Small Baseline Subset Technique Research Articles

Time series subsidence evaluation using NSBAS InSAR: a case study of twin megacities (Rawalpindi and Islamabad) in Pakistan

Ground deformation associated with natural and anthropogenic activities can be damaging for infrastructure and can cause enormous economic loss, particularly in developing countries which lack measuring instruments. Remote sensing techniques like interferometric synthetic aperture radar (InSAR) can thus play an important role in investigating deformation and mitigating geohazards. Rawalpindi and Islamabad are twin cities in Pakistan with a population of approximately 5.4 million, along with important government and private entities of national and international interest. In this study, we evaluate rapid paced subsidence in this area using a modified small baseline subset technique with Sentinel-1A imagery acquired between 2015 and 2022. Our results show that approximately 50 mm/year subsidence occurs in the older city of Rawalpindi, the most populated zone. We observed that subsidence in the area is controlled by the buried splays of the Main Boundary Thrust, one of the most destructive active faults in the recent past. We suggest that such rapid subsidence is most probably due to aggressive subsurface water extraction. It has been found that, despite provision of alternate water supplies by the district government, a very alarming number of tube wells are being operated in the area to extract ground water. Over 2017–2021, field data showed that near-surface aquifers up to 50–60 m deep are exhausted, and most of the tube wells are currently extracting water from depths of approximately 150–160 m. The dropping water level is proportional to the increasing number of tube wells. Lying downstream of tributaries originating from the Margalla and Murree hills, this area has a good monsoon season, and its topography supports recharge of the aquifers. However, rapid subsidence indicates a deficit between water extraction and recharge, partly due to the limitations inherent in shale and the low porosity near the surface lithology exposed in the area. Other factors amplifying the impacts are fast urbanization, uncontrolled population growth, and non-cultivation of precipitation in the area.

Integration of DInSAR and SBAS radar techniques to delineate the main areas of river recharge by sediments using ALOS-PALSAR-2 data: Oued Ghis case in Morocco

The Rif mountain range in northern Morocco comprises vulnerable lands highly susceptible to erosion, particularly water-induced erosion. This phenomenon significantly impacts the long-term sustainability of soil and water resources, including the lifespan of dam reservoirs and aquifer replenishment. Given that soil degradation is often accompanied by the transfer and accumulation of sediments over time in surface watercourses, monitoring this process using Differential Synthetic Aperture Radar Interferometry (DInSAR) provides insights into surface deformation. Integrating DInSAR techniques with the Small Baseline Subset (SBAS) approach using ALOS-PALSAR data enables the retrieval of a comprehensive deformation model over the study area. The results highlight the primary sources of erosion and sediment deposition zones. Displacement rates can reach up to 10 cm/year. Evaluation against ground truth data demonstrates that erosion and deposition rates are influenced by geological characteristics, rock mechanical properties, and topography. The good agreement between SBAS and DInSAR suggests that the SBAS technique could be reliable for identifying sediment recharge zones in these areas

Extending polarimetric optimization of multi-temporal InSAR techniques on dual polarized Sentinel-1 data

The rationale of combining polarimetric SAR data with multi-temporal InSAR techniques, which is based on polarimetric optimization, is to improve their performance in identifying coherent pixels and increasing the accuracy of deformation monitoring. This paper extended the polarimetric optimization of Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS) techniques on dual-polarized Sentinel-1 data. For this purpose, 20 dual-polarization (VV/VH) SAR images acquired by the Sentinel-1A sensor were used. The results indicated that by applying polarimetric optimization on dual-polarized data in the SBAS technique, the number of candidate and final coherent pixels increased 2.95 and 1.42 times, respectively. Similarly, the number of candidate and final coherent pixels (CP) increased 3.12 and 1.45 times in the PSI technique, respectively. Also, the effect of the polarimetric optimization on increasing the density of coherent points in different regions was investigated. In this framework, Sentinel-2 time-series images were classified into four classes (bare soil, vegetation, build-up, and others) using Google Earth Engine by applying remote sensing indices. This demonstrated that polarimetric optimization of the SBAS technique was more effective in bare soil and vegetated regions than in urban areas. However, polarimetric optimization of the PSI technique was more successful in non-urban regions than in urban areas. An external comparative analysis was also performed between the deformation results derived by PSI and SBAS techniques and GPS observation. The evaluation demonstrated that polarimetric optimization coupled with multi-temporal InSAR analysis yielded more reliable deformation results than conventional single-polarimetric data.

