landslide disaster prevention and mitigation.

Fluid extraction or injection into underground reservoirs may cause ground deformation, manifested as subsidence or uplift. Excessive deformation may threaten the infrastructure of the oilfield and its surroundings and may even induce earthquakes. Therefore, the monitoring of surface deformation caused by oil production activities is important for the safe production of oilfields and safety assessments of surrounding infrastructure. Karamay oilfield is one of the major oil and gas fields in China. In this study, we take the Karamay oilfield in Xinjiang as a case study to detect surface deformation caused by subsurface fluid injection. Sentinel-1A images of 32 ascending (Path 114) and 34 descending (Path 165) tracks spanning March 2017 to August 2018, were used to derive vertical and horizontal deformation over Karamay oilfield using the MSBAS-InSAR method. The observed two-dimensional deformation exhibited significant vertical and east-west deformation in this region. The maximum uplift and horizontal velocity was approximately 160 mm/year and 65 mm/year, respectively. We also modeled one of the typical deformation zones using a dislocation model in a homogenous elastic half-space.

The paper aims to detect the main changes that occurred in the area surrounding the Mario Zucchelli Station (MZS) through analysis of multi-temporal remote sensing integrated by geophysical measurements. Specific attention was directed at realizing an integrated geomorphological study of the Boulder Clay Glacier, a partially debris-covered glacier belonging to the Northern Foothills (Victoria Land, Antarctica). This area was recently chosen as the location for the construction of a new semi-permanent gravel runway for MZS logistical airfreight operations. Photogrammetric analysis was performed by comparing three historical aerial photogrammetric surveys (carried out in 1956, 1985, and 1993) and Very High Resolution (VHR) GeoEye-1 satellite stereo-image coverage acquired in 2012. The comparison of geo-referenced orthophoto-mosaics allowed the main changes occurring in some particular areas along the coast nearby MZS to be established. Concerning the study of the Boulder Clay Glacier, it has to be considered that glaciers and moraines are not steady-state systems by definition. Several remote sensing and geophysical investigations were carried out with the main aim of determining the general assessment of this glacier: Ground Penetrating Radar (GPR); Geodetic Global Positioning System (GPS) network; multi-temporal satellite Synthetic Aperture Radar (SAR) interferometry. The analysis of Boulder Clay Glacier moraine pointed out a deformation of less than 74 mm y−1 in a time span of 56 years, value that agrees with velocity and deformation data observed by GPS and InSAR methods. The presence of unexpected brine ponds at the ice/bedrock interface and the deformation pattern observed in the central part of the moraine has to be monitored and studied, especially under the long-term maintenance of the future runway.

This Special Issue hosts papers related to deformation monitoring in urban areas based on two main techniques: Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions highlight the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. In this Special Issue, a wide range of InSAR and PSI applications are addressed. Some contributions show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This issue includes a contribution that compares PSI and TomoSAR and another one that uses polarimetric data for TomoSAR.

Monitoring surface movement near highways over soft clay subgrades is fundamental for understanding the dynamics of the settlement process and preventing hazards. Earlier studies have demonstrated the accuracy and cost-effectiveness of using time series radar interferometry (InSAR) technique to measure the ground deformation. However, the accuracy of the advanced differential InSAR techniques, including short baseline subset (SBAS) InSAR, is limited by the temporal deformation models used. In this study, a comparison of four widely used time series deformation models in InSAR, namely Multi Velocity Model (MVM), Permanent Velocity Model (PVM), Seasonal Model (SM) and Cubic Polynomial Model (CPM), was conducted to measure the long-term ground deformation after the construction of road embankment over soft clay subgrade. SBAS-InSAR technique with TerraSAR-X satellite imagery were conducted to generate the time series deformation data over the studied highway. In the experiments, three accuracy indices were applied to show the residual phase, mean temporal coherence and the RMS of high-pass deformation, respectively. In addition, the derived time series deformation maps of the highway based on the four selected models and 17 TerraSAR-X images acquired from June 2014 to November 2015 were compared. The leveling data was also used to validate the experimental results. Our results suggested the Seasonal Model is the most suitable model for the selected study site. Consequently, we analyzed two bridges in detail and three single points distributed near the highway. Compared with the ground leveling deformation measurements and results of other models, SM showed better consistency, with the accuracy of deformation to be ±7 mm.

