A SHORT REVIEW ON PERSISTENT SCATTERER INTERFEROMETRY TECHNIQUES FOR SURFACE DEFORMATION MONITORING

Technology advancement has urged the development of Interferometric Synthetic Aperture Radar (InSAR) to be upgraded and transformed. The main contribution of the InSAR technique is that the surface deformation changes measurements can achieve up to millimetre level precision. Environmental problems such as landslides, volcanoes, earthquakes, excessive underground water production, and other phenomena can cause the earth's surface deformation. Deformation monitoring of a surface is vital as unexpected movement, and future behaviour can be detected and predicted. InSAR time series analysis, known as Persistent Scatterer Interferometry (PSI), has become an essential tool for measuring surface deformation. Therefore, this study provides a review of the PSI techniques used to measure surface deformation changes. An overview of surface deformation and the basic principles of the four techniques that have been developed from the improvement of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), which is Small Baseline Subset (SBAS), Stanford Method for Persistent Scatterers (StaMPS), SqueeSAR and Quasi Persistent Scatterer (QPS) were summarised to perceive the ability of these techniques in monitoring surface deformation. This study also emphasises the effectiveness and restrictions of each developed technique and how they suit Malaysia conditions and environment. The future outlook for Malaysia in realising the PSI techniques for structural monitoring also discussed in this review. Finally, this review will lead to the implementation of appropriate techniques and better preparation for the country's structural development.

Polarimetric Persistent Scatterer Interferometry for Ground Deformation Monitoring with VV-VH Sentinel-1 Data

With the launch of the Sentinel-1 satellites, it becomes easy to obtain long time-series dual-pol (i.e., VV and VH channels) SAR images over most areas of the world. By combining the information from both VV and VH channels, the polarimetric persistent scatterer interferometry (PolPSI) techniques is supposed to achieve better ground deformation monitoring results than conventional PSI techniques (using only VV channel) with Sentinel-1 data. According to the quality metric used for polarimetric optimizations, the most commonly used PolPSI techniques can be categorized into three main categories. They are PolPSI-ADI (amplitude dispersion index as the phase quality metric), PolPSI-COH (coherence as the phase quality metric), and PolPSI-AOS (taking adaptive optimization strategies). Different categories of PolPSI techniques are suitable for different study areas and with different performances. However, the study that simultaneously applies all the three types of PolPSI techniques on Sentinel-1 PolSAR images is rare. Moreover, there has been little discussion about different characteristics of the three types of PolPSI techniques and how to use them with Sentinel-1 data. To this end, in this study, three data sets in China have been used to evaluate the three types of PolPSI techniques’ performances. Based on results obtained, the different characteristics of PolPSI techniques have been discussed. The results show that all three PolPSI techniques can improve the phase quality of interferograms. Thus, more qualified pixels can be used for ground deformation estimation by PolPSI methods with respect to the PSI technique. Specifically, this pixel density improvement is 50%, 12%, and 348% for the PolPSI-ADI, PolPSI-COH, and POlPSI-AOS, respectively. PolPSI-ADI is the most efficient method, and it is the first choice for the area with abundant deterministic scatterers (e.g., urban areas). Benefitting from its adaptive optimization strategy, PolPSI-AOS has the best performances at the price of highest computation cost, which is suitable for rural area applications. On the other hand, limited by the medium resolution of Sentinel-1 PolSAR images, PolPSI-COH’s improvement with respect to conventional PSI is relatively insignificant.

Pemanfaatan Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) Untuk Mengidentifikasi Laju Deformasi Permukaan di Lapangan Panas Bumi Ulubelu

