Permanent Scatterers Research Articles

Dam Structure Deformation Monitoring by GB-InSAR Approach

Ground-based synthetic aperture radar (GB-SAR) has been proved to be one of the cutting-edge techniques for the timely detection of slope failures in both natural and engineered slopes. This paper focuses on the structure deformation monitoring on the dams using GB-SAR data. Temporal sequence data was collected by ground SAR equipment from 29 July to 1 August for the Geheyan dam and the SAR images with high quality were selected through the exhaustive spatial-temporal coherence analysis based on permanent scatterer (PS) theory in this paper. A practical solution for dam structure deformation extraction after the atmospheric effect reduction is proposed in depth. The deformation of the dam spillway gates is greater than that of the dam body monitored by this GB-SAR campaign, and with the increase of the water level in the reservoir area, the displacement increases along the direction of water flow gradually. The surface deformation rate of the dam body is fitted by linear regression analysis, and the interpolated rate results are compared and verified with the plumb line measurements. Finally, the consistency of the dam deformation average rate based on the PS time series analysis technology by GB-SAR and plumb lines is verified in this article, demonstrated the excellent performance of the proposed method for remote multipoint displacement measurements of the dam.

МОНІТОРИНГ МІСЦЕВОСТІ ТА ВИСОТНИХ ПЕРЕШКОД У РАЙОНАХ АЕРОПОРТУ

The urgency of the research. At present, new aviation rules concerning the provision of air navigation information have been introduced in Ukraine. The rules take into account the legislation of the European Union, Eurocontrol documents, ICAO Standards on the accuracy, processing and use of aeronautical data, which include data on terrain and obstacles in the areas of airports. Target setting.One of the factors influencing the safety of civil aviation is the consideration of obstacles on the routes in the form of elevations and high-altitude objects. This is evidenced by accidents and catastrophes of aircraft caused by col-lisions with high-altitude obstacles. Therefore, it is necessary to monitor the ground space in the areas of an airport for the timely detection of obstacles to the updating of the electronic database on terrain and obstacles.Actual scientific researches and issues analysis.Recent open access publications on existing methods of collecting geo-spatial data to determine terrain and obstacles in areas of the airport wer e reviewed.Uninvestigated parts of general matters defining.The analysis of the given sources allows to draw a conclusion that concerning area 1 of the airport which is the territory of the state, the contradictory information on use of this or that method of definition of a relief of district and obstacles is resulted.The research objective. The main purpose of the article is to analyze the methods of monitoring spatial information on terrain and obstacles in area 1 of the airport using space-based radar systems that would meet the requirements of ICAO in this area for the maintenance of electronic databases of terrain and obstacles.The statement of basic materials.The quantitative requirements of ICAO for data on terrain and obstacles in area 1 of theairport are given. The errors of the results of the satellite radar topographic survey (SRTM), which allowed to obtain a digital model of the Earth's topography, were resolutionin the vertical plane 1 m, and in the horizontal plane - 30 m. The method of Permanent Scatterer SAR Interferometry PSInSAR - interferometry of stable reflectors using radars with synthe-sized space-based aperture allows to obtain the accuracy of stable reflectors (natural and man-made objects) in the vertical plane of about 1 m and the error in determining the heights of other objects is 14 m. Currently, the PSInSAR method is used to monitor the subsidence of the earth's surface in cities, which allows to determine the deformation of the earth's surface to the nearest millimeter. The grouping of remote sensing satellites TerraSAR-X and TanDEM-X provided global coverage of the earth's surface with a digital terrain model with an accuracy of at least 2 m in height. The spatial resolution was about 1 m. In 2020, a satellite with a synthesized aperture of the Capella-2 radar survey was launched into Earth orbit. This unique micro satellite weighs 107 kg. Its camera equipment currently has an ultra-high spatial resolution of 50 x 50 cm.Conclusions.Modern methods of satellite radar can determine the planned and altitude position of objects in the area of airport 1 (territory of the state) with accuracy and resolution that meets the requirements of ICAO for the maintenance ofan electronicdatabase of terrain and obstacles. It is proposed to perform the first phase of monitoring objects in the country with the help of satellite radar, and in the second phase of monitoring to involve a ground survey - to clarify the attributive information about the objects detected in the first phase.

