PSInSAR Data Research Articles

InSAR-Driven Dynamic Landslide Hazard Mapping in Highly Vegetated Area

Landslide hazard mapping is important to urban construction and landslide risk management. Dynamic landslide hazard mapping considers landslide deformation with changes in the environment. It can show more details of the landslide process state. Landslides in highly vegetated areas are difficult to observe directly, which makes landslide hazard mapping much more challenging. The application of multi-InSAR opens new ideas for dynamic landslide hazard mapping. Specifically, landslide susceptibility mapping reflects the spatial probability of landslides. For rainfall-induced landslides, the scale exceedance probability reflects the temporal probability. Based on the coupling of them, dynamic landslide hazard mapping further considers the landslide deformation intensity at different times. Zigui, a highly vegetation-covered area, was taken as the study area. The landslide displacement monitoring effect of different band SAR datasets (ALOS-2, Sentinel-1A) and different interpretation methods (D-InSAR, PS-InSAR, SBAS-InSAR) were studied to explore a combined application method. The deformation interpreted by SBAS-InSAR was taken as the main part, PS-InSAR data were used in towns and villages, and D-InSAR was used for the rest. Based on the preliminary evaluation and the displacement interpreted by fusion InSAR, the dynamic landslide hazard mappings of the study area from 2019 to 2021 were finished. Compared with the preliminary evaluation, the dynamic mapping approach was more focused and accurate in predicting the deformation of landslides. The false positives in very-high-hazard zones were reduced by 97.8%, 60.4%, and 89.3%. Dynamic landslide hazard mapping can summarize the development of and change in landslides very well, especially in highly vegetated areas. Additionally, it can provide trend prediction for landslide early warning and provide a reference for landslide risk management.

Integration of Microtremor and PS-INSAR Analysis to Investigate the Susceptible Area in the Pronojiwo District (Indonesia) Following the 2021 East Java M6.1 Earthquake

The East Java M = 6.1 Earthquake struck on April 10, 2021, at the bottom of the Indian Ocean, about 96 km south of Kepanjen District, Malang Regency, Indonesia. The neighbouring Pronojiwo District in Lumajang Regency suffered significant damages and loss of lives. The earthquake aftermath underscored the necessity of examining susceptibility factors in the Pronojiwo area for future mitigation efforts. This research focuses on assessing earthquake vulnerability in Pronojiwo District using two methodologies: microtremor analysis and PS-InSAR. Microtremor data were directly collected, while PS-InSAR data were acquired from the Sentinel-1 satellite and processed using the ranging from 0.579 × 10 to 24.840 × 10 s /cm, in Pronojiwo District, with notably higher values found in areas with Semeru deposits, characterized by soft sediments. PS-InSAR analysis indicates concentrated negative shifts in residential zones, signaling structural damage. Regions with elevated vulnerability index values and negative PS points are considered more prone to earthquakes and subsequent building damages.

Deep Learning Improves Point Density in PS-InSAR Data Toward Finer-Scale Land Surface Displacement Detection

Deep Learning Improves Point Density in PS-InSAR Data Toward Finer-Scale Land Surface Displacement Detection

Mining Ground Deformation Estimation Based on Pre-Processed InSAR Open Data—A Norwegian Case Study

Sublevel caving mining causes surface deformation in three distinct zones parallel to the extracted deposit. Most of the published research is focused on the extent of the caved and fracture zones. The extent of the largest, continuous deformation zone and, thus, the influence of the mine on its surroundings is not yet fully documented. This study aimed at assessing the extent of surface deformation caused by the mining of a steep iron ore deposit in Norway. For this purpose, an innovative combination of the permanent scatterer (PS) InSAR technique and line-of-sight (LOS) movement data provided by a public web service and geographic information system (GIS) spatial interpolation methods was proposed. Two ascending tracks’ (A102 and A175) datasets spanning the period of 3 June 2016–11 October 2021 were used. Three interpolation methods, inverse distance weighted (IDW), radial basis function (RBF) and ordinary kriging (OK), were analysed in terms of their performance for mapping continuous deformation. The RBF and OK methods with anisotropy returned the lowest root mean square error (RMSE) values. The obtained difference in the maximum extent of deformation amounted to 26 m for the track A102 dataset and 44.5 m for the track A175 dataset, depending on the interpolation method used. The estimated maximum extent of the continuous deformation zone on the hanging-wall side of the sublevel caving mining operation is 663 m. This corresponds to a limit angle of 38.7 degrees, which is lower than in previously published studies. The results show that the influence of sublevel caving mining on the surroundings can be greater than previously thought. The usefulness of public PSInSAR data available from a national online service and spatial interpolation methods for determining the area of mining terrain deformations has been proven. The proposed approach provides a low-cost alternative and complementation for surveys performed about the mine and it is argued that it should be implemented as part of the mine’s monitoring system.

