Persistent Scatterer Interferometry Technique Research Articles

MONITORING OF ARTIFICIAL RESERVOIR INDUCED LANDSLIDES FROM SPACE: A CASE STUDY OF FROM INDIA

Abstract. Monitoring Reservoir-induced landslides is critical for determining and mitigating the geo-environmental risks associated with the artificial reservoir. This paper employs Persistent Scatterer Interferometry (PSI) technique for the mapping and monitoring of Reservoir Induced Landslides in the rim area of Baglihar Dam Reservoir on Chenab river (Jammu and Kashmir, India) along National Highway NH-244. It has been evident that the slope movements are necessarily impacted by the reservoir drawdown effect (RDE) as well as the rainfall. We have utilised 46 Sentinel-1A C-band radar satellite imagery of the study area. The monitoring results have yielded the Line of Sight slope movement along the reservoir rim varies from −97 mm/year to +80 mm/year. The temporal correlation between the displacements and the local precipitation (derived from TRMM using Google Earth Engine) was qualitatively analysed. Two unstable slopes have been identified and monitored.

INSAR DEFORMATION TIME SERIES CLASSIFICATION USING A CONVOLUTIONAL NEURAL NETWORK

Abstract. Temporal analysis of deformations Time Series (TS) provides detailed information of various natural and humanmade displacements. Interferometric Synthetic Aperture Radar (InSAR) generates millimetre-scale products, indicating the chronicle behaviour of detected targets via TS products. Deep Learning (DL) can handle a massive load of InSAR TS to categorize significant movements from non-moving targets. To this end, we employed a supervised Convolutional Neural Network (CNN) model to distinguish five deformations trends, including Stable, Linear, Quadratic, Bilinear, and Phase Unwrapping Error (PUE). Considering several arguments in a CNN model, we trained numerous combinations to explore the most accurate combination from 5000 samples extracted from a Persistent Scatterer Interferometry (PSI) technique and Sentinel-1 images over the Granada region, Spain. The model overall accuracy exceeds 92%. Deformations of three cases of landslides were also detected over the same area, including the Cortijo de Lorenzo, El Arrecife, and Rules Viaduct areas.

INTERFEROMETRIC SAR DEFORMATION MONITORING USING PASSIVE REFLECTORS AND ASCENDING AND DESCENDING PASSES

Abstract. The article concerns the estimation of land deformation in an area of copper mining using the Persistent Scatterer Interferometry (PSI) technique and C-band data coming from the Sentinel-1 satellite. The aim of the work is a comparison of two different PSI approaches exploiting passive corner reflectors deployed pairwise, oriented towards the satellites in ascending and descending orbits. The comparison was done in the line of sight geometry. In addition, a validation was carried out using GNSS measurements. The results achieved using the two PSI approaches are consistent and mutually coherent. They are also congruent with observations from GNSS stations. These results proves that the method proposed to identify pixels on multi-looked images is correct. In addition, the intermediary results on the corner reflectors shows that their responses, in terms of dispersion of amplitude and the coherence, is slightly different. This needs to be further studied.

INFRASTRUCTURE MONITORING USING THE INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) TECHNIQUE

Abstract. This paper focuses on the application of spaceborne radar interferometry as a tool for assisting the monitoring different types of infrastructures, including railways and highways. The Persistent Scatterer Interferometry (PSI) technique, the most advanced class of differential interferometric Synthetic Aperture Radar techniques (DInSAR), is used to generate the deformation maps, including the time series and the displacement velocity for each measured persistent scatterers. The dataset considered in this work consists of 261 SAR IW-SLC images acquired by the Sentinel-1 A/B satellites, between January 2016 and September 2021, over the metropolitan area of Barcelona. The infrastructures, especially railways and highways, not only cross the cities, but also connect them crossing non-urban areas. One main technical issue of monitoring infrastructures is the low density of persistent scatterers (PS) in rural areas. To improve the density, the processing chain combines the interferograms selection based on the coherence threshold. Also, for a better point selection, the Equivalent Spatial Coherence (Omega Factor) is tested.

