scholarly journals EVALUATION OF A PSI-BASED CHANGE DETECTION REGARDING SIMULATION, COMPARISON, AND APPLICATION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1959-1965
Author(s):  
C. H. Yang ◽  
U. Soergel
Keyword(s):  
Change Detection ◽  
Ground Truth ◽  
Coherent Signals ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterer ◽  
Deformation Velocity ◽  
Potential Applications ◽  
Pros And Cons ◽  
Coherent Radar ◽  
Occurrence Times

<p><strong>Abstract.</strong> Persistent scatterer interferometry (PSI) detects and analyses strong, stable, and coherent radar signals throughout a time series of SAR images. Such coherent signals are reflected from corner-reflector-like substructures in built-up cities, which are regarded as so-called PS points. Certain PS properties such as deformation velocity and topography height can be derived for scene monitoring. Previously, we introduced a PSI-based change detection to detect disappearing and emerging PS points along with their occurrence times. Such temporary PS points existing only during a certain period correspond to change events, e.g., mostly constructions in cities. The tests using TerraSAR-X images successfully identified where and when the construction events in Berlin took place in 2013. The results were compared and all agreed with the ground truth. In this study, we evaluate our method more deeply. A simulation test is conducted to evaluate the theoretical accuracy in space and time. We also compare our method with two classical approaches: image rationing and amplitude-based semi-PS detection. The computational requirements are revealed afterwards. Finally, potential applications are proposed and discussed. All of these works help us to better characterize our technique and learn the pros and cons.</p>

scholarly journals CHANGE DETECTION BASED ON PERSISTENT SCATTERER INTERFEROMETRY – A NEW METHOD OF MONITORING BUILDING CHANGES

2016 ◽  
Vol III-7 ◽  
pp. 243-250
Author(s):  
C. H. Yang ◽  
B. K. Kenduiywo ◽  
U. Soergel
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Ground Truth ◽  
Google Earth ◽  
Aerial Images ◽  
Radar Signal ◽  
Persistent Scatterer Interferometry ◽  
Small Surface ◽  
Persistent Scatterer ◽  
Main Station

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

scholarly journals CHANGE DETECTION BASED ON PERSISTENT SCATTERER INTERFEROMETRY – A NEW METHOD OF MONITORING BUILDING CHANGES

2016 ◽  
Vol III-7 ◽  
pp. 243-250 ◽  
Author(s):  
C. H. Yang ◽  
B. K. Kenduiywo ◽  
U. Soergel
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Ground Truth ◽  
Google Earth ◽  
Aerial Images ◽  
Radar Signal ◽  
Persistent Scatterer Interferometry ◽  
Small Surface ◽  
Persistent Scatterer ◽  
Main Station

Persistent Scatterer Interferometry (PSI) is a technique to detect a network of extracted persistent scatterer (PS) points which feature temporal phase stability and strong radar signal throughout time-series of SAR images. The small surface deformations on such PS points are estimated. PSI particularly works well in monitoring human settlements because regular substructures of man-made objects give rise to large number of PS points. If such structures and/or substructures substantially alter or even vanish due to big change like construction, their PS points are discarded without additional explorations during standard PSI procedure. Such rejected points are called big change (BC) points. On the other hand, incoherent change detection (ICD) relies on local comparison of multi-temporal images (e.g. image difference, image ratio) to highlight scene modifications of larger size rather than detail level. However, image noise inevitably degrades ICD accuracy. We propose a change detection approach based on PSI to synergize benefits of PSI and ICD. PS points are extracted by PSI procedure. A local change index is introduced to quantify probability of a big change for each point. We propose an automatic thresholding method adopting change index to extract BC points along with a clue of the period they emerge. In the end, PS ad BC points are integrated into a change detection image. Our method is tested at a site located around north of Berlin main station where steady, demolished, and erected building substructures are successfully detected. The results are consistent with ground truth derived from time-series of aerial images provided by Google Earth. In addition, we apply our technique for traffic infrastructure, business district, and sports playground monitoring.

scholarly journals Monitoring of Building Construction by 4D Change Detection Using Multi-temporal SAR Images

2017 ◽  
Vol IV-1/W1 ◽  
pp. 35-42 ◽  
Author(s):  
C. H. Yang ◽  
Y. Pang ◽  
U. Soergel
Keyword(s):  
Change Detection ◽  
Ground Truth ◽  
Night Vision ◽  
City Management ◽  
Persistent Scatterer Interferometry ◽  
Spatiotemporal Resolution ◽  
Sar Images ◽  
Construction Monitoring ◽  
Radar Images ◽  
Multi Temporal