Integrated Approaches for Field Mapping by Traditional Investigation and Satellite PSInSAR Data: Results from the Montemartano Landslide (Central Italy)

The study presents an integrated investigation of a complex landslide based on multitemporal stereo aerial photographic interpretations, existing geotechnical monitoring data, and different PSInSAR datasets. The available information allowed for the quantification of the deformation history, also in periods with no monitoring in the field, making it possible to revise the geometry of the landslide compared to the official landslide mapping. Data from sparse inclinometers are compared with more spatially continuous satellite measurements, showing that the two monitoring techniques are consistent in terms of cumulative deformation trend and in terms of response to prolonged drought and wet periods. Therefore, reliable landslide mass displacements can be monitored using satellite products when ground instrumentations are no longer operating. Understanding the landslide behavior to rainfall conditions offers an important insight into the velocities and cumulative displacements expected during similar stages of enhanced landslide activity. The findings can be helpful to support urban planners in re-evaluating hazard and risk classification and implementing efficient mitigation techniques to reduce landslide damage.

Study on Influencing Factors of Surface Subsidence in Beijing Based on PSInSAR Data

Study on Influencing Factors of Surface Subsidence in Beijing Based on PSInSAR Data

Semi-automated regional classification of the style of activity of slow rock-slope deformations using PS InSAR and SqueeSAR velocity data

Large slow rock-slope deformations, including deep-seated gravitational slope deformations and large landslides, are widespread in alpine environments. They develop over thousands of years by progressive failure, resulting in slow movements that impact infrastructures and can eventually evolve into catastrophic rockslides. A robust characterization of their style of activity is thus required in a risk management perspective. We combine an original inventory of slow rock-slope deformations with different PS-InSAR and SqueeSAR datasets to develop a novel, semi-automated approach to characterize and classify 208 slow rock-slope deformations in Lombardia (Italian Central Alps) based on their displacement rate, kinematics, heterogeneity and morphometric expression. Through a peak analysis of displacement rate distributions, we characterize the segmentation of mapped landslides and highlight the occurrence of nested sectors with differential activity and displacement rates. Combining 2D decomposition of InSAR velocity vectors and machine learning classification, we develop an automatic approach to characterize the kinematics of each landslide. Then, we sequentially combine principal component and K-medoids cluster analyses to identify groups of slow rock-slope deformations with consistent styles of activity. Our methodology is readily applicable to different landslide datasets and provides an objective and cost-effective support to land planning and the prioritization of local-scale studies aimed at granting safety and infrastructure integrity.

Non-Invasive Methodological Approach to Detect and Characterize High-Risk Sinkholes in Urban Cover Evaporite Karst: Integrated Reflection Seismics, PS-InSAR, Leveling, 3D-GPR and Ancillary Data. A NE Italian Case Study

Sinkholes linked to cover evaporite karst in urban environments still represent a challenge in terms of their clear identification and mapping considering the rehash and man-made structures. In the present research, we have proposed and tested a methodology to identify the subsiding features through an integrated and non-invasive multi-scale approach combining seismic reflection, PS-InSAR (PSI), leveling and full 3D Ground Penetrating Radar (GPR), and thus overpassing the limits of each method. The analysis was conducted in a small village in the Alta Val Tagliamento Valley (Friuli Venezia Giulia region, NE Italy). Here, sinkholes have been reported for a long time as well as the hazards linked to their presence. Within past years, several houses have been demolished and at present many of them are damaged. The PSI investigation allowed the identification of an area with higher vertical velocities; seismic reflection imagined the covered karst bedrock, identifying three depocenters; leveling data presented a downward displacement comparable with PSI results; 3D GPR, applied here for the first time in the study and characterization of sinkholes, defined shallow sinking features. Combining all the obtained results with accurate field observations, we identified and mapped the highest vulnerable zone.