Locating and monitoring of landslides based on small baseline subset interferometric synthetic aperture radar

Due to the effects of rugged terrain and vegetation cover, improving the locating and monitoring accuracy of time series interferometric synthetic aperture radar (TS-InSAR) in detecting the development of landslides in mountainous and valley areas has become a problem that needs to be solved. Our study uses the ground local incident angle (GLIA) to locate noneffective monitoring areas that are affected by steep terrain as well as to improve the locating accuracy of TS-InSAR technology in the effective coverage area. At the same time, the improved small baseline subset InSAR (SBAS-InSAR) method is used to improve the density of interferometer targets as well as to solve the problem of insufficient permanent scatterers due to the effects of vegetation coverage. A geometric model of GLIA was established. Ascending and descending synthetic aperture radar (SAR) data from the Advanced Land Observation Satellite (ALOS) were used for calculating the value of GLIA. The relationships of the GLIA and the interference characteristics of InSAR data were analyzed, and the locations of noneffective areas were determined. Finally, 19 ascending pass SAR data scenes acquired by the ALOS-1 satellite were processed through using the improved SBAS-InSAR method, and the detailed time series moving displacement information from 2007 to 2011 was mapped in Wudongde hydropower reservoir. Furthermore, the potentially moving landslide areas and landslide hazard areas were located in the effective interference areas. The active Jinpingzi landslide was investigated in detail, and the single-point monitoring results of SBAS-InSAR were compared with the electronic total station (ETS) measurement results. The conclusion shows that the monitoring results of SBAS-InSAR were in agreement with the ground field survey and the single-point ETS monitoring, and the applicability of the model and algorithm proposed was proved. Our study provides a reference for the early identification and high-precision monitoring of landslides in mountainous and valley areas.

Refinement of Landslide Susceptibility Map Using Persistent Scatterer Interferometry in Areas of Intense Mining Activities in the Karst Region of Southwest China

Incremental vertical ground movements due to coal mining can increase landslide susceptibility greatly in a short time and have thus triggered a large number of geological disasters, especially in the Karst Region, where a lot of steep slopes are on fractured rocks. Therefore, the landslide susceptibility maps (LSM) in Karst Region should be updated regularly. This paper presents an efficient methodology to update and refine LSM by using Persistent Scatterer Interferometry (PSI) data directly. First, an original LSM was produced by using a support vector machine (SVM) algorithm, and the distribution of coal mining was considered a crucial factor to generate the LSM. Then, the Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique was implemented to retrieve displacement time-series. Finally, the landslide displacement map, produced by the PSInSAR analysis, was projected to the direction of the steepest slope and resampled to the same cell in the LSM, to update the original LSM. This methodology is illustrated with the case study of Bijie in the Karst Region of Southwest China, wherein the ascending RADARSAT-2 and descending Sentinel-1 datasets are processed for the period of 2017–2019. The results show that the susceptibility degree increased in 56.41 km2 of the study area, and 80 percent of the increased susceptibility degree was caused by coal mining. The comparison between original and refined LSM in two specific areas revealed that the proposed method can produce more-reliable landslide susceptibility maps in areas of intense mining activities in the Karst Region.

Analysis of Clay-Induced Land Subsidence in Uppsala City Using Sentinel-1 SAR Data and Precise Leveling

Land subsidence and its subsequent hazardous effects on buildings and urban infrastructure are important issues in many cities around the world. The city of Uppsala in Sweden is undergoing significant subsidence in areas that are located on clay. Underlying clay units in parts of Uppsala act as mechanically weak layers, which for instance, cause sinking of the ground surface and tilting buildings. Interferometric Synthetic Aperture Radar (InSAR) has given rise to new methods of measuring movements on earth surface with a precision of a few mm. In this study, a Persistent Scatterer Interferometry (PSI) analysis was performed to map the ongoing ground deformation in Uppsala. The subsidence rate measured with PSI was validated with precise leveling data at different locations. Two ascending and descending data sets were analyzed using SARPROZ software, with Sentinel-1 data from the period March 2015 to April 2019. After the PSI analyses, comparative Permanent Scatterer (PS) points and metal pegs (measured with precise leveling) were identified creating validation pairs. According to the PSI analyses, Uppsala was undergoing significant subsidence in some areas, with an annual rate of about 6 mm/year in the line-of-sight direction. Interestingly, the areas of great deformation were exclusively found on postglacial clay.