Monitoring of Maskun landslide and determining its quantitative relationship to different climatic conditions using D-InSAR and PSI techniques

Climate change has resulted in severe landslides in Maskun, Iran. This study evaluates and monitors the displacement caused by the landslide mass in Bam using Interferometry Synthetic Aperture Radar (DInSAR) and Persistent Scatterer Interferometry (PSI) techniques, as well as identifies relationships between climatic conditions and mass displacement. Temperature and precipitation data from 2007 to 2019 were combined with satellite images and the DInSAR method was used to determine the mass displacement differences after selecting eighteen radar images from the ASAR sensor of the ENVISAT satellite. Additionally, Sentinel 1 satellite images were acquired and analyzed using the PSI method from November 5, 2014, to June 24, 2019. The highest displacement level at the surface of the Maskun landslide mass was then extracted. The ASAR images show a monthly displacement rate of 7.3 mm. The smallest displacement, on the other hand, occurred between May and September 2009, at a rate of 3.1 mm/month. PSI results also revealed that the maximum Line Of Sight (LOS) velocities detected by PSI are −64.5 mm/yr (away from the satellite) and 32.45 mm/yr (toward the satellite). Rainfall is one of the main triggers for increasing the deformation of the Maskun landslide according to the time-series analysis.

Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique.

Landslides are the most catastrophic geological hazard in hilly areas. The present work intends to identify landslide susceptibility along Karakorum Highway (KKH) in Northern Pakistan, using landslide susceptibility mapping (LSM). To compare and predict the connection between causative factors and landslides, the random forest (RF), extreme gradient boosting (XGBoost), k nearest neighbor (KNN) and naive Bayes (NB) models were used in this research. Interferometric synthetic aperture radar persistent scatterer interferometry (PS-InSAR) technology was used to explore the displacement movement of retrieved models. Initially, 332 landslide areas alongside the Karakorum Highway were found to generate the landslide inventory map using various data. The landslides were categorized into two sections for validation and training, of 30% and 70%. For susceptibility mapping, thirteen landslide-condition factors were created. The area under curve (AUC) of the receiver operating characteristic (ROC) curve technique was utilized for accuracy comparison, yielding 83.08, 82.15, 80.31, and 72.92% accuracy for RF, XGBoost, KNN, and NB, respectively. The PS-InSAR technique demonstrated a high deformation velocity along the line of sight (LOS) in model-sensitive areas. The PS-InSAR technique was used to evaluate the slope deformation velocity, which can be used to improve the LSM for the research region. The RF technique yielded superior findings, integrating with the PS-InSAR outcomes to provide the region with a new landslide susceptibility map. The enhanced model will help mitigate landslide catastrophes, and the outcomes may help ensure the roadway’s safe functioning in the study region.

Multi-temporal analysis of groundwater depletion-induced land subsidence in Central Ganga Alluvial plain, Northern India

This study explores the Persistent Scatterer Interferometry technique to identify the developing pattern of groundwater depletion-induced land subsidence in Lucknow, northern India. The results show the development of two significant subsidence zones, one each in the north and south of Lucknow. The situation is potentially alarming as ∼9.3% (∼27.6 km2) of the total area is under the expression of a weak degree of subsidence (∼10–40 mm/yr). The detected displacement trends substantially correspond to the constant dwindling of groundwater levels in the city, further indicating that the first unconfined aquifer is under high stress and faces a continuous storage capacity loss with time. The time-series displacement trends have been later forecasted using the Autoregressive Integrated Moving Average method, indicating the city might face subsidence at the rate of ∼25–40 mm/yr. The findings of this study are significant to take precise mitigation measures in the areas facing continuous groundwater depletion on a long-term basis.