Lapangan panas bumi Ulubelu telah diekstraksi sejak tahun 2012 dengan menghasilkan 2 x 55 MW dari PLTP unit 1 & 2 dan meningkat menjadi 4 x 55 MW sejak tahun 2016 dengan beroperasinya unit 3 dan unit 4. Peningkatan eksploitasi energi panas bumi di Ulubelu berpotensi menimbulkan perubahan kondisi geologi dan lingkungan yang salah satunya adalah subsiden. Penelitian ini bertujuan untuk mengidentifikasi potensi laju deformasi permukaan memanfaatkan metode Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) di lapangan panas bumi Ulubelu. Sebanyak 49 data Sentinel-1 periode Oktober 2014 hingga Maret 2020 dengan mode descending telah diolah dan dianalisis menggunakan tiga software utama yaitu SNAP, StaMPS dan StaMPS-Visualizer. Pembentukan interferogram pada setiap pasangan data (image pair) antara master dengan seluruh slave dilakukan menggunakan SNAP. Seluruh data interferogram kemudian diexport sebagai input data StaMPS untuk mendapatkan nilai piksel yang memiliki koherensi terbaik dan persistent. Hasil pengolahan menunjukkan laju deformasi per titik persistent scatterer (PS) berkisar antara -7,3 hingga +7,5 mm/tahun relatif pada arah Line of Sight (LOS) tanpa validasi lapangan. Pola deformasi berupa penurunan muka tanah berada di sekitar area eksploitasi panas bumi, sedangkan kenaikan muka tanah (uplift) terdeteksi di luar area eksploitasi. Hasil analisis menunjukkan bahwa kesamaan laju deformasi pada PLTP unit 1 & 2 dengan PLTP unit 3 & 4 mengindikasikan proses subsiden di area Ulubelu didominasi oleh proses ekstraksi fluida panas bumi. Temuan ini juga memperkuat penelitian sebelumnya yang menunjukkan bahwa proses subsiden di area panas bumi Ulubelu disebabkan oleh pemadatan batuan alterasi.

Accuracy of Sentinel-1 PSI and SBAS InSAR Displacement Velocities against GNSS and Geodetic Leveling Monitoring Data

Correct use of multi-temporal Interferometric Synthetic Aperture Radar (InSAR) datasets to complement geodetic surveying for geo-hazard applications requires rigorous assessment of their precision and accuracy. Published inter-comparisons are mostly limited to ground displacement estimates obtained from different algorithms belonging to the same family of InSAR approaches, either Persistent Scatterer Interferometry (PSI) or Small BAseline Subset (SBAS); and accuracy assessments are mainly focused on vertical displacements or based on few Global Navigation Satellite System (GNSS) or geodetic leveling points. To fill this demonstration gap, two years of Sentinel-1 SAR ascending and descending mode data are processed with both PSI and SBAS consolidated algorithms to extract vertical and horizontal displacement velocity datasets, whose accuracy is then assessed against a wealth of contextual geodetic data. These include permanent GNSS records, static GNSS benchmark repositioning, and geodetic leveling monitoring data that the National Institute of Statistics, Geography, and Informatics (INEGI) of Mexico collected in 2014−2016 in the Aguascalientes Valley, where structurally-controlled land subsidence exhibits fast vertical rates (up to −150 mm/year) and a non-negligible east-west component (up to ±30 mm/year). Despite the temporal constraint of the data selected, the PSI-SBAS inter-comparison reveals standard deviation of 6 mm/year and 4 mm/year for the vertical and east-west rate differences, respectively, thus reassuring about the similarity between the two types of InSAR outputs. Accuracy assessment shows that the standard deviations in vertical velocity differences are 9−10 mm/year against GNSS benchmarks, and 8 mm/year against leveling data. Relative errors are below 20% for any locations subsiding faster than −15 mm/year. Differences in east-west velocity estimates against GNSS are on average −0.1 mm/year for PSI and +0.2 mm/year for SBAS, with standard deviations of 8 mm/year. When discrepancies are found between InSAR and geodetic data, these mostly occur at benchmarks located in proximity to the main normal faults, thus falling within the same SBAS ground pixel or closer to the same PSI target, regardless of whether they are in the footwall or hanging wall of the fault. Establishing new benchmarks at higher distances from the fault traces or exploiting higher resolution SAR scenes and/or InSAR datasets may improve the detection of the benchmarks and thus consolidate the statistics of the InSAR accuracy assessments.

PS-InSAR-Based Validated Landslide Susceptibility Mapping along Karakorum Highway, Pakistan