A Temporal Phase Coherence Estimation Algorithm and Its Application on DInSAR Pixel Selection

Pixel selection is a crucial step of all advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques that have a direct impact on the quality of the final DInSAR products. In this paper, a full-resolution phase quality estimator, i.e., the temporal phase coherence (TPC), is proposed for DInSAR pixel selection. The method is able to work with both distributed scatterers (DSs) and permanent scatterers (PSs). The influence of different neighboring window sizes and types of interferograms combinations [both the single-master (SM) and the multi-master (MM)] on TPC has been studied. The relationship between TPC and phase standard deviation (STD) of the selected pixels has also been derived. Together with the classical coherence and amplitude dispersion methods, the TPC pixel selection algorithm has been tested on 37 VV polarization Radarsat-2 images of Barcelona Airport. Results show the feasibility and effectiveness of TPC pixel selection algorithm. Besides obvious improvements in the number of selected pixels, the new method shows some other advantages comparing with the other classical two. The proposed pixel selection algorithm, which presents an affordable computational cost, is easy to be implemented and incorporated into any advanced DInSAR processing chain for high-quality pixels' identification.

Change in regional land subsidence in Beijing after south-to-north water diversion project observed using satellite radar interferometry

ABSTRACTOver-exploitation of groundwater has caused severe land subsidence in Beijing during the past two decades. Since the middle route of South-to-North Water Diversion Project (SNWDP), the biggest water diversion project in China, started to deliver water to Beijing in December 2014, the groundwater shortage has been greatly alleviated. This study aims to analyze the impact of SNWDP on the spatiotemporal evolution of land subsidence in Beijing. Change in surface displacement in Beijing after SNWDP was retrieved and the spatiotemporal patterns of the change were analyzed based on long time-series Envisat Advanced Synthetic Aperture Radar (ASAR) (2004–2010), Radarsat-2 (2011–2014), and Sentinel-1 (2015–2017) satellite datasets using Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) techniques. Land subsidence unevenness index (LSUI) was proposed to represent the spatial unevenness of surface displacement. PS-Time approach was then adapted to examine the time series evolution of LSUI. The results showed that the InSAR measurements agree well with leveling measurements with R2 over 0.96. Although the maximum annual displacement rate reached −159.7 mm/year by 2017, over 57% of the area within 25 mm/year contour line showed decreasing or unchanged displacement rate after the south-north water delivered to Beijing. The settlement rate in Chaoyang-Dongbalizhuang (CD) subsidence center has decreased for 26 mm/year from 2011–2014 to 2015–2017. Only around 15% of the area experienced continued accelerating settlement rate through the three time periods, which was mainly located in the area with the compressible layer thickness over 190 m, while the magnitude of velocity increment considerably decreased after SNWDP. Land subsidence unevenness, represented by LSUI, developed more slowly after SNWDP than that during 2011–2014. However, LSUI at the edge of settlement funnel has kept developing and reached 1.7‰ in 2017. Decreasing groundwater level decline after SNWDP and the positive relationship (R2 > 0.74) between land subsidence and groundwater level clearly showed impacts of SNWDP on the alleviating land subsidence. Other reasons include geological background, increasing precipitation, and strict water management policies implemented during these years.

A Compensation Method for a Time–Space Variant Atmospheric Phase Applied to Time-Series GB-SAR Images

An atmospheric effect is a main error source that affects interferometric measurements. When a ground-based multiple-input multiple-output (GB-MIMO) radar, i.e., a specific type of GBsynthetic aperture radar (GB-SAR), was utilized to continuously monitor an open-pit mine, the interferometric phases of some interferograms were complexly space-variant due to time-variant weather conditions. The conventional method of atmospheric phase (AP) compensation was no longer applicable. This paper proposes an improved compensation method of a time-space variant AP applied to time-series GB-SAR images. The permanent scatterers (PSs) were classified into three types based on their different spatial properties: The noise-dominant PS (NPS), the deformationdominant PS (DPS), and the atmospheric effect-dominant PS (APS). The NPSs were firstly rejected based on the differential phase analysis of neighboring PSs. The DPSs were then rejected based on the cluster partition and selection. With the APSs, the space-variant AP was estimated with a spatial interpolation. To validate the feasibility of the proposed method, short-term and long-term experimental datasets were processed. Comparisons with a conventional method proved that the proposed method can well reduce AP errors and avoid the misunderstanding of motional areas.