In this work, the statistical fundaments of the recently proposed enhanced, multi-temporal interferometric synthetic aperture radar (InSAR) noise-filtering (E-MTInSAR) technique is addressed. The adopted noise-filtering algorithm is incorporated into the improved extended Minimum Cost Flow (EMCF) Small Baseline Subset (SBAS) differential interferometric SAR (InSAR) processing chain, which has extensively been used for the generation of Earth’s surface displacement time-series in several different contexts. Originally, the input of the InSAR EMCF-SBAS processing toolbox consisted of a sequence of multi-looked, small baseline interferograms, which were unwrapped using the space-time EMCF phase unwrapping algorithm. Subsequently, the unwrapped interferograms were inverted through the SBAS algorithm to retrieve the expected InSAR deformation products. The improved processing chain has complemented the original codes with two additional steps. In particular, a new multi-temporal noise-filtering algorithm for sequences of time-redundant multi-looked DInSAR interferograms, followed by a proper interferogram selection step, has been proposed. This research study is aimed at primarily assessing the performance of the E-MTInSAR noise-filtering algorithm from a theoretical perspective. To this aim, the principles of directional statistics and errors propagation are exploited. Experimental results, carried out by applying the E-MTInSAR algorithm to a sequence of SAR data collected over the Los Angeles bay area, have been used to corroborate the academic outcome of this research.

In this work, ground deformation of the Shanghai coastal area is inferred by using the multiple-satellite Differential Synthetic Aperture Radar interferometry (DInSAR) approach, also known as the minimum acceleration (MinA) combination algorithm. The MinA technique allows discrimination and time-evolution monitoring of the inherent two-dimensional components (i.e., with respect to east-west and up-down directions) of the ongoing deformation processes. It represents an effective post-processing tool that allows an easy combination of preliminarily-retrieved multiple-satellite Line-Of-Sight-projected displacement time-series, obtained by using one (or more) of the currently available multi-pass DInSAR toolboxes. Specifically, in our work, the well-known small baseline subset (SBAS) algorithm has been exploited to recover LOS deformation time-series from two sets of Synthetic Aperture Radar (SAR) data relevant to the coast of Shanghai, collected from 2014 to 2017 by the COSMO-SkyMed (CSK) and the Sentinel-1A (S1-A) sensors. The achieved results evidence that the Shanghai ocean-reclaimed areas were still subject to residual deformations in 2016, with maximum subsidence rates of about 30 mm/year. Moreover, the investigation has revealed that the detected deformations are predominantly vertical, whereas the east-west deformations are less significant. [ABSTRACT FROM AUTHOR]

On the afternoon of 28 June 2010, an enormous landslide occurred in the Gangwu region of Guanling County, Guizhou Province. In order to better understand the mechanism of the Guanling landslide, archived ALOS/PALSAR data was used to acquire the deformation prior to the landslide occurrence through stacking and time-series InSAR techniques. First, the deformation structure from InSAR was compared to the potential creep bodies identified using the optical remote sensing data. A strong consistency between the InSAR detected deformed regions and the creep bodies detected from optical remote sensing images was achieved. Around 10 creep bodies were suffering from deformation. In the source area, the maximum pre-slide mean deformation rate along the slope direction reached 160 mm/year, and the uncertainty of the deformation rates ranged from 15 to 34 mm/year. Then, the pre-slide deformation at the source area was analyzed in terms of the topography, geological structure, and historical rainfall records. Through observation and analysis, the deformation pattern of one creep body located within the source area can be segmented into three sections: a creeping section in the front, a locking section in the middle, and a cracking section in the rear. These sections constitute one of the common landslide modes seen in the south-west of China. This study concluded that a sudden shear failure in the locking segment of one creeping body located within the source area was caused by a strong rainstorm, which triggered the Guanling landslide. [ABSTRACT FROM AUTHOR]

This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed. [ABSTRACT FROM AUTHOR]

Earth Observations (EO) encompasses different types of sensors (e.g., Synthetic Aperture Radar, Laser Imaging Detection and Ranging, Optical and multispectral) and platforms (e.g., satellites, aircraft, and Unmanned Aerial Vehicles) and enables us to monitor and model geohazards over regions at different scales in which ground observations may not be possible due to physical and/or political constraints. EO can provide high spatial, temporal and spectral resolution, stereo-mapping and all-weather-imaging capabilities, but not by a single satellite at a time. Improved satellite and sensor technologies, increased frequency of satellite measurements, and easier access and interpretation of EO data have all contributed to the increased demand for satellite EO data. EO, combined with complementary terrestrial observations and with physical models, have been widely used to monitor geohazards, revolutionizing our understanding of how the Earth system works. This Special Issue presents a collection of scientific contributions focusing on innovative EO methods and applications for monitoring and modeling geohazards, consisting of four Sections: (1) earthquake hazards; (2) landslide hazards; (3) land subsidence hazards; and (4) new EO techniques and services. [ABSTRACT FROM AUTHOR]

