Persistent Scatterer Interferometry Research Articles

Utilizing InSAR for Surface Stability Monitoring in Mining Sites: A Case Study of Sukari Gold Mine in Egypt

Abstract. The monitoring of mining sites is crucial as a result of the safety and environmental issues linked to mining activities. Traditional surveying and monitoring tools exhibit limitations in terms of spatial coverage and are associated with various concerns regarding time and cost efficiency. Hence, the mining industry has shown increased interest in the time-series analysis of interferometric synthetic aperture radar (InSAR). This is primarily due to its precision and wide spatial coverage advantages. This study employed an InSAR technology, persistent scatterer interferometry (PSI), to identify potential geohazards within the Sukari gold mine (SGM), located in Egypt. A total of 23 images were collected from the ascending orbit of Sentinel-1 sensor between January 7, 2022, and November 3, 2022, for the SGM mining location. Results revealed relatively stable measurements in non-mining areas of the site, with a surface displacement within ±10mm per year in the line-of-sight (LOS) direction. However, several active mining operation areas showed significant surface motion. Various sections of the open pit of the SGM exhibited displacement, including the southwestern edge (-16.8mm) and the northeastern edge (35.7mm), and the highest velocity was detected at a section of the western edge, which demonstrated an annual displacement of -64mm in the LOS. Additionally, notable surface motion was observed in some parts of the two tailings storage facilities at the site. The results of this study illustrate the importance of InSAR techniques in mining site-wide coverage stability monitoring.

Liquefaction ground deformations and cascading coastal flood hazard in the 2023 Kahramanmaraş earthquake sequence

The 2023 Kahramanmaraş earthquake sequence produced extensive liquefaction-induced ground deformations and ongoing flooding along the shoreline of the Mediterranean port city of İskenderun, Türkiye. This study compiles field observations and analyses from cross-disciplinary perspectives to investigate whether earthquake-induced liquefaction was a significant factor for increasing the flood hazard in İskenderun. Geotechnical reconnaissance observations following the earthquakes included seaward lateral spreading, settlement beneath buildings, and failures of coastal infrastructure. Three presented lateral spreading case histories indicate consistent ground deformation patterns with areas of reclaimed land. Persistent scatterer interferometry (PSI) measurements from synthetic aperture radar (SAR) imagery identify a noticeably greater rate of pre- and post-earthquake subsidence within the İskenderun coastal and urban areas relative to the surrounding regions. The PSI measurements also indicate subsidence rates accelerated following the earthquakes and were typically highest near the observed liquefaction manifestations. These evaluations suggest that while the liquefaction of coastal reclaimed fill caused significant ground deformations in the shoreline area, ongoing subsidence of İskenderun and other factors likely also exacerbated the flood hazard. Insights from this work suggest the importance of evaluating multi-hazard liquefaction and flood consequences for enhancing the resilience of coastal cities.

Automated Python workflow for generating Sentinel-1 PSI and SBAS interferometric stacks using SNAP on Geospatial Computing Platform

Detecting and monitoring surface deformation using radar satellite data is vital in geohazard assessment. Sentinel-1 has provided unprecedented spatial and temporal resolution, but data processing is complicated and poses computational challenges. Although software and tools exist, each with its own limitations. SNAP-ESA is notable for its user-friendly interface and stable performance in Interferometric Synthetic Aperture Radar (InSAR). However, SNAP-ESA lacks a flexible approach for generating interferometric time series stacks for Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) techniques and faces computational challenges over large areas. Here, we present an automated Python workflow, SNAPWF, using SNAP-ESA to enable efficient PSI and SBAS interferometric time series stacks generation using flexible network graphs. SNAPWF has been implemented on a dedicated geospatial computing platform, enabling efficient performance over large areas. Results confirm its ability to generate PSI and SBAS interferometric stacks using full Sentinel-1 scenes and achieve results comparable to existing software.