Landslide classification and identification along Karakorum Highway (KKH) is still challenging due to constraints of proposed approaches, harsh environment, detail analysis, complicated natural landslide process due to tectonic activities, and data availability problems. A comprehensive landslide inventory and a landslide susceptibility mapping (LSM) along the Karakorum Highway were created in recent research. The extreme gradient boosting (XGBoost) and random forest (RF) models were used to compare and forecast the association between causative parameters and landslides. These advanced machine learning (ML) models can measure environmental issues and risks for any area on a regional scale. Initially, 74 landslide locations were determined along the KKH to prepare the landslide inventory map using different data. The landslides were randomly divided into two sets for training and validation at a proportion of 7/3. Fifteen landslide conditioning variables were produced for susceptibility mapping. The interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technique investigated the deformation movement of extracted models in the susceptible zones. It revealed a high line of sight (LOS) deformation velocity in both models’ sensitive zones. For accuracy comparison, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve approach was used, which showed 93.44% and 92.22% accuracy for XGBoost and RF, respectively. The XGBoost method produced superior results, combined with PS-InSAR results to create a new LSM for the area. This improved susceptibility model will aid in mitigating the landslide disaster, and the results may assist in the safe operation of the highway in the research area.

Monitoring Land Subsidence With The Combination of Persistent Scatterer Interferometry Techniques And Distributed Fiber Optic Sensing Techniques: A Case Study In Suzhou, China

Land subsidence is a global geo-hazard caused by various natural and human factors, and it directly threatens the safety of the environment and infrastructures. Investigating the mechanism of land subsidence is becoming more and more important. In this paper, we use the Persistent Scatterer Interferometry (PSI) technique combining the Distributed Fiber Optic Sensing (DFOS) technique to detect the spatial-temporal distributions of land subsidence and investigate the stratum deformation characteristics in Shengze, Suzhou. By analyzing Sentinel-1A date between 2017 and 2019 with the PSI technique and the deformation date derived by the DFOS technique, we conclude that the land surface deformations are mostly affected by the transitional exploitation of groundwater. The average Line-Of-Sight (LOS) deformation rate is mostly concentrated in -3 to 2.2 mm/yr, and a maximum subsidence rate of up to -16.9 mm/yr is observed in four industrial areas. Meanwhile, the DFOS-derived results reveal that the compression strata are mostly concentrated in 41.2-137.9 m depth, which is closely associated with the pore water pressure in the second confined aquifer. And it also reveals that the groundwater over-exploitation may be the significant triggering factor of the subsidence in the study area. The InSAR-derived results are also evaluated by the deformation time series obtained by the DFOS technique. The combination of those two new sensing and monitoring technologies enables us to highlight the large deformation area and reveal the mechanism of its subsidence, which is conducive to urban development, disaster risk management, and rational exploitation and management of groundwater in Suzhou.

An Investigation into Ground Movement on the Ventnor Landslide Complex, UK Using Persistent Scatterer Interferometry

Analysis of ground movement rates along the coastline and upper sections of the Ventnor landslide complex was carried out utilizing Persistent Scatterer Interferometric Synthetic Aperture Radar methods using Sentinel-1 SAR data from 2015 to 2019 (four years). Results were compared with rainfall data, historical ground investigation records and monitoring surveys carried out at Ventnor to relate observations to geology, geomorphology and rainfall. Decomposition of InSAR viewing geometries to vertical and horizontal aligned well with previous ground-based studies. Subsidence of −9.8 mm a−1 at the Lowtherville Graben and heave of +8.5 mm a−1 along the coastline south of Ventnor Park were observed. Decomposition to east-west geometry results showed an eastward displacement of approximately 12.4 mm a−1 along the coastline south of Ventnor Park, and a westward displacement of −3.7 mm a−1 throughout built up sections of Ventnor town, indicating the landslide was displacing more in an eastern direction than vertically. The cause of this movement was investigated by using publicly available intrusive boreholes paired with Persistent Scatterer Interferometry, and a new ground model spanning east-west parallel to the coastline was presented. No evidence of significant ground movement was observed along heavily protected sections of the coastline, suggesting coastal defences comprised of concrete aprons and rip rap appear to be an effective coastal management/landslide stabilisation tool when compared to rip rap alone. The mechanism of this increased stability is likely due to the combination of toe weighting and reduced toe erosion. A lag of approximately 13–20 days was observed between high rainfall events and subsequent peaks in ground displacement, which was shorter than a 29 day lag observed in a previous study. Similar observations of prolonged rainfall resulting in prolonged displacements were also observed. The study demonstrates the capabilities of the PSI methodology in identifying the same ground movements that conventional methods provide. By providing detailed analysis of ground deformation of the Ventnor landslide, we demonstrate small ground movements, validated with existing ground movement surveys. Similar methodology can be applied to coastal landslides in urban environments worldwide, providing a relatively cheap and rapid resource for coastal landslide monitoring.