Enviromental Monitoring of Land Subsidence in The Coastal Area of Padang City Using Sentinel 1 Sar Dataset

The land surface in the Padang City is thought to be experiencing a continuous relative subsidence due to natural processes and man-made activities. Factors that affect land subsidence include earthquakes, sea level rise, infrastructure development, sediment transport, and excessive use of groundwater sources. The purpose of this research is to map the rate of land subsidence which is processed from the Sentinel 1-A radar, satellite imagery using the Differential Synthetic Aperture Radar (DInSAR) method. The data used are two pairs of Sentinel-1A level 1 Single Looking Complex (SLC) imagery which were acquired in 2018 and 2019. Image processing is carried out by filtering and multilooking techniques on Synthetic Aperture Radar (SAR) images. The following process changes the phase unwrapping to the ground level phase using phase displacement. Land subsidence in 2018–2019 from DInSAR processing reached -10.5 cm / year. The largest land subsidence occurred in North Padang with an average of -7.64 cm/year. Land subsidence in the Padang City, which is located near the estuary, is due to the nature of the alluvial sediment material. The use of Sentinel 1 SAR remote sensing data can provide important information in the context of mitigating land subsidence in the Padang City. Therefore, we need the right policies to handle future land subsidence cases. Land subsidence mapping is one of the factors that determine the vulnerability of coastal areas to disaster

Monitoring of critical infrastructures by micro-motion estimation : the Mosul dam destabilization

In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures. Particularly, through the analysis of COSMO-SkyMed satellite data, a detailed and updated survey is provided, for monitoring the accelerating destabilization process of the Mosul dam, that represents the largest hydraulic facility of Iraq and is located on the Tigris river. The destructive potential of the wave that would be generated, in the event of the dam destruction, could have serious consequences. If the concern for human lives comes first, the concern for cultural heritage protection is not negligible, since several archaeological sites are located around the Mosul dam. The proposed procedure is an in-depth modal assessment based on the micro-motion estimation, through a Doppler sub-apertures tracking and a Multi-Chromatic Analysis (MCA). The method is based initially on the Persistent Scatterers Interferometry (PSI) that is also discussed for completeness and validation. The modal analysis has detected the presence of several areas of resonance that could mean the presence of cracks, and the results have shown that the dam is still in a strong destabilization. Moreover, the dam appears to be divided into two parts: the northern part is accelerating rapidly while the southern part is decelerating and a main crack in this north-south junction is found. The estimated velocities through the PS-InSAR technique show a good agreement with the GNSS in-situ measurements, resulting in a very high correlation coefficient and showing how the proposed procedure works efficiently

Measurements of surface river Doppler velocities with along-track InSAR using a single antenna

Nowadays, a worldwide database containing the historical and reliable data concerning the water surface speed of rivers is not available and would be highly desirable. In order to meet this requirement, the present work is aimed at the design of an estimation procedure for water flow velocity by means of synthetic aperture radar (SAR) data. The main technical aspect of the proposed procedure is that an along-track geometry is synthesized using a single antenna and a single image. This is achieved by exploiting a multichromatic analysis in the Doppler domain. The application of this approach allows us to obtain along-track interferometry equivalent virtual baselines much lower than the equivalent baseline corresponding to the decorrelation time of raw data preserving data coherence. The performance analysis, conducted on live airborne full-polarimetric SAR data, highlights the effectiveness of the proposed approach in providing reliable river surface velocity estimates without the need of multiple passes on the observed scene

Campotosto Dam destabilization under earthquake series ongoing in central Italy

This paper reports the results of a study on the estimation of the deformation of the Italian Campotosto Lake dams and bridge due to the earthquake series recently occurring in the Central of Italy and still ongoing. The analysis is performed by processing a stack of 180 synthetic aperture radar (SAR) interferometric images, observed by the Italian satellite system COSMO-SkyMed (CSK) and 74 interferometric SAR images, collected by the European Space Agency (ESA) satellite system Sentinel. Results show an ongoing negative subsidence at the location of the main Campotosto lake dam infrastructure and the main bridge connecting two opposite roads. The work reveals information about the Earth surface deformation, which might be useful in order to track the subsidence caused by the recent earthquake series occurring in the center of Italy and, hence, for a correct administration of the dam and an efficient technical maintenance of the local territory

An atmospheric phase screen estimation strategy based on multi-chromatic analysis for differential interferometric synthetic aperture radar