Detection and 3D Visualization of Deformations for High-Rise Buildings in Shenzhen, China from High-Resolution TerraSAR-X Datasets

Shenzhen, a coastal city, has changed from a small village to a supercity since the late 1980s. With the rapid development of its population and economy, ground disasters also occur frequently. These disasters bring great harm to human life and surface architecture. However, there is a lack of regular ground measurement data in this area. Permanent scatterer interferometry (PSI) technology can detect millimeter deformation of urban surface. In this paper, the building height and deformation from 2008 to 2010 in the Futian District of Shenzhen are obtained by using this technique alongside high-resolution TerraSAR-X data. For a visual expression of the result, we export the permanent scatterer (PS) points on buildings to Google Earth for 3D visualization after ortho-rectification of the PS height. Based on the Google Earth 3D model, the temporal and spatial characteristics of the building deformation became obvious. The InSAR measurements show that during the study period, the deformation rates of the Futian area are between −10 and 10 mm/year, and deformation is mainly distributed in a few buildings. These unstable activities can be attributed to human activities and the natural climate, which provides a reference for the local government to carry out a survey of surface deformation, as well as the monitoring and management of urban buildings, in the future.

SMF-POLOPT: An Adaptive Multitemporal Pol(DIn)SAR Filtering and Phase Optimization Algorithm for PSI Applications

Speckle noise and decorrelation can hamper the application and interpretation of PolSAR images. In this paper, a new adaptive multitemporal Pol(DIn)SAR filtering and phase optimization algorithm is proposed to address these limitations. This algorithm first categorizes and adaptively filters permanent scatterer (PS) and distributed scatterer (DS) pixels according to their polarimetric scattering mechanisms [i.e., the scattering-mechanism-based filtering (SMF)]. Then, two different polarimetric DInSAR (POLDInSAR) phase OPTimization methods are applied separately on the filtered PS and DS pixels (i.e., POLOPT). Finally, an inclusive pixel selection approach is used to identify high-quality pixels for ground deformation estimation. Thirty-one full-polarization Radarsat-2 SAR images over Barcelona (Spain) and 31 dual-polarization TerraSAR-X images over Murcia (Spain) have been used to evaluate the performance of the proposed algorithm. The PolSAR filtering results show that the speckle of PolSAR images has been well reduced with the preservation of details by the proposed SMF. The obtained ground deformation monitoring results have shown significant improvements, about $\times 7.2$ (the full-polarization case) and $\times 3.8$ (the dual-polarization case) with respect to the classical full-resolution single-pol amplitude dispersion method, on the valid pixels’ densities. The excellent PolSAR filtering and ground deformation monitoring results achieved by the adaptive Pol(DIn)SAR filtering and phase optimization algorithm (i.e., the SMF-POLOPT) have validated the effectiveness of this proposed scheme.

GB‐InSAR interferogram processing method to generate DEM based on PS technology

Ground-based interferometry synthetic aperture radar (GB-InSAR) technology is becoming an important terrain mapping technology as it has the characteristics of short observation intervals, flexible operation environment and high data precision. Compared with air/space borne InSAR system, it is much easier for GB-InSAR to acquire repeat-pass/short-baseline data set, which can bring huge convenience on permanent scatterer (PS) technology. By using PS technology, on the one hand, the error caused by low coherence can be avoided, and on the other hand, the speed of the phase unwrapping part can be increased. In order to overcome the disadvantages of the non-uniform PS points distribution and low coherence cavities, the Kriging interpolation method is used to get an uniform digital elevation model (DEM) eventually. This study proposed a GB-InSAR interferogram processing method. First, it proposes a PS point selection method considering both accuracy and efficiency. Second, the study shows a network programming phase unwrapping method to unwrap the PS points. Then, Kriging interpolation method is analysed and used to fill the low coherence cavities. Finally, a field test is carried out in an open pit in Hebei, China. The DEM result of the observation area is shown to verify the correctness of this study's method.