Monitoring urban changes is important for city management, urban planning, updating of cadastral map, etc. In contrast to conventional field surveys, which are usually expensive and slow, remote sensing techniques are fast and cost-effective alternatives. Spaceborne synthetic aperture radar (SAR) sensors provide radar images captured rapidly over vast areas at fine spatiotemporal resolution. In addition, the active microwave sensors are capable of day-and-night vision and independent of weather conditions. These advantages make multi-temporal SAR images suitable for scene monitoring. Persistent scatterer interferometry (PSI) detects and analyses PS points, which are characterized by strong, stable, and coherent radar signals throughout a SAR image sequence and can be regarded as substructures of buildings in built-up cities. Attributes of PS points, for example, deformation velocities, are derived and used for further analysis. Based on PSI, a 4D change detection technique has been developed to detect disappearance and emergence of PS points (3D) at specific times (1D). In this paper, we apply this 4D technique to the centre of Berlin, Germany, to investigate its feasibility and application for construction monitoring. The aims of the three case studies are to monitor construction progress, business districts, and single buildings, respectively. The disappearing and emerging substructures of the buildings are successfully recognized along with their occurrence times. The changed substructures are then clustered into single construction segments based on DBSCAN clustering and α-shape outlining for object-based analysis. Compared with the ground truth, these spatiotemporal results have proven able to provide more detailed information for construction monitoring.

scholarly journals Improving PSI Processing of Mining Induced Large Deformations with External Models

2020 ◽  
Vol 12 (19) ◽  
pp. 3145
Author(s):  
Sen Du ◽  
Jordi J. Mallorqui ◽  
Hongdong Fan ◽  
Meinan Zheng
Keyword(s):  
Ground Deformation ◽  
Ground Truth ◽  
Deformation Monitoring ◽  
Persistent Scatterer Interferometry ◽  
Mining Operations ◽  
Sar Images ◽  
Temporal Behaviour ◽  
Persistent Scatterer ◽  
Large Gradient ◽  
External Model

Ground subsidences, either caused by natural phenomena or human activities, can threaten the safety of nearby infrastructures and residents. Among the different causes, mining operations can trigger strong subsidence phenomena with a fast nonlinear temporal behaviour. Therefore, a reliable and precise deformation monitoring is of great significance for safe mining and protection of facilities located above or near the mined-out area. Persistent Scatterer Interferometry (PSI) is a technique that uses stacks Synthetic Aperture Radar (SAR) images to remotely monitor the ground deformation of large areas with a high degree of precision at a reasonable cost. Unfortunately, PSI presents limitations when monitoring large gradient deformations when there is phase ambiguity among adjacent Persistent Scatterer (PS) points. In this paper, an improvement of PSI processing, named as External Model-based Deformation Decomposition PSI (EMDD-PSI), is proposed to address this limitation by taking advantage of an external model. The proposed method first uses interferograms generated from SAR Single Look Complex (SLC) images to optimize the parameter adjustments of the external model. Then, the modelled spatial distribution of subsidence is utilized to reduce the fringes of the interferograms generated from the SAR images and to ease the PSI processing. Finally, the ground deformation is retrieved by jointly adding the external model and PSI results. In this paper, fourteen Radarsat-2 SAR images over Fengfeng mining area (China) are used to demonstrate the capabilities of the proposed method. The results are evaluated by comparing them with leveling data of the area covering the same temporal period. Results have shown that, after the optimization, the model is able to mimic the real deformation and the fringes of the interferograms can be effectively reduced. As a consequence, the large gradient deformation then can be better retrieved with the preservation of the nonlinear subsidence term. The ground truth shows that, comparing with the classical PSI and PSI with unadjusted parameters, the proposed scheme reduces the error by 35.2% and 20.4%, respectively.

scholarly journals Monitoring and Mapping of Shallow Landslides in a Tropical Environment Using Persistent Scatterer Interferometry: A Case Study from the Western Ghats, India

Geomatics ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 3-17
Author(s):  
Ambujendran Rajaneesh ◽  
Natarajan Logesh ◽  
Chakrapani Lekha Vishnu ◽  
El Hachemi Bouali ◽  
Thomas Oommen ◽  
...  
Keyword(s):  
Western Ghats ◽  
Regional Scale ◽  
Mitigation Measures ◽  
False Alarms ◽  
Persistent Scatterer Interferometry ◽  
Tropical Regions ◽  
Persistent Scatterer ◽  
Western Ghats Of India ◽  
Deformation Velocity ◽  
The Western Ghats

Persistent Scatterer Interferometry (PSI) techniques are now well established and accepted for monitoring ground displacements. The presence of shallow-seated landslides, ubiquitous phenomena in the tropics, offers an opportunity to monitor and map these hazards using PSI at the regional scale. Thus, the Western Ghats of India, experiencing a tropical climate and in a topographically complex region of the world, provides an ideal study site to test the efficacy of landslide detection with PSI. The biggest challenge in using the PSI technique in tropical regions is the additional noise in data due to vegetation. In this study, we filtered these noises by utilizing the 95-percentile of the highest coherence data, which also reduced the redundancy of the PSI points. The study examined 12 landslides that occurred within one of the three temporal categories grouped as Group 1, Group 2, and Group 3, categorized in relation to PSI monitoring periods, which was also further classified into east- and west-facing landslides. The Synthetic Aperture Radar (SAR) data is in descending mode, and, therefore, the east-facing landslides are characterized by positive deformation velocity values, whereas the west-facing landslides have negative deformation values. Further, the landslide-prone areas, delineated using the conventional factor of safety (FS), were refined and mapped using PSI velocity values. The combination of PSI with the conventional FS approach helped to identify exclusive zones prone to landslides. The main aim of such an attempt is to identify critical areas in the unstable category in the map prepared using FS and prioritizing the mitigation measures, and to develop a road map for any developmental activities. The approach also helps to increase confidence in the susceptibility mapping and reduce false alarms.