In synthetic aperture radar (SAR), the separation of the height between the ground subsidence phase components and the atmospheric phase delay mixed in the global SAR interferometry (InSAR) phase information is an issue of primary concern in the remote sensing community. This paper describes a complete procedure to address the challenge to estimate the atmospheric phase screen and to separate the three-phase components by exploiting only one InSAR image couple. This solution has the capability to process persistent scatterers subsidence maps potentially using only two multitemporal InSAR couples observed in any atmospheric condition. The solution is obtained by emulating the atmosphere compensation technique that is largely used by the global positioning system where two frequencies are used in order to estimate and compensate the positioning errors due to atmosphere parameters' variations. A sub-chirping and sub-Doppler algorithm for atmospheric compensation is proposed, which allows the successful separation of the height from the subsidence and the atmosphere parameters from the interferometric phase observed on one InSAR couple. The results are given processing images of two InSAR couples observed by the COSMO-SkyMed satellite system

Ionospheric correction of interferometric SAR data with application to the cryospheric sciences

Thesis (Ph.D.) University of Alaska Fairbanks, 2018The ionosphere has been identified as an important error source for spaceborne Synthetic Aperture Radar (SAR) data and SAR Interferometry (InSAR), especially for low frequency SAR missions, operating, e.g., at L-band or P-band. Developing effective algorithms for the correction of ionospheric effects is still a developing and active topic of remote sensing research. The focus of this thesis is to develop robust and accurate techniques for ionospheric correction of SAR and InSAR data and evaluate the benefit of these techniques for cryospheric research fields such as glacier ice velocity tracking and permafrost deformation monitoring. As both topics are mostly concerned with high latitude areas where the ionosphere is often active and characterized by turbulence, ionospheric correction is particularly relevant for these applications. After an introduction to the research topic in Chapter 1, Chapter 2 will discuss open issues in ionospheric correction including processing issues related to baseline-induced spectrum shifts. The effect of large baseline on split spectrum InSAR technique has been thoroughly evaluated and effective solutions for compensating this effect are proposed. In addition, a multiple sub-band approach is proposed for increasing the algorithm robustness and accuracy. Selected case studies are shown with the purpose of demonstrating the performance of the developed algorithm. In Chapter 3, the developed ionospheric correction technology is applied to optimize InSAR-based ice velocity measurements over the big ice sheets in Greenland and the Antarctic. Selected case studies are presented to demonstrate and validate the effectiveness of the proposed correction algorithms for ice velocity applications. It is shown that the ionosphere signal can be larger than the actual glacier motion signal in the interior of Greenland and Antarctic, emphasizing the necessity for operational ionospheric correction. The case studies also show that the accuracy of ice velocity estimates was significantly improved once the developed ionospheric correction techniques were integrated into the data processing flow. We demonstrate that the proposed ionosphere correction outperforms the traditionally-used approaches such as the averaging of multi-temporal data and the removal of obviously affected data sets. For instance, it is shown that about one hundred multi-temporal ice velocity estimates would need to be averaged to achieve the estimation accuracy of a single ionosphere-corrected measurement. In Chapter 4, we evaluate the necessity and benefit of ionospheric-correction for L-band InSAR-based permafrost research. In permafrost zones, InSAR-based surface deformation measurements are used together with geophysical models to estimate permafrost parameters such as active layer thickness, soil ice content, and permafrost degradation. Accurate error correction is needed to avoid biases in the estimated parameters and their co-variance properties. Through statistical analyses of a large number of L-band InSAR data sets over Alaska, we show that ionospheric signal distortions, at different levels of magnitude, are present in almost every InSAR dataset acquired in permafrost-affected regions. We analyze the ionospheric correction performance that can be achieved in permafrost zones by statistically analyzing correction results for large number of InSAR data. We also investigate the impact of ionospheric correction on the performance of the two main InSAR approaches that are used in permafrost zones: (1) we show the importance of ionospheric correction for permafrost deformation estimation from discrete InSAR observations; (2) we demonstrate that ionospheric correction leads to significant improvements in the accuracy of time-series InSAR-based permafrost products. Chapter 5 summarizes the work conducted in this dissertation and proposes next steps in this field of research

Fractures in glaciers - Crack tips and their stress fields by observation and modeling