PERFORMANCE EVALUATION OF TEMPORAL MODEL AND SPATIAL CORRELATION METHODS FOR PERSISTENT SCATTERER DETERMINATION IN LANDSLIDE PRONE AREAS

Abstract. The Philippines is no stranger to natural hazards. Aside from flooding, landslides emerge as a primary contributor to damage dealt by natural hazards. Traditional methods for landslide monitoring require on-site field measurements, which makes them resource-intensive and time-consuming. Moreover, the frequency of updating of existing landslide hazard maps is limited by resources and manpower. This research introduces the application of remote sensing technology, specifically Persistent Scatter Interferometry (PSI), as a complementary tool for updating hazard maps. PSI enables the identification of stable ground points, eliminating the need for labor-intensive fieldwork and facilitating assessments of potential slope instability. Two distinct PSI processing methods are evaluated in the study; the Temporal Model approach and the Spatial Correlation model approach. Findings reveal that the Temporal Model approach successfully detected 11,647 Persistent Scatterers (PS) points, while the Spatial Correlation approach identified 272,614 PS points. Furthermore, the Spatial Correlation approach demonstrated its capability to detect PS points within high landslide susceptibility areas. Consequently, the results highlight the suitability of the Spatial Correlation approach for detecting PS points, particularly in landslide-prone regions, offering support to local landslide hazard monitoring systems. This research supports the initiative to a more efficient and cost-effective approach to maintaining up-to-date landslide susceptibility maps in the Philippines in enhancing disaster preparedness and mitigation efforts.

Surface Displacement Evaluation of Canto Do Amaro Onshore Oil Field, Brazil, Using Persistent Scatterer Interferometry (PSI) and Sentinel-1 Data

This study aims to investigate the occurrence of surface displacements in the Canto do Amaro (CAM) onshore oil field, situated in Rio Grande do Norte, Brazil, using Sentinel-1 data. The persistent scatterer interferometry (PSI) technique was used to perform the analysis based on 42 Sentinel-1 images, acquired from 23 July 2020 to 21 December 2021. Moreover, information regarding the structural geology of the study area was collected by referencing existing literature datasets. Additionally, a study of the water, gas, and oil production dynamics in the research site was conducted, employing statistical analysis of publicly available well production data. The PSI points results were geospatially correlated with the closest oil well production data and the structural geology information. The PSI results indicate displacement rates from −20.93 mm/year up to 14.63 mm/year in the CAM region. However, approximately 90% of the deformation remained in the range of −5.50 mm/year to 4.95 mm/year, indicating low levels of ground displacement in the designated research area. No geospatial correlation was found between the oil production data and the zones of maximum deformation. In turn, ground displacement demonstrates geospatial correlation with geological structures such as strike-slip and rift faults, suggesting a tectonic movement processes. The PSI results provided a comprehensive overview of ground displacement in the Canto do Amaro field, with millimeter-level accuracy and highlighting its potential as a complementary tool to field investigations.

A review on advances in persistent scatterer interferometry and proposing a novel method for phase optimization of distributed scatterers pixels

A review on advances in persistent scatterer interferometry and proposing a novel method for phase optimization of distributed scatterers pixels

Persistent scatterer interferometry (PSI) technique for road infrastructure monitoring: a case study of the roadway network of the Nile Delta (Egypt)

A dependable transportation infrastructure is an essential local resource, linking communities and facilitating economic expansion. The Nile Delta, renowned for its high population density, is experiencing subsidence as a result of natural forces exerting pressure on its sediments. Land subsidence exerts a substantial influence on infrastructure, economic, and social progress. This study examines the evaluation of land subsidence in roads experiencing various issues in the Nile Delta. Each year, subsidence results in significant damage and, in certain instances, complete disruption of numerous road networks, with potential durations ranging from a few days to several months. Conventional methods for identifying and monitoring subsidence on a large and intricate road network can be challenging due to the substantial time and resource requirements. Satellite-based monitoring is essential as it can effectively detect ground displacements caused by human activities (such as subterranean diggings and disruption of other infrastructures) or environmental dangers, specifically those associated with crucial hydrogeological incidents. Moreover, it possesses the benefit of efficiently encompassing extensive regions with precision. This study utilized the persistent scatterer interferometry (PSI) of SNAP-StaMPS workflow to employ differential interferometry synthetic aperture radar (DInSAR) processing methods for investigating the area. By utilizing Sentinel-1 data, we successfully acquired a comprehensive understanding of the deformation occurring in the study area, specifically in the roads where subsidence is persistently taking place. The data has demonstrated its value in enhancing our understanding of the safety status of infrastructure and facilitating maintenance actions. The accuracy of the radar interferometry results was confirmed through the use of in situ methods, including Global Navigation Satellite System (GNSS), Global Positioning System (GPS), smart phone, and unmanned aerial vehicle. This approach has demonstrated its capability to consistently detect vertical displacement in critical areas of roads. Furthermore, there is a strong correlation between the PSI interferometry and the in situ measurements when absolute values are taken into consideration. The findings of this study also demonstrate that open-source solutions are more effective, which encompass freely available data and software, offered through the COPERNICUS program, possess significant potential for monitoring vertical displacements in roads.