PS-InSAR derived deformation study in the Kachchh, Western India

The accumulation of crustal strain towards the western part of India, especially in the Kachchh Rift basin, is making one of the most seismically active parts of the Indian plate. Several strong to major earthquakes, including the recent 2001 (M7.7) Bhuj earthquake, were triggered in the Kachchh rift basin during the last two centuries. Therefore, in the present study, we have attempted to quantify crustal deformation towards the eastern part of mainland Kachchh using PSInSAR and GPS data from 2014 to 2019. The average LOS displacement of 4.3 ​mm/yr has been observed along the eastern segment of the Katrol Hill Fault (KHF). The deformation in this part can be correlated with the accumulation of strain along the hanging wall side of the south-dipping KHF. The accumulated strain is reflected in the form of seismic activity in this part and highlights the importance of the KHF zone for seismic hazard analysis. The PS-InSAR results are in good correlation with the GPS results of this part.

Long-Term Displacement Monitoring of Slow Earthflows by Inclinometers and GPS, and Wide Area Surveillance by COSMO-SkyMed Data

With reference to two slow earthflows in structurally complex clayey formations of the Italian southern Apennines, this paper shows the results of a long-term displacement monitoring using integrated systems of inclinometers and GPS, and their comparison with PSInSAR data. A fixed-in-place and traversal inclinometer system, first installed in 2004, recorded both the shear displacements along the slip bands, and the internal deformations of the landslide masses. A GPS network of permanent stations and benchmarks, installed in 2006–2007 in 23 strategic points of the slope, allowed for the temporal continuity of displacement monitoring. The two long series of data allowed to evaluate the factor scaling of the PSInSAR COSMO-SkyMed data, although the component of the displacement vector along the line of sight (LOS) was small. PSInSAR data allowed for the monitoring extension to houses and rigid structures that acted as reflectors. The joint data analysis allowed for the comprehension of the main features of the landslides’ kinematics.

The pattern of surface deformations in the Dąbrowa Basin (Poland) based on PSInSAR analysis

Slow, long-term ground deformations in the Dąbrowa Basin (southern Poland) were identified based on ERS-1 , ERS-2 and ENVISAT Synthetic Aperture Radar (SAR) images that were processed by means of Permanent Scatterer SAR Interferometry (PSInSAR). The Dąbrowa Basin is a region where two major factors can affect surface stability: intensive coal exploitation and neotectonic processes. In this study, in order to clarify the origin of surface deformations, the authors propose applying a newly developed algorithm of spatio-temporal PSInSAR data analysis. This analysis revealed that subsidence is a characteristic feature of the Dąbrowa Basin. A significant correlation exists between slow, long-term ground deformations and the location of the main tectonic structure of this region. The proposed spatiotemporal analysis of the PSInSAR data additionally showed some degree of correlation between mining activity and the studied deformations. This interconnection is a significant achievement of this study since the deformation values determined by means of PSInSAR were identified in earlier works solely on the basis of Dąbrowa Basin neotectonics. Normal 0 21 false false false PL X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Standardowy; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi; mso-fareast-language:EN-US;}