A Model for Complex Subsidence Causality Interpretation Based on PS-InSAR Cross-Heading Orbits Analysis

Urban areas are subject to subsidence due to varying natural and anthropogenic causes. Often, subsidence is interpreted and correlated to a single causal factor; however, subsidence is usually more complex. In this study, we adopt a new model to distinguish different causes of subsidence in urban areas based on complexity. Ascending and descending Sentinel-1 data were analyzed using permanent scatterer interferometry (PS-InSAR) and decomposed to estimate vertical velocity. The estimated velocity is correlated to potential causes of subsidence, and modeled using different weights, to extract the model with the highest correlations among subsidence. The model was tested in Alexandria City, Egypt, based on three potential causes of subsidence: rock type, former lakes and lagoons dewatering (FLLD), and built-up load (BL). Results of experiments on the tested area reveal singular patterns of causal factors of subsidence distributed across the northeast, northwest, central south, and parts of the city center, reflecting the rock type of those areas. Dual causes of subsidence are found in the southwest and some parts of the southeast as a contribution of rock type and FLLD, whereas the most complex causes of subsidence are found in the southeast of the city, as the newly built-up areas interact with the rock type and FLLD to form a complex subsidence regime. Those areas also show the highest subsidence values among all other parts of the city. The accuracy of the final model was confirmed using linear regression analysis, with an R2 value of 0.88.

Transport Infrastructure Monitoring by InSAR and GPR Data Fusion

This study reviews research developments in non-destructive assessment of linear transport infrastructures. The main focus will be on the integration between satellite remote sensing and ground-based techniques. Specifically, the potential of using interferometric synthetic aperture radar (InSAR) and high-frequency ground penetrating radar (GPR) techniques as self-standing and integrated survey methodologies will be discussed. To this effect, an overview on data fusion techniques will be given. The last section of the paper reports recent results achieved by using both GPR systems and the permanent scatterers InSAR technique on a real-life railway.

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.

PS-driven inventory of town-damaging landslides in the Benevento, Avellino and Salerno Provinces, southern Italy

ABSTRACT The Apennine provinces of Campania Region (southern Italy), Benevento, Avellino and Salerno, are known for their ‘unstable towns’ suffering periodic damage from landslides. Their identification and mapping are very challenging tasks, since boundary mapping under urban settlements is not always possible without time-consuming field analysis of building damage and/or expensive mid-term diffuse ground-surface deformation monitoring. To overcome this problem, an inventory of town-damaging landslides, guided by available Permanent Scatterers (PS) ground-deformation data, was prepared. It provides an updated tool suitable to guide future land planning and historical site restoration in the Apennine provinces of Campania Region. Our fourteen Map Sheets show active and local reactivation of suspended/dormant landslides. Overall, 356 landslides were identified, amongst which 162 were identified as flows, 101 as slides, 1 as a spreads and 92 as complex landslides. To supplement our maps, a simplified distribution analysis based on major landslide morphometric characteristics was completed.

Assessment of capacity of using sentinel-1 images in monitoring land subsidence in Ho Chi Minh City

Permanent Scatterer InSAR (PSInSAR) technique is used commonly to evaluate land subsidence for some cities in the world and the pilot project in Ho Chi Minh City has shown the capability of this technique for mapping land subsidence in the period from 2006 to 2010. The result shows that PSInSAR can be applied to study the land subsidence phenomenon more efficiently than any traditional methods. However, SAR data often are commercial images such as ERS, ALOS, COSMO SkyMed… that a large number of SAR scenes must be collected to ensure the best results. This paper introduces results of the average subsidence velocities in Ho Chi Minh City that PSInSAR technique is applied to process SAR data from Sentinel-1 and COSMO SkyMed satellite. Evaluating the preliminary result showed that the capacity of using free Sentinel-1 images to replace commercial images for monitoring land subsidence.

Application of particle swarm optimization to the estimation of the TSInSAR deformation parameter

ABSTRACTTime-series Interferometric Synthetic Aperture Radar (TSInSAR) is a significant technology that monitors the earth’s surface deformation. Obtaining a highly accurate deformation parameter is challenging because of errors caused by local extremums. In this letter, we introduce Particle Swarm Optimization (PSO) to solve this problem. The deformation rate and elevation correction parameters to be estimated can be regarded as a particle in continuous two-dimensional space. An iterative search strategy is executed so that the particles move in the solution space. Cooperation and information sharing between particles are utilized in the search strategy, which is expected to move the particles toward the best solution and avoid the local optimum. To validate the reliability of PSO, 23 Synthetic Aperture Radar (SAR) images in Beijing were exploited to retrieve deformation by PSO as well as by standard Permanent Scatterer Interferometry (PSI). We compared the results with the corresponding levelling data. Experiment suggested that there about 11% points have higher accuracy by employing PSO than those by standard PSI.