Tracking deformation velocity via PSI and SBAS as a sign of landslide failure: an open-pit mine-induced landslide in Himmetoğlu (Bolu, NW Turkey)

AbstractA destructive landslide occurred in Himmetoğlu village in Göynük District (Bolu, NW Turkey) caused by open-pit coal mining activities. Field observations after the landslide failure and interviews with villagers motivated us to question the possibility of using satellite SAR data to detect precursory signs of failure with regard to deformation velocity. In this study, first, landslide deformations were mapped by applying the digital elevation model (DEM) of Difference (DoD) method using DEMs from aerial photography and UAV data. However, the primary aim was to track deformation velocity as a sign of landslide failure with persistent scatterers interferometry (PSI) and small baseline subset (SBAS) methods from Sentinel-1A data. For the SBAS, the deformation velocity for ascending and descending orbits varied between − 12 and 39 mm year−1 and between − 24 and 6 mm year−1, respectively. For the PSI, the deformation velocity for ascending and descending orbits varied between − 16 and 31 mm year−1 and between − 18 and 20 mm year−1, respectively. PSI and SBAS resulted in sharply changing line-of-sight displacement rates, which were interpreted as slope failure signs, from three months prior to the landslide. In addition, higher deformation velocities were observed in locations closer to landslide crack as expected. Based on our findings, we concluded that SAR interferometric time-series analysis have the makings of being used as a suitable approach in early discerning and avoiding potential slope failures in open-pit mining areas, when it is made carefully by observing the progress in mining activities by considering the other factors such as rainfall and earthquakes.

Surface Displacements Monitoring in Cyprus via InSAR and Field Investigation: The Case Studies of Pyrgos-Parekklisia and Pedoulas Villages

The island of Cyprus is characterised by a complex geological environment as it overlies a boundary zone of three tectonic plates, leading to high seismicity and intensive tectonism. It consists highly of Neogene marls, exhibiting serious geotechnical problems due to their high content of clay minerals. Along with strong, destructive earthquakes, various geohazards have been identified in Cyprus, including landslides, swelling/shrinking phenomena and land subsidence etc. Pedoulas is a village in Cyprus experiencing ground deformation due to landslide phenomena. Conversely, Pyrgos and Parekklisia villages in Limassol, Cyprus are experiencing a long-term swelling/shrinking phenomenon. To further investigate this surface deformation, a time-series InSAR analysis of Sentinel-1 SLC images of ascending satellite passes was performed, with a parallelised version of PSI (Persistent Scatterers Interferometry), along with field investigation, for the time period of 2016 to 2021. Negative vertical displacements with maximum rates of −10 mm/y, were identified in Pedoulas village, while positive vertical displacements with a maximum rate of 10 mm/y, dominated in Pyrgos and Parekklisia villages. The analysis of precipitation data from 2017 to 2021, presented a correlation between annual fluctuations in precipitation in the affected areas and changes in the InSAR time-series deformation trends. In Pedoulas village, landslide movements sped up during spring and summer, when the infiltration of waste water in the ground intensified due to the increase in the tourist population. In Pyrgos-Parekklisia villages, higher positive deformation rates were identified in winter months, while during summer, when the formations dried out, uplifting phenomena stopped evolving. The integration of InSAR displacements with field investigation provided validation of the observed ground failures and added valuable insights into the driving mechanisms of the deformation phenomena. Finally, the assessment of the impact of the triggering factor in the evolution of the deformation phenomena, can serve as a valuable tool for risk mitigation.