Hydro-geotechnical modelling of subsidence in the Como urban area

The urban area of Como (Italy) is particularly susceptible to subsidence. The reason is the particular structure of the subsoil, combined with the anthropic modification of the lakeshore lands linked to the historical evolution of the area. Moreover, this phenomenon exposes the lakefront areas to an increasing risk of flooding. The primary purpose of this study was to develop an effective methodology for the assessment of subsidence in urban areas, to be used as a support in groundwater management. The development of a coupled hydrogeological-geotechnical numerical model for the period 2004–2011 allowed recognizing the shoreline results as most susceptible areas to the phenomenon. Model results were critically evaluated through comparison with time series of PSInSAR and high precision levelling data available in the area. The anthropic perturbations of groundwater flow linked to the construction of lake flooding defenses in 2008–2009, enhanced the subsidence phenomenon in a localized area, pointing out the strong inter-dependence of groundwater circulation, lake level oscillations and geotechnical behavior of soils. Thus, the model revealed the most critical zones and geotechnical units, demonstrating to be a potential powerful tool to predict subsidence scenarios (e.g. the future completion of the floods defense works in the shoreline area).

Joint SAR Image Time Series and PSInSAR Data Analytics: An LDA Based Approach

Due to the constant increase in Earth Observation (EO) data collections, the monitoring of land cover is facilitated by the temporal diversity of the satellite images datasets. Due to the capacity of Synthetic Aperture Radar (SAR) sensors to operate independently of sunlight and weather conditions, SAR image time series offer the possibility to form a dataset with almost regular temporal sampling. This paper aims at mining the SAR image time series for an analysis of target’s behavior from the perspective of both temporal evolution and coherence. The authors present a two-level analytical approach envisaging the assessment of global (related to perceivable structures on the ground) and local (related to changes occurred within a perceivable structure on the ground) evolution inside the scene. The Latent Dirichlet Allocation (LDA) model is implemented to identify the categories of evolution present in the analyzed scene, while the statistical and coherent proprieties of the dataset’s images are exploited in order to identify the structures with stable electromagnetic response, the so-called Persistent Scatterers (PS). A comparative study of the two algorithms’ classification results is conducted on ERS and Sentinel-1 data. At global scale, the results fit human perception, as most of the points which can be exploited for Persistent Scatterers Interferometry (PS-InSAR) are classified within the same class, referring to stable structures. At local scale, the LDA classification demands for an extended number of classes (defined through a perplexity-based analysis), enabling further differentiation inside the evolutional character of those stable structures. The comparison against the map of detected PS reveals which classes present higher temporal correlation, determining a stable evolutionary character, opening new perspectives for validation of both PS detection and SITS analysis algorithms.

RESEARCH ON METHODS OF HIGH COHERENT TARGET EXTRACTION IN URBAN AREA BASED ON PSINSAR TECHNOLOGY

Abstract. PSInSAR technology has been widely applied in ground deformation monitoring. Accurate identification of Persistent Scatterers (PS) is key to the success of PSInSAR data processing. In this paper, the theoretic models and specific algorithms of PS point extraction methods are summarized and the characteristics and applicable conditions of each method, such as Coherence Coefficient Threshold method, Amplitude Threshold method, Dispersion of Amplitude method, Dispersion of Intensity method, are analyzed. Based on the merits and demerits of different methods, an improved method for PS point extraction in urban area is proposed, that uses simultaneously backscattering characteristic, amplitude and phase stability to find PS point in all pixels. Shanghai city is chosen as an example area for checking the improvements of the new method. The results show that the PS points extracted by the new method have high quality, high stability and meet the strong scattering characteristics. Based on these high quality PS points, the deformation rate along the line-of-sight (LOS) in the central urban area of Shanghai is obtained by using 35 COSMO-SkyMed X-band SAR images acquired from 2008 to 2010 and it varies from −14.6 mm/year to 4.9 mm/year. There is a large sedimentation funnel in the cross boundary of Hongkou and Yangpu district with a maximum sedimentation rate of more than 14 mm per year. The obtained ground subsidence rates are also compared with the result of spirit leveling and show good consistent. Our new method for PS point extraction is more reasonable, and can improve the accuracy of the obtained deformation results.