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

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

MONITORING OF LAND SURFACE DISPLACEMENT BASED ON SBAS-INSAR TIME-SERIES AND GIS TECHNIQUES: A CASE STUDY OVER THE SHIRAZ METROPOLIS, IRAN

Abstract. Nowadays, subsidence as one of the natural disasters, threaten urban environments. Over the past three decades, the small baseline subset (SBAS) InSAR method due to its capability to monitor medium to large-scale deformations, has emerged as an important tool for estimating surface displacements. In densely vegetated environments, however, the SBAS technique is not effective due to the decorrelation effect. Since the SBAS technique can estimate millions of points for subsidence, these data can be used as input to the Kriging method to estimate the unknown points. Therefore, in this study, we identified the subsidence disaster-stricken-urban areas in the Shiraz metropolis over a 4-year period (between 2017 and 2021) based on the fusion of the SBAS technique and geospatial information science (GIS) using Sentinel-1A time-series images. In the GIS part of this research, the ordinary kriging method was used for interpolation of the SBAS data. Also, the kernel estimation density (KED) was used for the preparation of the raster layers of a population and the built-up density. Based on 33 radar images in ascending and descending orbit, a total of 95 interferograms have been computed. In this research, temporal baselines of less than 100 meters and multi-look window dimensions of 200 meters were used. What is more, the amount of coherence was 0.8 in estimating displacements. Based on the results, the highest displacements occurred in districts 2, 4, 7, and 11. The maximum value of the displacement (30 mm per year) was seen in the southeast of the Shiraz metropolis, in district 7. Moreover, the surface displacement was mainly observed in the lands of the Shiraz international airport and some of the agricultural lands located in district 2. The reasons for the displacements in districts 4 and 11 are related to the high density of the building coverages in these regions. Also, the increased population density was another reason for the subsidence in district 4. It can be concluded that the suggested framework is efficient in determining time-series surface movements in extensive urban and non-urban areas.

SBAS-DInSAR analysis of January 2020 eruption of La cumbre Volcano, Galapagos Archipelago

The Galapagos Archipelago in the Pacific Ocean, situated 1000 km from the Ecuadorian coast, has been considered one of the UNESCO World Heritage sites. Its geographical location, ongoing seismo_volcanic activities, and the island's extreme isolation have led to the development of a wide variety of unique plant and animal species, which inspired Charles Darwin's theory of evolution. La cumbre volcano is one of the most active volcanoes in the Galapagos archipelago and is situated closest to the mantle plume. Eruptions are frequent here, with a record of 30 eruptions since 1800. Recently La Cumbre volcano erupted on 2020 January 12, with 11 seismic tremors recorded on that day with a maximum magnitude of 4.7. The Small Baseline Subset (SBAS) is an advanced Differential Interferometric SAR technique used to generate the deformation time series from the sequence of SAR datasets with a reduced spatiotemporal decorrelation. It is one of the best approaches for monitoring and analyzing surface deformations from space with a millimeter level of accuracy. In this paper, we analyze the January 2020 eruption of the La cumbre volcano using the SBAS technique. 9 Sentinel-1C band SAR data granules from 2019 November 17 to 2020 February 21 were used to generate the deformation time series map for estimating the degree of deformation at the volcanic edifice. As per the analysis, it is evident that the recent eruption has caused a displacement of up to −38 cm at the South Eastern flank of the crater, which has increased initially and then decreased on approaching the steady-state of eruption.

Evolution Assessment of Mining Subsidence Characteristics Using SBAS and PS Interferometry in Sanshandao Gold Mine, China

Ground subsidence is a common geological phenomenon occurring in mining areas. As an important Chinese gold mine, Sanshandao Gold Mine has a mining history of 25 years, with remarkable ground subsidence deformation. Mining development, life security, property security and ecological protection all require comprehension of the ground subsidence characteristics and evolution in the mining area. In this study, the mining subsidence phenomenon of the Sanshandao Gold Mine was investigated and analyzed based on Persistent Scatterer Interferometry (PSI) and small baseline subset (SBAS). The SAR (synthetic aperture radar) images covering the study area were acquired by the Sentinel-1A satellite between 2018 and 2021; 54 images (between 22 February 2018 and 25 May 2021) were processed using the PSI technique and 24 images (between 11 April 2018 and 12 July 2021) were processed using the SBAS technique. In addition, GACOS (generic atmospheric correction online service) data were adopted to eliminate the atmospheric error in both kinds of data processing. The interferometric synthetic aperture radar (InSAR) results showed a basically consistent subsidence area and a similar subsidence pattern. Both InSAR results indicated that the maximum LOS (line of sight) subsidence velocity is about 49 mm/year. The main subsidence zone is situated in the main mining area, extending in the northwest and southeast directions. According to the subsidence displacement of several representative sites in the mining area, we found that the PSI result has a higher subsidence displacement value compared to the SBAS result. Mining activities were accompanied by ground subsidence in the mining area: the ground subsidence phenomenon is exacerbated by the increasing mining quantity. Temporally, the mining subsidence lags behind the increase in mining quantity by about three months. In summary, the mining area has varying degrees of ground subsidence, monitored by two reliable time-series InSAR techniques. Further study of the subsidence mechanism is necessary to forecast ground subsidence and instruct mining activities.