Many coastal cities have undertaken reclamation projects to satisfy the land demands of rapid urbanization. However, the foundations of reclaimed land are susceptible to settlement and can have undesirable environmental impacts that could adversely affect these dense, populated areas. In the case of international airports built on reclaimed areas especially, regional-scale deformation must be monitored to ensure operational security for public safety. Persistent Scatterer SAR Interferometry (PSI) technology has proven to be an effective tool to detect ground deformation in urban areas. However, it is still a challenge to apply PSI to effectively monitor settlement at airports built on newly developed coastal reclamation areas because of the scarcity of identifiable targets. Moreover, additional issues arise as the complicated deformation patterns associated with the underlying geological conditions make it difficult to interpret InSAR-derived results. In this study, a time-series analysis of a high-resolution TerraSAR-X satellite image stack acquired from September 2011 to October 2012 was performed by employing a modified PSI technique to retrieve the mean deformation velocity and time series of surface deformation at Pudong International Airport. Qualitative evaluation of spatial distribution and temporal evolution of deformation was conducted by joint analyses of deformation measurements and local geological data. Detailed analysis of various driving forces for deformation patterns confirmed that the results of deformation monitoring obtained by PSI are reliable and consistent with that of local geological surveys. Since the factors responsible for the subsidence within the airport are still at play, ongoing and routine deformation monitoring is warranted. [ABSTRACT FROM AUTHOR]

Displacement and deformation are fundamental measures of Earth surface mass movements such as glacier flow, rockglacier creep and rockslides. Ground-based methods of monitoring such mass movements can be costly, time consuming and limited in spatial and temporal coverage. Remote sensing techniques, here matching of repeat optical images, are increasingly used to obtain displacement and deformation fields. Strain rates are usually computed in a post-processing step based on the gradients of the measured velocity field. This study explores the potential of automatically and directly computing velocity, rotation and strain rates on Earth surface mass movements simultaneously from the matching positions and the parameters of the geometric transformation models using the least squares matching (LSM) approach. The procedures are exemplified using bi-temporal high resolution satellite and aerial images of glacier flow, rockglacier creep and land sliding. The results show that LSM matches the images and computes longitudinal strain rates, transverse strain rates and shear strain rates reliably with mean absolute deviations in the order of 10−4 (one level of significance below the measured values) as evaluated on stable grounds. The LSM also improves the accuracy of displacement estimation of the pixel-precision normalized cross-correlation by over 90% under ideal (simulated) circumstances and by about 25% for real multi-temporal images of mass movements.

We study the tectonic deformation from the February 2017 shallow earthquake sequence onshore Biga Peninsula (NW Turkey, NE Aegean region). We use InSAR interferograms (Sentinel-1 satellites) to identify the seismic fault (striking N110°E) and seismological data (parametric data and Moment Tensor solutions from NOA and KOERI catalogues) so as to refine its geometry and kinematics using inversion techniques. Despite the moderate magnitudes of the main events of the sequence (5.0 ≤ Mw ≤ 5.2), the total surface deformation is 2.2 fringes (or maximum 6.2 cm along LOS) and it is well visible with InSAR because of the shallow depth of the four main events (6–8 km) and the good coherence of the signal phase. Our geodetic inversion showed that the fault has normal-slip kinematics, dimensions of 6 by 6 km (length, width) and dips at 45°. The InSAR data are fitted by a uniform slip of 28 cm. In addition, 429 earthquakes were relocated with the HypoDD software and the use of a 1-D velocity model. The dip-direction of the fault is not retrievable from InSAR, but a south-dipping plane is clear from seismology and the aftershocks distribution. The spatial distribution of relocated events indicates the activation of one fault with a rupture zone length of about 10 km, a result of the occurrence of off-fault aftershocks along strike the main rupture. A stress inversion using 20 focal mechanisms (M ≥ 3.6; NOA solutions) indicates that faulting accommodates a N196°E extension. It is confirmed that moderate (5.0 ≤ M ≤ 5.2) shallow events can be traced in InSAR studies and can produce surface displacements that provide useful data in fault inversion.