Monitoring of Radial Deformations of a Gravity Dam Using Sentinel-1 Persistent Scatterer Interferometry

Dams have many important socio-economic functions, fulfilling roles ranging from storing water to power generation, but also serving as leisure areas. Monitoring of their deformation is usually performed using time-consuming traditional terr estrial techniques, leading to a yearly monitoring cycle. To increase the monitoring cycle, new methods are needed. Persistent Scatterer Interferometry (PSI) is a well-established technique for monitoring millimeter deformation of the Earth’s surface. The availability of free and open SAR data with a repeat cycle of 6 to 12 days from the Copernicus mission Sentinel-1, allows PSI to be used complementary to traditional surveying techniques. This present study investigates deformation dynamics at the Moehne gravity dam in North Rhine-Westphalia, Germany. The applicability of the PSI technique to the deformation monitoring of dams is evaluated, in relation to the necessary accuracy requirements. For this purpose, Sentinel-1 data from January 2015 to November 2020 are analyzed and the deformation estimates are assessed with in situ information. Using a precise dam model, the radial deformation of the dam could be extracted and compared to trigonometric and plumb measurements. The first results show that the movements of the Moehne dam follow a seasonal pattern, reaching a maximum radial deformation of up to 4 mm in Spring, following a decline to −4 mm in the late summer. RMSE between 1.1 mm and 1.5 mm were observed between the PSI observations and the in situ data, showing that the PSI technique achieves the necessary accuracy requirements for gravity dam monitoring from space.

Monitoring glacial lake outburst flood susceptibility using Sentinel-1 SAR data, Google Earth Engine, and persistent scatterer interferometry

Continuous monitoring of glacial lakes, their parent glaciers and their surroundings is crucial because possible outbursts of these lakes pose a serious hazard to downstream areas. Ongoing climate change increases the risk of this hazard globally due to recession of glaciers leading to formation and expansion of glacial lakes, and permafrost degradation which impacts the stability of glaciers, slopes and moraines. Here, we demonstrate the capability of our approach for monitoring lake outburst susceptibility using time-series of Sentinel-1 Synthetic Aperture Radar (S-1 SAR) data. We selected Lunana in the Bhutanese Himalayas as an example region as it is highly susceptible to glacial lake outburst floods and suitable baseline data were available. We used Google Earth Engine (GEE) to calculate average radar backscatter intensity (ARBI) of glaciers, lakes, basins, and moraines. To determine the periodicity of the highest and the lowest radar backscatter intensity, we denoised the ARBI data using a Fast Fourier Transform and autocorrelated using a Pearson correlation function. Additionally, we determined glacier melt area, basin melt area, lake area, open water area, and lake ice area using radar backscatter intensity data. The Persistent Scatterer Interferometry (PSI) technique was used to investigate the stability of moraines and slopes around glacial lakes. The PSI results were qualitatively validated by comparison with high-resolution digital elevation model differencing results. Our approach showed that glaciers and basins in the region underwent seasonal and periodic changes in their radar backscatter intensity related to changes in ice and snow melt. Lakes also showed seasonal changes in their radar backscatter intensity related to the variation of lake ice and open water area, but the radar backscatter intensity change was not periodic. We could also infer lake area change using a time-series radar backscatter intensity data such as the rapid expansion of Bechung Tsho. The PSI analysis showed that all the terminal moraines were stable except Drukchung Tsho. Its terminal moraine showed subsidence at the rate of –5.18 mm/yr. Sidewalls of lakes were also stable with the exception of Lugge Tsho at site 4. Due to the free availability of S-1 SAR data, the efficiency of processing a large amount of imagery within GEE, and the PSI technique, we were able to understand the outburst susceptibility of glacial lakes in the region at great detail. The regular acquisition of S-1 SAR data enables continuous monitoring of glacial lakes. A similar approach and concept can be transferred to any geographic region on earth that shares similar challenges in glacial lake monitoring.