An Optical Flow SBAS Technique for Glacier Surface Velocity Extraction Using SAR Images

The pixel offset-tracking (PO) technique developed from correlation matching for use on synthetic aperture radar (SAR) images has been widely employed to monitor glacier dynamics. However, the decorrelation caused by rapid changes in a glacier surface reduces the integrity of flow velocity extraction. In this letter, we propose a novel method, termed the optical flow (OF) small baseline subset(SBAS), developed from the optical flow algorithm, which is defined as the apparent motion of individual pixels on the image plane. The OF algorithm can compute dense flows at the individual pixel level with a low computational cost and may serve as an alternative to PO for estimating the glacier velocity field. During processing, We selected the image pairs having short spatiotemporal baselines and calculated their offset series according to the OF algorithm. We then used an interval estimation strategy to eliminate outliers to refine stacked offsets. Finally, the least-squares method was used to calculate the displacement series for each pixel. We tested the proposed method utilizing eight ALOS-2/PALSAR-2 images on a temperate debris-covered glacier, the Hailuogou Glacier on the southeastern Tibetan Plateau. Compared with PO-SBAS, our method effectively improves the coverage of glacier flow velocity monitoring from 73.5% to 99.6%.

Review of the SBAS InSAR Time-series algorithms, applications, and challenges

In the past 30 years, the small baseline subset (SBAS) InSAR time-series technique has emerged as an essential tool for measuring slow surface displacement and estimating geophysical parameters. Because of its ability to monitor large-scale deformation with millimeter accuracy, the SBAS method has been widely used in various geodetic fields, such as ground subsidence, landslides, and seismic activity. The obtained long-term time-series cumulative deformation is vital for studying the deformation mechanism. This article reviews the algorithms, applications, and challenges of the SBAS method. First, we recall the fundamental principle and analyze the shortcomings of the traditional SBAS algorithm, which provides a basic framework for the following improved time series methods. Second, we classify the current improved SBAS techniques from different perspectives: solving the ill-posed equation, increasing the density of high-coherence points, improving the accuracy of monitoring deformation and measuring the multi-dimensional deformation. Third, we summarize the application of the SBAS method in monitoring ground subsidence, permafrost degradation, glacier movement, volcanic activity, landslides, and seismic activity. Finally, we discuss the difficulties faced by the SBAS method and explore its future development direction.

InSAR Monitoring of Arctic Landfast Sea Ice Deformation Using L-Band ALOS-2, C-Band Radarsat-2 and Sentinel-1

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.

Remote Monitoring of Ground Motion Hazards in High Mountain Terrain Using InSAR: A Case Study of the Lake Sarez Area, Tajikistan

High mountain terrains, with steep slopes and deep valleys, are generally challenging areas to monitor using satellite earth observation techniques since the terrain creates perspective distortions and differences in illumination that can occlude or obfuscate a significant proportion of the land. This is particularly prominent in synthetic aperture radar (SAR) data, where the oblique geometry can result in large areas of layover and shadow, which must be excluded from any analysis. Interferometric SAR (InSAR) is an established technique for monitoring ground motion and this study assesses its potential for geohazard monitoring in mountainous areas using Lake Sarez in Tajikistan as a case study, applying SAR data from the Sentinel-1 mission. It is shown that, although the effect of layover and shadow is severe, a judicious combination of ascending and descending satellite passes is still capable of surveying 88% of the land surface. It is also demonstrated that, through the use of an advanced InSAR technique (the APSIS™ Intermittent Small Baseline Subset technique), near-complete coverage of ground motion measurements is possible, despite intermittent snow cover. Moreover, this is achieved without the need for ground control, which can be hazardous to establish in such areas. It is concluded that a combination of satellite passes and advanced InSAR techniques greatly facilitates the remote monitoring of ground motion hazards in high mountain areas.