Multidisciplinary approach for fault detection: Integration of PS-InSAR, geomorphological, stratigraphic and structural data in the Venafro intermontane basin (Central-Southern Apennines, Italy)

A multidisciplinary methodology, integrating stratigraphic, geomorphological and structural data, combined with GIS-aided analysis and PS-InSAR interferometric data, was applied to characterize the relationships between ground deformations and the stratigraphic and the morphostructural setting of the Venafro intermontane basin. This basin is a morphostructural depression related to NW-SE and NE-SW oriented high angle normal faults bordering and crossing it. In particular, a well-known active fault crossing the plain is the Aquae Juliae Fault, whose recent activity is evidenced by archeoseismological data. The approach applied here reveals new evidence of possible faulting, acting during the Lower to Upper Pleistocene, which has driven the morphotectonic and the environmental evolution of the basin. In particular, the tectonic setting emerging from this study highlights the influence of the NW-SE oriented extensional phase during the late Lower Pleistocene – early Middle Pleistocene, in the generation of NE-SW trending, SE dipping, high-angle faults and NW-SE trending, high-angle transtensive faults. This phase has been followed by a NE-SW extensional one, responsible for the formation of NW-SE trending, both NW and SE dipping, high-angle normal faults, and the reactivation of the oldest NE-SW oriented structures. These NW-SE trending normal faults include the Aquae Juliae Fault and a new one, unknown until now, crossing the plain between the Venafro village and the Colle Cupone Mt. (hereinafter named the Venafro-Colle Cupone Fault, VCCF). This fault has controlled deposition of the youngest sedimentary units (late Middle Pleistocene to late Upper Pleistocene) suggesting its recent activity and it is well constrained by PS-InSAR data, as testified by the increase of the subsidence rate in the hanging wall block.

PSInSAR analysis in urban areas: a case study in the Arno coastal plain (Italy

The Permanent Scatterer Interferometry (PSI) has been used to detect the land subsidence of the Arno coastal plain, in particular within the urban area of the city of Pisa. Two satellite PSInSAR dataset (ERS 1/2 and Envisat) were used to quantify the spatial evolution of ground displacements. A set of 92 geotechnical borehole was also analyzed to relate the measured displacements with the local stratigraphic asset. Furthermore, the results of the interferometric data analysis were compared with the urban development, from1978 to 2013, of the eastern part of Pisa. The PSInSAR data show that the city of Pisa is divided in two sectors with different subsidence rates: the south - western part, with null or very small movements, and the eastern part that shows a general lowering with maximum velocities of 5 mm/yr. In the eastern part, single or small groups of buildings recorded subsidence rates higher than 15 mm/yr. Through the analysis of the temporal evolution and magnitude of the subsidence rates recorded by several buildings in these areas, the importance of the urbanization as an accelerating factor for the consolidation process have been demonstrated.

Dynamic online visualization of PS-InSAR surface motion estimation results using WebGL

ABSTRACTPersistent scatterer interferometry (PS-InSAR) is a common technique used in surface motion estimation. However, it is not easy to fully analyse the results, especially for non-experts. Due to the complexity of the formation of Persistent Scatterers (PS) points as well as the large difference in scale and time-series characteristics, it is necessary to develop new visualization methods for a better understanding and analysis of PS-InSAR data. In this article, we implement a dynamic online visualization for PS-InSAR surface motion estimation results using WebGL. A 3D interactive visualization method gives users vivid experiences with interactive operations so that they can easily observe scene details. Animation is used to show the development of surface motion over time as estimated using PS-InSAR, presenting results in an intuitive way through scientific visualization methods. Online visualization through our application makes PS-InSAR results accessible and relevant to dispersed users from diverse domains.

Detecting Slope and Urban Potential Unstable Areas by Means of Multi-Platform Remote Sensing Techniques: The Volterra (Italy) Case Study