Classification of ground deformation using sentinel-1 persistent scatterer interferometry time series

ABSTRACT Displacement time series (TS) provides temporal and spatial information related to ground deformation. This study aims to investigate temporal behavior of ground deformation TS, including classification of displacement trends and periodicity evaluation, which ease the interpretation of movements. To this end, we propose several modifications to an existing automatic classification workflow of Persistent Scatterers Interferometry (PSI) TS using new tests to classify ground deformations into seven main trends: Stable, Linear, Quadratic, Bilinear, Phase Unwrapping Errors (PUE), Discontinuous with constant and different velocities. We illustrate our approach over 1500 km2 of the Granada region and the metropolitan area of Barcelona, which were monitored using Sentinel-1 images and a PSI technique. This study provided the spatial distribution of different ground movement types and was useful to detect several TS anomalies due to PUE. The proposed approach also identified stable targets, which were wrongly classified as moving scatterers by the existing classification method. A periodicity analysis was finally performed using the Welch’s power spectral density estimator to investigate seasonal and yearly fluctuations. The method was validated using simulated data, where the classified TSs characterized by probable phase unwrapping errors were verified by PSI experts. The overall classification accuracy was 77.8%, indicating that the proposed method has a considerable TS classification potential.

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

Abstract. 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.

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.

Ground Movement Classification Using Statistical Tests Over Persistent Scatterer Interferometry Time Series

This study proposes modifications to an existing automatic classification method of Persistent Scatterers Interferometry (PSI) time series (TS) and a new procedure to classify ground movements into seven classes. We also represent a technique to detect TSs affected by phase unwrapping errors and a reclassification part to detect stable points, which are incorrectly classified as moving points using the original method. Around 60 km2 of Catalunya were classified using Sentinel-1 images and a PSI technique. The proposed method classified 78359 PS TS. This study provided the spatial distribution of ground movement classes and detected several time series anomalies.

Wide-area ground deformation monitoring in geothermal fields in western Turkey

The large-scale production and injection of geothermal fluids induce pressure, volume, and temperature gradient changes in the subsurface, which may result in surface deformation as well. Interferometric synthetic aperture radar (InSAR) is a promising utility for monitoring ground surface deformation and inferring subsurface reservoir operations that are difficult to observe directly. This study provides the first wide-area InSAR-derived long-term ground deformation across major geothermal fields in western Turkey. It aims to identify ground deformation hotspots within the geothermal exploitation sites and analyze their relationship with energy production and pumping. In the present study, the whole 2014?2020 Sentinel 1-A and 1-B SAR archive available over the region along ascending and descending orbits was processed using the persistent scatterer interferometry (PS-InSAR) technique. Compaction and land subsidence hot spots caused by fluid withdrawal are found within the geothermal fields. The results indicate that the observed systematic surface subsidence deformation result from the increase of geothermal production during the observation period in western Turkey. The realtime power data of geothermal plants retrieved from the transparency platform of the Turkish energy exchange are related to surface deformation. We estimated the drainage area of the production wells using subsidence deformation, caused by pore pressure decline in the reservoir. The results provide supporting evidence for the systematic monitoring and identification of deformation patterns in spatial-temporal extend can reveal reservoir dynamics and compartments, which are crucial for reservoir characterization and field development plan.

Wide-area ground deformation monitoring in geothermal fields in western Turkey

The large-scale production and injection of geothermal fluids induce pressure, volume, and temperature gradient changes in the subsurface, which may result in surface deformation as well. Interferometric synthetic aperture radar (InSAR) is a promising utility for monitoring ground surface deformation and inferring subsurface reservoir operations that are difficult to observe directly. This study provides the first wide-area InSAR-derived long-term ground deformation across major geothermal fields in western Turkey. It aims to identify ground deformation hotspots within the geothermal exploitation sites and analyze their relationship with energy production and pumping. In the present study, the whole 2014?2020 Sentinel 1-A and 1-B SAR archive available over the region along ascending and descending orbits was processed using the persistent scatterer interferometry (PS-InSAR) technique. Compaction and land subsidence hot spots caused by fluid withdrawal are found within the geothermal fields. The results indicate that the observed systematic surface subsidence deformation result from the increase of geothermal production during the observation period in western Turkey. The realtime power data of geothermal plants retrieved from the transparency platform of the Turkish energy exchange are related to surface deformation. We estimated the drainage area of the production wells using subsidence deformation, caused by pore pressure decline in the reservoir. The results provide supporting evidence for the systematic monitoring and identification of deformation patterns in spatial-temporal extend can reveal reservoir dynamics and compartments, which are crucial for reservoir characterization and field development plan.