Analysis of Groundwater Depletion/Inflation and Freeze–Thaw Cycles in the Northern Urumqi Region with the SBAS Technique and an Adjusted Network of Interferograms

This work investigated the large-scale ground deformations threatening the Northern Urumqi district, China, which are connected to groundwater exploitation and the seasonal freeze–thaw cycles that characterize this frozen region. Ground deformations can be well captured by satellite data using a multi-temporal interferometric synthetic aperture radar (Mt-InSAR) approach. The accuracy of the achievable ground deformation products (e.g., mean displacement time series and related ground displacement time series) critically depends on the number and quality of the selected interferograms. This paper presents a straightforward interferogram selection algorithm that can be applied to identify an optimal network of small baseline (SB) interferograms. The selected SB interferograms are then used to produce ground deformation products using the well-known small baseline subset (SBAS) Mt-InSAR algorithm. The developed interferogram selection algorithm (ISA) permits the selection of the group of SB data pairs that minimize the relative error of the mean ground deformation velocity. Experiments were carried out using a group of 102 Sentinel-1B SAR data collected from 12 April 2017 to 29 October 2020. This research study shows that the investigated farmland region is characterized by a maximum ground deformation rate of about 120 mm/year. Periodic groundwater overexploitation, coupled with irrigation and freeze–thaw phases, is also responsible for seasonal (one-year) ground displacement signals, with oscillation amplitudes up to 120 mm in the zones of maximum displacement.

Monitoring of land subsidence due to excessive groundwater extraction using small baseline subset technique in Konya, Turkey.

Konya, which is located within the Konya Closed Basin, is the most important agricultural production region in Turkey. The future of agriculture is threatened in this region due to the decline in groundwater levels and the intensive agricultural activities that require high water consumption and are not suitable to the climate conditions of the region. In addition to these parameters, the geological structure of Konya also poses various environmental problems such as land subsidence and sinkhole formation. This study aimed to investigate the causes of the land subsidence problem in Konya and its surroundings with the help of the interferometric synthetic aperture radar (InSAR) technique and auxiliary data, namely optic, Coordination of Information on the Environment (CORINE), and groundwater monitoring station data. In order to investigate the land subsidence in the study area, 58 Sentinel-1A images acquired between 2014 and 2018 were processed by using the small baseline subset (SBAS) technique. In addition, the time series derived from the SAR data was validated by a global navigation satellite system (GNSS) station located in the study area. The results revealed that severe land subsidence, some of which reached 75 mm/year, occurred in certain areas of the study area over a period of three and a half years. High consistency was found between the land subsidence and the groundwater level change observed in the region, with a cross-correlation of over 95%. Moreover, the temporal and spatial patterns of the cultivated area and urbanization, which are the main reasons for the consumption of groundwater in the region, were revealed using the optic data.

Deformations Prior to the Brumadinho Dam Collapse Revealed by Sentinel-1 InSAR Data Using SBAS and PSI Techniques

Differential Interferometric SAR (DInSAR) has been used to monitor surface deformations in open pit mines and tailings dams. In this paper, ground deformations have been detected on the area of tailings Dam-I at the Córrego do Feijão Mine (Brumadinho, Brazil) before its catastrophic failure occurred on 25 January 2019. Two techniques optimized for different scattering models, SBAS (Small BAseline Subset) and PSI (Persistent Scatterer Interferometry), were used to perform the analysis based on 26 Sentinel-1B images in Interferometric Wide Swath (IW) mode, which were acquired on descending orbits from 03 March 2018 to 22 January 2019. A WorldDEM Digital Surface Model (DSM) product was used to remove the topographic phase component. The results provided by both techniques showed a synoptic and informative view of the deformation process affecting the study area, with the detection of persistent trends of deformation on the crest, middle, and bottom sectors of the dam face until its collapse, as well as the settlements on the tailings. It is worth noting the detection of an acceleration in the displacement time-series for a short period near the failure. The maximum accumulated displacements detected along the downstream slope face were −39 mm (SBAS) and −48 mm (PSI). It is reasonable to consider that Sentinel-1 would provide decision makers with complementary motion information to the in situ monitoring system for risk assessment and for a better understanding of the ongoing instability phenomena affecting the tailings dam.