Assessing Riverbank Change Caused by Sand Mining and Waste Disposal Using Web-Based Volunteered Geographic Information

River water is one of the most important natural resources for economic development and environmental sustainability. However, river water systems are vulnerable in some of the densely populated regions across the globe. Intense sand mining and waste disposal can lead to river changes, loose foundations, and biodiversity loss. This study aims to develop a web-based geographic information system (GIS) platform to monitor river channel changes and their impacts on river environments due to sand mining and waste burial. The system integrates open-source software, Windows Server 2012, a web server, and PostgreSQL with PostGIS plugins for efficient mapping and storage of geospatial data and volunteered reporting of location events. Interferometric methods, including SNAP2STAMPS Automated Algorithm, persistent scatterer interferometry (PSI), small baseline subset (SBAS), and Snap software, were used to analyze spatial changes of subsidence from Sentinel-1 satellite data from 2021 to 2023 in the Gadar River in Oshnavieh, Iran. The results showed that the maximum subsidence at the riverbank was −10.1 cm due to sand mining, and the maximum uplift was 8.2 cm due to waste landfilling. The average subsidence was reported to be −5.1 cm. The results emphasize spatial analysis, showcasing material mining’s impact on subsidence trends and underscoring the significance of public participation in monitoring river health. Three parameters—completeness, correctness, and quality—were used to validate the system. Validation results showed completeness, correctness, and quality rates of 94.15%, 92.48%, and 86.63%, respectively.

Monitoring land subsidence in the Peshawar District, Pakistan, with a multi-track PS-InSAR technique.

Peshawar is one of the most densely populated cities of Pakistan with high urbanization rate. The city overexploits groundwater resources for household and commercial usage which has caused land subsidence. Land subsidence has long been an issue in Peshawar due to insufficient groundwater removal. In this research, we employ the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique with Sentinel-1 imaging data to observe the yearly land subsidence and generate accumulative time-series maps for the years (2018 to 2020) using the SAR PROcessing tool (SARPROZ). The PS-InSAR findings from two contiguous paths are combined by considering the variance over the overlapping area. The subsidence rates in the Peshawar are from -59 to 17 mm/yr. The results show that subsidence is -28.48 mm/yr in 2018, the subsidence reached -49.02 mm/yr in 2019, while in 2020, the subsidence reached -49.90 mm/yr. The findings indicate a notable rise in land subsidence between the years 2018 and 2020. Subsidence is predicted in the research region primarily due to excessive groundwater removal and soil consolidation induced by surficial loads. The correlation of land subsidence observations with groundwater levels and precipitation data revealed some relationships. Overall, the proposed method efficiently monitors, maps, and detects subsidence-prone areas. The utilization of land subsidence maps will enhance the efficiency of urban planning, construction of surface infrastructure, and the management of risks associated with subsidence.

Irshalwadi landslide in Western Ghats of India: Observations from precursory slope movement, rainfall and soil moisture

The Western Ghats of India, a UNESCO world heritage site, is gradually becoming a hotspot for catastrophic landslides. On July 19, 2023, the entire Irshalwadi village in the Raigad district of Maharashtra, India, was obliterated due to a single catastrophic landslide. Of the 228 residents of the village, the landslide killed 27 people and 57 are still reported to be missing. The landslide occurred on a slope which exhibited no visual precedence of disturbance or creep. However, analysis of potential precursory movements prior to slope failure using the Persistent Scatterer Interferometry (PSI) technique reveals active movement near the base of the slope (in order of ∼12 mm/y). Sentinel-2 satellite imagery acquired post-event characterises the landslide as a bifurcated debris flow possibly triggered by heavy rainfall in the region. Peak cumulative rainfall, estimated by the Indian Meteorological Department (IMD), was observed in this region on 17, 18 and July 19, 2023 (∼500) mm and was the highest recorded rainfall in the region during the given period. This caused significant water percolation into the porous basaltic soil, leading to increased soil moisture, as supported by the Soil Moisture Active Passive (SMAP) data. The resultant increase in pore pressure caused the slope material to fail and eventually trigger the landslide.

On the Consistency of Tropospheric Delays Over Mountainous Terrain Retrieved From Persistent Scatterer Interferometry, GNSS, and Numerical Weather Prediction Models

On the Consistency of Tropospheric Delays Over Mountainous Terrain Retrieved From Persistent Scatterer Interferometry, GNSS, and Numerical Weather Prediction Models

SYNERGY OF ADVANCED PROCESSING TECHNIQUES USING COPERNICUS SAR AND OPTICAL SATELLITE IMAGERY TO DETECT GROUND DISPLACEMENTS: THE CASE STUDIES OF PYRGOS AND PAREKKLISIA VILLAGES IN CYPRUS