ESTIMATION OF EARTH’S SURFACE MOVES AND DEFORMATION OF THE TERRITORY OF MINE “KHOTIN” OF KALUSH-GOLINSKYY FIELD BY METHOD OF RADAR INTERFEROMETRY

The article present processing techniques of radar data for calculating the deformations of the earth’s surface on the example of minefield, that is situated under the exogenous influence of underground workings of the “Khotin” minery Kalush-Golinskyy deposit. The estimation of accuracy of radar image processing methods, namely, the interferometry of the permanent radar scatterers and the interferometry of a series of small baseline lines, is made, by comparison with the results of processional geometric levelling with a short beam of deformation soil rappers of the profile lines of the mine field. On the basis of geodetic instrumental field observations, shells of sediments of the earth’s surface were constructed and the boundaries of zero deposition caused by deformation processes in the area of hollow fields were established. Working out of an array of measurements by two methods of interferometry allowed to put on the digital map the data that reflect the average sedimentation rates in the year at the radar measurement locations. Due to the ranking of average annual sedimentation rates, areas of interest were outlined where significant precipitation was observed. This made it possible to assert that the earth’s crust was caused by the anthropogenic influence on the Khotin miner, which was observed since 1977 and continues existing, albeit at lower speeds. The use of expensive and labour-intensive processional levelling only on pre-determined problem areas is rational both from a scientific and from a production point of view, as it allows better use of material and human resources. Therefore, there is a need for an integrated monitoring system to prevent an exogenous catastrophe on an ongoing basis.

A PS processing framework for long-term and real-time GB-SAR monitoring

ABSTRACTBased on the permanent scatterer (PS) technique, deformation measurements were taken in ground-based synthetic aperture radar (GB-SAR) applications. To realize long-term and real-time deformation monitoring, a PS processing framework is proposed. Firstly, a group selection framework is introduced. A certain number of GB-SAR images are selected as a group and different PS sets are selected. Secondly, a fluctuation factor is defined to detect abnormal images. Some images with abnormal amplitude information should not be used for deformation analysis. Thirdly, an adaptive threshold determination method to select the PSs is proposed. The PS numbers in different PS sets can be highly stable. Lastly, a real-time processing framework is introduced which can be applied for on-site monitoring. The proposed processing framework was also used to monitor an open-pit mine for about 11 days. Experimental results validated the effectiveness and reliability of the framework for long-term and real-time GB-SAR monitoring.

Sentinel-1 for Monitoring Land Subsidence of Coastal Cities in Africa Using PSInSAR: A Methodology Based on the Integration of SNAP and StaMPS

The sub-Saharan African coast is experiencing fast-growing urbanization, particularly around major cities. This threatens the equilibrium of the socio-ecosystems where they are located and on which they depend: underground water resources are exploited with a disregard for sustainability; land is reclaimed from wetlands or lagoons; built-up areas, both formal and informal, grow without adequate urban planning. Together, all these forces can result in land surface deformation, subsidence or even uplift, which can increase risk within these already fragile socio-ecosystems. In particular, in the case of land subsidence, the risk of urban flooding can increase significantly, also considering the contribution of sea level rise driven by climate change. Monitoring such fast-changing environments is crucial to be able to identify key risks and plan adaptation responses to mitigate current and future flood risks. Persistent scatterer interferometry (PSI) with synthetic aperture radar (SAR) is a powerful tool to monitor land deformation with high precision using relatively low-cost technology, also thanks to the open access data of Sentinel-1, which provides global observations every 6 days at 20-m ground resolution. In this paper, we demonstrate how it is possible to monitor land subsidence in urban coastal areas by means of permanent scatterer interferometry and Sentinel-1, exploiting an automatic procedure based on an integration of the Sentinel Application Platform (SNAP) and the Stanford Method for Persistent Scatterers (StaMPS). We present the results of PSI analysis over the cities of Banjul (the Gambia) and Lagos (Nigeria) showing a comparison of results obtained with TerraSAR-X, Constellation of Small Satellites for the Mediterranean Basin Observation (COSMO-SkyMed) and Environmental Satellite advanced synthetic aperture radar (Envisat-ASAR) data. The methodology allows us to highlight areas of high land deformation, information that is useful for urban development, disaster risk management and climate adaptation planning.