Disruptive influences of residual noise, network configuration and data gaps on InSAR-derived land motion rates using the SBAS technique

The interferometric synthetic aperture radar (InSAR) small baseline subset (SBAS) technique can be applied to land with varying deformation magnitudes ranging from mm/yr to tens of cm/yr. SBAS defines a network of interferograms that is limited by temporal and spatial baseline thresholds that are often applied arbitrarily, or in apparently subjective ways in the literature. We use simulated SAR data to assess (1) the influence of residual noise and SBAS network configuration on InSAR-derived deformation rates, and (2) how the number of interferograms and data gaps in the time series may further impact the estimated rates. This leads us to an approach for defining a SBAS network based on geodetic reliability theory represented by the redundancy number (r-number). Simulated InSAR datasets are generated with three subsidence signals of linear rates plus sinusoidal annual amplitudes of −2 mm/yr plus 2 mm, −20 mm/yr plus 5 mm and −100 mm/yr plus 10 mm, contaminated by Gaussian residual noise bounded within [−2;+2] mm, [−5;+5] mm and [−10;+10] mm, corresponding to standard deviations of approximately 0.5 mm, 1.5 mm and 3.0 mm, respectively. The influence of data gaps is investigated through simulations with percentages of missing data ranging from 5% to 50% that are selected (1) randomly across the 4-year time series, and (2) for three-month windows to represent the northern winter season where snow cover may cause decorrelation. These simulations show that small deformation rates are most adversely affected by residual noise. In some extreme cases, the recovered trends can be contrary to the signal (i.e., indicating uplift when there is simulated subsidence). We demonstrate through simulations that the r-number can be used to pre-determine the reliability of SBAS network design, indicating the r-values between ~0.8 and ~0.9 are optimal. r-numbers less than ~0.3 can deliver erroneous rates in the presence of noise commensurate with the magnitude of deformation. Finally, the influence of data gaps is not as significant compared to other factors such as a change in the number of interferograms used, although the blocks of “winter” gaps in the SBAS network show a larger effect on the rates than gaps at random intervals across the simulated time series.

Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland

Underground coal exploitation often results in land-surface subsidence, the rate of which depends on geological characteristics, the mechanical properties of the rocks, and the applied extraction technology. Since mining-related subsidence is characterized by “fast” displacement and high nonlinearity, monitoring this process by using Interferometric Synthetic Aperture Radar (InSAR) is very challenging. The Small BAseline Subset (SBAS) approach needs to predefine an a priori deformation model to properly estimate an interferometric component related to displacements. As a consequence, there is a lack of distributed scatterers (DS) when the selected a priori deformation model deviates from the real deformation. The conventional differential SAR interferometry (DInSAR) approach does not have this limitation, since it does not need any deformation model. However, the accuracy of this technique is limited by factors related to spatial and temporal decorrelation, signal delays due to the atmospheric artifacts, and orbital or topographic errors. Therefore, this study presents the integration of DInSAR and SBAS techniques in order to leverage the advantages and overcome the disadvantages of both methods and to retrieve the complete deformation pattern over the investigated study area. The obtained results were evaluated internally and externally with leveling data. Results indicated that the Kriging-based integration method of DInSAR and SBAS can be effectively applied to monitor mining-related subsidence. The root-mean-square Error (RMSE) between modeled and measured deformation by InSAR was found to be 11 and 13 mm for vertical and horizontal displacements, respectively. Moreover, DInSAR technique as a cost-effective and complementary method to conventional geodetic techniques can be applied for effective monitoring fast mining subsidence. The minimum and maximum RMSE between DInSAR displacement and specific leveling profiles were found to be 0.9 and 3.2 cm, respectively. Since the SBAS processing failed in subsidence estimation in the area of maximum deformation rate, the deformation estimates outside the maximum rate could only be compared. In these areas, the good agreement between SBAS and DInSAR indicates that the SBAS technique could be reliable for monitoring the residual subsidence that surrounds the subsidence trough. Using the proposed approach, we detected subsidence of up to −1 m and planar displacements (east–west) of up to 0.24 m.

Estimation of groundwater abstraction induced land subsidence by SBAS technique

The groundwater over pumping induced land subsidence is one of the major geological hazards in the alluvial aquifers. The objective of this study is to assess the rate of land subsidence in Kolkata metropolitan area, India. Land subsidence can be estimated with high precision by Small Baseline Subset (SBAS) analysis. The advantages of this method are generation of a mean deformation map. The ENVISAT ASAR data acquired at six different periods over the study site were processed by SBAS technique. The decline in the piezometric head from the year 2003 to 2010 was about 6 m. Land subsidence velocity was ~8 mm/year at Salt Lake City and Science City (near the eastern metropolitan bypass). The major cause for land subsidence is over pumping of groundwater from the confined aquifers in these areas. There is a reasonable comparison between the maximum region of land subsidence and low value piezometric head contours confirming that the over extraction of the confined aquifer of this region is responsible for land subsidence. It is necessary to control the groundwater pumping so as to arrest the declining trend of piezometric head of study area for managing the problem of land subsidence. Hence, the possible remedial measures that can be taken are reducing groundwater pumping in the study region.