Abstract. Cyprus has a long history of destructive tectonic activity and related geohazards. This is mainly due to its location on the Mediterranean fault zone and the interaction of the Eurasian and African plates. To study the occurrence of land displacements on a national scale, various space-based monitoring techniques exploiting the Copernicus program’s datasets were studied using Sentinel-1 and Sentinel-2 satellite images for the period of 2016–2021. More specifically, differential spectral indices were calculated by subtracting the reference 2016 Sentinel-2 image from an image for every year until 2021, and a parallelised version of Persistent Scatterer Interferometry (PSI) was conducted using a time series of Sentinel-1 data over the same period, to identify ground displacements over time. The PSI analysis in the area around Pyrgos and Parekklisia villages, detected Line-of-Sight (LoS) uplift phenomena of a maximum rate of 8 mm/y, in ascending and descending Sentinel-1 satellite passes. Similarly, deformation was identified from optical image processing. The integration of both techniques provided qualitative and quantitative information about ground deformation events in both areas, showcasing a complementarity of results obtained, with PSI detecting displacements in urban/built-up areas, and multispectral change detection in rural environment. In terms of correlation, the two techniques showed a fit of 31.34% in ascending and 26% in descending pass, providing additional information on the size of affected areas. This synergistic approach facilitates the systematic monitoring of areas of interest, providing significant and timely information to decision-makers, to take actions and adopt protective measures when and where it is required.

ARTIFICIAL NEURAL NETWORK FOR PREDICTION OF LAND SUBSIDENCE IN MUDSLIDES REGION THROUGH INSAR AND RAIN DATA

Abstract. Mudslides are powerful and fast-moving mass movements that pose significant risks to human lives, infrastructure, and natural environments. They are commonly triggered by intense rainfall and their impact is particularly severe in mountainous regions. Synthetic Aperture Radar (SAR) technology can be used to calculate the subsidence of the territory over time by means of a temporal series of SAR images through the Persistent Scatterer Interferometry (PSI) technique. In some research Interferometric SAR (InSAR PSI) data were used to train Long Short-Term Memory (LSTM) based Artificial Neural Network (ANN) to provide movements forecasting. This paper proposes a new LSTM based ANN to forecast future territory movements considering both the past InSAR PSI data, the rain forecasting of the next acquisition and the past cumulative amount of rain since the movements of mudslides are strictly dependent to the quantity of rainfall accumulated in the terrain. The results of the proposed ANN are shown in terms of Mean Square Error (MSE) and Mean Absolute error (MAE) by comparing them with a LSTM-based ANN trained with only the InSAR PSI data.

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

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

Analysis of Land subsidencein coastal and urban areas by using various techniques– Literature Review

Over the past several decades, subsidence has emerged as a significant issue affecting urban, coastal, and mining areas worldwide. This phenomenon has been exacerbated by a decrease in groundwater resources, which has become a major problem on a global scale. Insufficient availability of surface water has led to excessive exploitation of the earth's groundwater system through unplanned processes. As a result, serious problems have arisen, including economic challenges, hazardous activities, and damage to the Earth's surface. One of the most significant and impactful consequences of excessive groundwater extraction is land subsidence. During a comprehensive literature review focusing on land displacement, 40 research papers were analyzed and discussed. These studies explored various techniques employed to monitor subsidence, such as synthetic aperture radar (SAR), interferometry synthetic aperture radar (InSAR), persistent scatterer interferometry synthetic aperture radar (PS-InSAR), and differential synthetic aperture radar (D-InSAR). Researchers have consistently found a strong correlation between the over extraction of underground fluids, such as water, oil, and gas, and land subsidence. One prominent cause of land subsidence identified by researchers is the over extraction of underground fluids. When excessive amounts of water, oil, or gas are extracted from underground reservoirs, the resulting voids and reduced pressure cause the overlying land to sink and compact. This process can have severe consequences for human settlements, infrastructure, and ecosystems in affected areas. The depletion of groundwater reserves, in particular, has become a pressing concern because of its vital role in supporting agricultural, industrial, and domestic water needs.Furthermore, the underground construction of tunnels has also been identified as a significant contributor to land subsidence. The excavation of tunnels creates voids and alters the natural balance of underground structures, leading to ground settlement and subsidence. This issue is particularly relevant in urban areas where extensive tunneling projects are undertaken to facilitate transportation, utilities, and infrastructure development. To monitor and assess land subsidence, various methods and processes are employed. SAR, InSAR, PS-InSAR, and D-InSAR techniques are valuable tools in this regard. SAR uses satellite-based radar systems to capture high-resolution images of the Earth's surface, enabling the detection of subtle changes over time. In contrast, InSAR employs two or more radar images to measure ground deformation by analyzing interference patterns. PS-InSAR focuses on persistent scatterers, which are specific targets that exhibit stable radar reflections over time, providing precise measurements of subsidence. D-InSAR combines two radar images acquired at different times to accurately calculate differential ground movements. By using advanced monitoring methods, scientists can assess the extent of subsidence and develop strategies to mitigate its negative impacts. It is crucial to adopt sustainable practices and ensure careful management of groundwater resources to effectively address this pressing issue.