scholarly journals EXTRACTING AND EVALUATING CLUSTERS IN DINSAR DEFORMATION DATA ON SINGLE BUILDINGS

2020 ◽  
Vol V-3-2020 ◽  
pp. 157-163
Author(s):  
P. J. Schneider ◽  
R. Khamis ◽  
U. Soergel
Keyword(s):  
Ground Truth ◽  
Deformation Space ◽  
Powerful Method ◽  
Persistent Scatterer Interferometry ◽  
Ground Truth Data ◽  
Precise Levelling ◽  
The Past ◽  
Persistent Scatterer ◽  
Displacement Patterns ◽  
Insight Into

Abstract. In the past two decades persistent scatterer interferometry (PSI) has become a well understood and powerful method to monitor the deformations of man-made structures. PSI can derive displacement histories of thousands of scattered points on a single building with accuracy of a few millimetre per year, by analysing space-borne SAR data. In this paper, we present a method to cluster PS points on a single building into segments which show the same deformation behavior. The spatial distribution of those clusters gives an insight into the structural behavior of a building. We use dimensionality reduction to visualize the clusters in the deformation space. The comparison of our extracted displacement patterns with ground truth data from precise levelling and 3D tachymetry confirms the plausibility of our remote sensing method.

Deformation Monitoring of Offshore Platform Using the Persistent Scatterer Interferometry Technique

2014 ◽  
Vol 567 ◽  
pp. 325-330 ◽  
Author(s):  
Abdul Nasir Matori ◽  
Amir Sharifuddin Ab Latip ◽  
Indra Sati Hamonangan Harahap ◽  
Daniele Perissin
Keyword(s):  
Structural Integrity ◽  
Oil And Gas ◽  
Deformation Monitoring ◽  
Offshore Platform ◽  
Offshore Platforms ◽  
Persistent Scatterer Interferometry ◽  
Reservoir Compaction ◽  
Persistent Scatterer ◽  
Deformation Velocity ◽  
Global Positioning

One of the problems that occur during the exploitation of oil and gas is offshore platform deformation. It could occur due to the environments load as well as the extraction of oil and gas itself under the seabed that caused reservoir compaction. Offshore platform deformation may affect the platform structural integrity and cause loss of production, thus it is very important to monitor its occurrences. Offshore platform deformation monitoring has been carried out using the satellite-based Global Positioning System (GPS) technique until recently. Even though the technique has proven its worth for the job, it has however some limitations, the most prominent is it could only monitor selected portion of the offshore platform. Thus, this study presents an attempt of detecting and monitoring the deformation phenomenon of an offshore platform using the Persistent Scatterer Interferometry (PSI) technique. This technique would overcome some of the limitations of the previous (GPS) deformation monitoring technique. A total of 11 high resolution TerraSAR-X images (i.e., 3 m in StripMap mode) were acquired from Aug, 2012 to Apr, 2013 for this purpose, while one of the offshore platforms in South China Sea is being used as monitored platform. Preliminary results showed that detail and sensitive deformations could be detected by this technique. In addition, analysis results in the form of mean deformation velocity map and displacement time series would allow us to further understand the behaviour of offshore platform deformation.

scholarly journals Deformation Monitoring Using Sentinel-1 SAR Data

Proceedings ◽  
2018 ◽  
Vol 2 (7) ◽  
pp. 344 ◽  
Author(s):  
Núria Devanthéry ◽  
Michele Crosetto ◽  
Oriol Monserrat ◽  
María Cuevas-González ◽  
Bruno Crippa
Keyword(s):  
Earth Observation ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Persistent Scatterer Interferometry ◽  
Sar Images ◽  
Persistent Scatterer ◽  
Deformation Velocity ◽  
Different Types ◽  
Processing Steps ◽  
Deformation Measurements

Satellite earth observation enables the monitoring of different types of natural hazards, contributing to the mitigation of their fatal consequences. In this paper, satellite Synthetic Aperture Radar (SAR) images are used to derive terrain deformation measurements. The images acquired with the ESA satellites Sentinel-1 are used. In order to fully exploit these images, two different approaches to Persistent Scatterer Interferometry (PSI) are used, depending on the characteristics of the study area and the available images. The main processing steps of the two methods, i.e.; the simplified and the full PSI approach, are described and applied over an area of 7500 km2 located in Catalonia (Spain). The deformation velocity map and deformation time series are analysed in the last section of the paper.

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