Detection of sinkhole activity in West-Central Florida using InSAR time series observations

Sinkhole activity in Florida is a major hazard for people and property. Its increasing frequency is often related to an accelerated use of ground-water and land resources in the region. In this work, we use a combined approach of radar interferometry and spatial clustering analysis over three selected sites in West-Central Florida to identify localized deformation that may be caused by sinkhole activity. The region of West-Central Florida is a densely active sinkhole region, where sinkholes tend to be small and land cover is mixed resulting in variable interferometric coherence that complicates Interferometric Synthetic Aperture Radar (InSAR) surveys. In this work, we present a combined methodology implementing InSAR and a Density-Based Spatial Clustering Analysis (DBSCAN) algorithm to detect unknown sinkhole activity and to alert to possible precursors of sinkhole collapse. The data used for the study consist of acquisitions from three TerraSAR-X frames covering time spans of ~1.7 and 2.5 years with spatial resolutions ranging from 25 cm up to 1 m. We applied the Persistent Scatterer Interferometry (PSI) technique using the Stanford Method for Persistent Scatterers (StaMPS) and confirmed the observed deformation signals by also processing the data using the SAR PROcessing tool (SARPROZ). Results show several areas of localized subsidence, from which the cluster with highest rates for each site was selected for detailed inspection. Locations of selected clusters were found in buildings with sizes ranging from 300 m2 to nearly 2000 m2, with subsidence trends ranging from −3 to −6 mm/yr. Results were compared with in-situ observations such as ground penetrating radar (GPR), electrical resistivity tomography (ERT) surveys, visual structural inspection and public county archive documents to help as ground truthing; subsiding locations were found to be related to sinkhole presence or development.

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.

PSI and GNSS derived ground subsidence detection in the UNESCO Heritage City of Ahmedabad, Western India

Presently, ground subsidence in urban areas is becoming a peril to the infrastructure and society. In this study, we conducted a detailed analysis of the results, based on the Persistent Scatterer Interferometry (PSI), Global Navigation Satellite System (GNSS) and groundwater in the ‘World Heritage City’ of Ahmedabad, a major metro city in western India. The PSI technique is applied to measure the ground subsidence using the Sentinel 1 A dataset for the period 2017 to 2020. The results reveal a subsidence, maximum up to the level of 25 mm/yr in the areas of the southeast and west parts of the city. Analysis derived from GNSS results indicates a significant amount of ground subsidence based on the 2009–2020 dataset. Groundwater data (1995–2019) were analyzed to identify factors likely to cause ground subsidence and the results are in close agreement with the PSI and GNSS results.

Monitoring of small-scale deformation at sea-filled Ordu-Giresun Airport, Turkey from multi-temporal SAR data

Today, many countries cannot meet the land demands brought about by rapid urbanization. Especially for coastal cities, this problem is even greater when the topography does not allow it, and filling projects are produced in order to eliminate the problem. Artificial areas built on the sea with filling have a sensitive and geologically active structure. This situation may cause negative effects, especially where the density of the population is high. Management of operational safety is very important in terms of public safety in buildings built on this type of filling. The airport surface should be monitored at regional scales in order to establish this security continuously. In this study, the surface deformation that occurred at Ordu-Giresun Airport, which was founded on the sea-filled area in 2011 and has been operating since 2015, was determined. The airport is the first one that was built on sea-filled land in Turkey and Europe. For the analysis, Sentinel-1 Synthetic Aperture Radar (SAR) images spans between 2015 and 2020 are used with Persistent Scatterer Interferometry (PSI) technique. The results showed that maximum deformation determined at the breakwater and nearby taxiway. The half of the runway also indicated high rates of deformation, whereas the apron and the terminal indicated almost stable behavior.