Micro-vibration monitoring of pipelines using millimetre-wave MIMO radar

ABSTRACTTo ensure pipelines’ safety it is essential to have a regular and accurate monitoring system to inspect the behaviour of pipelines over time to prevent potential damage. This paper explores the capability of a millimetre-wave multiple-input multiple-output (MIMO) radar system for micro-vibration monitoring of pipelines. Compared to the conventional radars, MIMO radar provides cross-range resolution, while still being capable of monitoring a scene with sub-second data acquisition intervals. This makes it a non-contact system suitable for fast displacement and vibration monitoring. However, the application of MIMO radars has not been fully investigated and analysed for structural monitoring, especially for pipeline vibrations. In this study, a dense time-series of MIMO radar data was collected and processed by proposing a framework based on persistent scatterer interferometry to obtain a map of pipeline vibrations. Experiments were conducted in a controlled environment consisting of both functional and inactive water pipelines. The results showed that the system could detect displacements from micrometre up to sub-millimetre levels, with a displacement error of less than 3 μm. Additionally, the radar could identify the dominant frequencies of 24.375 and 24.500 Hz even in pipelines with very small vibration patterns. These results validate the high potential of millimetre-wave MIMO radar systems for non-contact monitoring of micro-vibrations in pipelines.

Analysis of the performance of polarimetric PSI over distributed scatterers with Sentinel-1 data

Sentinel−1 (S1) data enables effective monitoring of displacements using persistent scatterer interferometry (PSI). S1 includes VV and VH polarization channels, allowing us to apply polarimetric techniques to PSI. In short, polarimetric PSI (PolPSI) exploits the available polarization channels to enhance the identification and processing of measurement points including persistent scatterers (PS) and distributed scatterers (DS). Previous works have shown the benefits of using PolPSI for PS points with S1 data, but the corresponding analysis for DS is missing.DS points are processed by finding a neighborhood of statistically homogeneous pixels (SHP) and averaging the phase within that neighborhood. In this work we show how dual-polarimetric data are stricter on the selection of the SHP group than single-polarimetric data. Thanks to the information added by the second channel, different land covers are not mixed in the SHP group. As a result, the number of points in the SHP groups is generally smaller than with VV alone, but they are more reliable. The impact of this strategy on the resulting deformation estimates is also investigated in this work, showing that the deformation areas are fully preserved and the influence of nearby pixels associated with other scene elements is avoided.

Assessment and mapping of landslides in steep mountainous terrain using PS-InSAR: A case study of Karimabad Valley in Chitral

Assessing and mapping landslides in rugged, mountainous terrain presents considerable challenges due to the high cost, risk, and complexity involved. High-resolution assessments of landslides are essential for mitigating landslide-relevant damage and understanding landslide kinematics. Recent studies have utilized satellite-based Synthetic Aperture Radar Interferometry (InSAR) to achieve millimeter-scale detection of ground surface deformation. Among these InSAR techniques, Persistent Scatterers Interferometry (PS-InSAR) is particularly useful in identifying landslide-prone areas, offering a means to map and detect slope movements and characterize the stability of potentially unstable slopes. This study focuses on the slow-moving unstable hillslopes of Karimabad Valley in Chitral. We conducted an analysis using Sentinel-1 SLC data over a three-year period, obtained in interferometric wide swath mode with vertical-vertical polarization. Our results, derived from both ascending and descending satellite passes, reveal that the hillslopes of Karimabad Valley exhibit an average velocity of −25 to +28 mm/yr. Based on the deformation pattern identified, we detected seven deformation zones, with particular concern for the Beshgram village area. To better understand terrain steepness, four topographic profile lines (AA', BB', CC', and DD') were extracted and correlated with the deformation time series. Furthermore, the deformation time series were examined in relation to rainfall, earthquake, and snowfall data. These analyses highlight the complex interplay of multiple factors contributing to the observed variations in deformation, including the region's topography characterized by steep slopes, the freezing and thawing of snow, and seismic events.