High-resolution optical camera systems are opening new opportunities to studyfractures in ice. Here, we present data obtained from the Modular Aerial CameraSystem camera system operated onboard of Alfred Wegener Institute HelmholtzCentre for Polar and Marine Research (AWI) polar aircraft in northeast Green-land in 2022. In addition, we are using optical and radar satellite imagery. Thestudy area is the 79N Glacier (Nioghalvfjerdsbræ, 79NG), an outlet glacier of theNortheast Greenland Ice Stream. We found that crack tips are exhibiting addi-tional isolated cracks ahead of the main crack. Subsequent crack propagationis starting from those isolated cracks, leading to an advance of the crack, withbridges between crack faces. The bridges provide information of the episodiccrack propagation. Fractures have typically a length scale of kilometers andthe distance of crack faces is in the order of meters to tenths of meters. Frac-ture modes will be inferred from stress fields computed by an inverse modelingapproach using the Ice Sheet and Sea Level System Model. To this end, a surfacevelocity field derived from satellite remote sensing is used for the optimal controlmethod that constrains model parameters, for example, basal friction coefficientor rheology

Terrestrial radar signal improvement by correction for atmospheric disturbances

Glaciers have a major impact on the world’s climate and are therefore, along with other factors, the focus of research on climate change. There are many options to study glaciers and their condition. One of them is the speed of ice flow. In this paper, the ice flow velocity of the Gorner Glacier, which is located in the Swiss Alps, is studied. The main aim of this thesis is investigating the potential of terrestrial radar interferometry (TRI) to calculate the ice flow of a alpine glacier. A big challenge with radio detection and ranging (radar) is diffraction, which is the change in the optical properties of the atmosphere. Thus, it is visible on the GAMMA Portable Radar Interferometer (GPRI) measurements but is not the information one is interested in. This cause temporary phase shifts that can attain several phase cycles which significantly distorts the results. There are several approaches to correct the atmospheric disturbances on radar images. In this master thesis, two of them are investigated. The first one was developed by Dr. Martin L¨uthi from the Glaciology and Geomorphodynamics group at University of Zurich. His approach is to model the ice flow by the assumption that the ice moves regularly and particularly in the same direction. Thus, the phase shift of an ice pixel should show a clear trend. The irregular movements of the phase shift is noise and among others the mentioned atmospheric disturbance. To correct the atmospheric disturbance, it is assumed that the disturbance is similar on one azimuth line, so the extracted noise is grouped over them and a general noise pattern is subtracted from the original radar signal. The second algorithm corrects the atmospheric disturbance by an adaptive filtering of multi-looking images, which was developed by Goldstein and C. L. Werner (1998) and is an often used approach. The effectiveness of correcting for atmospheric disturbance using the extracted noise was not fully confirmed. When comparing the results with correction by an adaptive filter it was revealed relatively similar results. The calculations using GPRI data were verified using control points based on independent photogrammetry data from uncrewed aerial vehicles (UAV). The modeling via GPRI data shows a significant underestimation of the velocity of the ice flow compared to the UAV control points. It can be assumed that this underestimation could be significantly improved if the location of the GPRI were chosen more favourably or by implementing a correction factor of the angle. Furthermore, it became clear that both algorithms, which are based on the GPRI data, show only small changes in the calculated velocities before and after the correction. The atmospheric disturbance is very complex and requires more sophisticated approaches, whereby a combination between different approaches and an optimal selection of data is to be preferred

A new paradigm to observe early warning faults of critical infrastructures by micro-motion estimation from satellite SAR observations. Application to pre-collapse damage assessment of the Morandi bridge in Genoa (Italy)

Damage in civil engineering structures can be represented by a reduction of the structural bearing capacity during their service period. This reduction is usually caused by degradation of materials, structural components or connections due to environmental phenomena leading to excessive loading effects. Typical damages in civil engineering structures include cracks, fatigue, steel corrosion, concrete spalls, scour and deterioration. Undetected damage can lead to structural failure causing loss of human life. Considering these problems it is necessary to detect early damage within a structure, in order to undertake appropriate repairs as early as possible. The main issue of early warning infrastructure fault detection is that expensive in-situ distributed monitoring sensor networks has to be installed. This research propose a new global infrastructure monitoring paradigm using micro-motion (m-m) estimation of critical sites, from space borne Synthetic Aperture Radar (SAR) data, in this case. In order to apply this method for damage detection, an approach using modal proprieties is applied. m-m is processed to extract modal features such as natural frequencies and mode shapes. The case study of the Morandi bridge (Polcevera Viaduct) in Genoa (Italy) is considered in this paper and the proposed method shows abnormal vibrational modes during the period before the collapse of the bridge