Advanced DINSAR analysis on dam stability monitoring: A case study in the Germano mining complex (Mariana, Brazil) with SBAS and PSI techniques

This work presents an investigation of detection and monitoring of surface motions using Advanced Differential SAR Interferometry (A-DInSAR) with SBAS (Small Baseline Subset) and PSI (Persistent Scatterer Interferometry) techniques in the Germano iron mining complex region (Mariana, Brazil), after the collapse of the Fundão tailing dam occurred on November 5th, 2015. The research was carried out aiming to provide useful information about ground movement monitoring, planning and risk assessment in the area after the tragic event. The analysis was performed using 46 TerraSAR-X images and a Digital Elevation Model (DEM) obtained by Pleiades data. A-DInSAR processing provided the removal of the atmospheric phase artifacts, baseline related errors, DEM height error estimation and finally the ground displacement determination. The results pointed out that with both techniques it was possible to assess the stability conditions of the Germano mining assets, particularly the main structures of the Germano dam and the detection of small settlements in the mining tailings storage, pointing out that these may be an important components for risk management of open pit mining operations, including tailings dams.

Monitoring the Land Subsidence Area in a Coastal Urban Area with InSAR and GNSS.

In recent years, the enormous losses caused by urban surface deformation have received more and more attention. Traditional geodetic techniques are point-based measurements, which have limitations in using traditional geodetic techniques to detect and monitor in areas where geological disasters occur. Therefore, we chose Interferometric Synthetic Aperture Radar (InSAR) technology to study the surface deformation in urban areas. In this research, we discovered the land subsidence phenomenon using InSAR and Global Navigation Satellite System (GNSS) technology. Two different kinds of time-series InSAR (TS-InSAR) methods: Small BAseline Subset (SBAS) and the Permanent Scatterer InSAR (PSI) process were executed on a dataset with 31 Sentinel-1A Synthetic Aperture Radar (SAR) images. We generated the surface deformation field of Shenzhen, China and Hong Kong Special Administrative Region (HKSAR). The time series of the 3d variation of the reference station network located in the HKSAR was generated at the same time. We compare the characteristics and advantages of PSI, SBAS, and GNSS in the study area. We mainly focus on the variety along the coastline area. From the results generated by SBAS and PSI techniques, we discovered the occurrence of significant subsidence phenomenon in the land reclamation area, especially in the metro construction area and the buildings with a shallow foundation located in the land reclamation area.

Time-Series InSAR Analysis of the Small Baseline Subset to Estimate Surface Deformation at Mt. Bromo Indonesia

Penginderaan jauh kini memainkan peranan penting dalam pengamatan perilaku gunung api. Penelitian ini bertujuan untuk mengamati deformasi permukaan Gunung Bromo, yang terletak di Jawa bagian Timur, Indonesia, yang masuk dalam rangkaian sistem volkanik di Taman Nasional Bukit Tengger Semeru (TNBTS). Penggunaan algoritma SAR Interferometry (InSAR) yang disebut sebagai pendekatan Small Baseline Subset (SBAS) memungkinkan perancangan peta kecepatan deformasi rata-rata dan and peta time series displacement di wilayah kajian. Teknik SBAS yang biasa menghasilkan rangkaian observasi tahap interferometrik. Ini tercatat sebagai kombinasi linear dari nilai fase SAR scene untuk setiap pixel secara tersendiri. Analisis yang dilakukan terutama berdasarkan 22 data SAR data yang diperoleh melalui sensor ALOS/PALSAR selama kurun waktu 2007–2011. Beberapa penelitian menunjukkan bahwa kemampuan analisis InSAR dalam menyelidiki siklus gunung api, terutama Gunung Bromo yang memiliki karakteristik erupsi stratovolcano dalam satu hingga lima tahun. Analisis hasil memperlihatkan adanya kemajuan dari kajian sebelumnya akan InSAR wilayah tersebut, yang lebih fokus kepada deformasi yang berpengaruh kepada kaldera. Hal ini menunjukkan bahwa penelitian ini bisa diimplementasikan pada manajemen risiko atau manajemen infrastruktur