Volterra (Central Italy) is a town of great historical interest, due to its vast and well-preserved cultural heritage, including a 2.6 km long Etruscan-medieval wall enclosure representing one of the most important elements. Volterra is located on a clayey hilltop prone to landsliding, soil erosion, therefore the town is subject to structural deterioration. During 2014, two impressive collapses occurred on the wall enclosure in the southwestern urban sector. Following these events, a monitoring campaign was carried out by means of remote sensing techniques, such as space-borne (PS-InSAR) and ground-based (GB-InSAR) radar interferometry, in order to analyze the displacements occurring both in the urban area and the surrounding slopes, and therefore to detect possible critical sectors with respect to instability phenomena. Infrared thermography (IRT) was also applied with the aim of detecting possible criticalities on the wall-enclosure, with special regards to moisture and seepage areas. PS-InSAR data allowed a stability back-monitoring on the area, revealing 19 active clusters displaying ground velocity higher than 10 mm/year in the period 2011–2015. The GB-InSAR system detected an acceleration up to 1.7 mm/h in near-real time as the March 2014 failure precursor. The IRT technique, employed on a double survey campaign, in both dry and rainy conditions, permitted to acquire 65 thermograms covering 23 sectors of the town wall, highlighting four thermal anomalies. The outcomes of this work demonstrate the usefulness of different remote sensing technologies for deriving information in risk prevention and management, and the importance of choosing the appropriate technology depending on the target, time sampling and investigation scale. In this paper, the use of a multi-platform remote sensing system permitted technical support of the local authorities and conservators, providing a comprehensive overview of the Volterra site, its cultural heritage and landscape, both in near-real time and back-analysis and at different scales of investigation.

Coastal inundation risk assessment due to subsidence and sea level rise in a Mediterranean alluvial plain (Volturno coastal plain – southern Italy)

Interdisciplinary studies of the last years highlight that the Italian coasts are significantly subject to retreat and to inundation by sea ingression due to natural and anthropic causes. In this study, the effects of future relative sea level have been evaluated for the Volturno River Plain, one of the widest coastal plain in southern Italy. The plain is characterized by high economical and ecological value, for the presence of farm activities, tourist structures and wetland protected zones. The study area is potentially prone to coastal flooding due to its very low topography and because it is affected by a severe subsidence, which emphasize the local effect of sea level rise due to the ongoing climate changes.In accordance with the guidelines of the MEDFLOOD project, the areas prone to inundation in the years 2065 and 2100 have been evaluated by comparing the future topographical information and expected relative sea level scenarios. The local Vertical Ground Displacements have been derived by PS-InSAR processing data whilst the mean values of the scenarios RCP 2.6 and RCP 8.5 provided by the IPCC (2014) have been used as future sea level projections in 2065 and 2100. The PS-InSar data elaboration shows that the area affected by subsidence corresponds to 35% of the Volturno plain and that the annual rate of the phenomenon ranges between −1 and −25 mm/yr.The inundation analysis, based on the classification of the areas in four hazard classes, indicates that in 2065 the zones located below the sea level will increase approximately of 50% respect to the present conditions, while between 2065 and 2100 the increase can be at least of 60% (IPCC, RCP 8.5 scenarios). Considering the socio-economical and ecological exposure, evaluated following the EUROSION project guidelines, the coastal flooding risk maps have been produced. Almost 8.2 km2 and 14.4 km2 of the investigated area has to be considered subject to very high marine inundation risk in 2065 and 2100, respectively.

Use of PSInSAR data to map highly compressible soil layers

A new approach to the use of Persistent Scatterers (PS) Interferometry data in the reconstruction of the extension of compressible geological bodies is presented. The methodology was applied in the test area of the Tiber River delta (Italy), characterized by the presence of two large marshy zones, known as the Maccarese and Ostia Antica ponds. PSInSAR™ data, derived from ERS1/2, ENVISAT and RADARSAT-1 images, and spanning a time interval between 1992 and 2006 were used to verify the possibility to reconstruct the spatial distribution of the peat levels inside the Maccarese and Ostia Antica ponds. Borehole information was analyzed to calibrate the InSAR data and the deformation rates were used to hypothesize the presence of a thick compressible layer where geological information is lacking. Variations in deformation rates registered by the single PS were assumed to be representative of a variation in the stratigraphic asset. The obtained results demonstrate that this approach could be satisfactorily used to investigate wide areas in a short time, reducing the number of boreholes to drill, and it could be a complementary technique to obtain information about the 2D geometry of specific geological levels.