scholarly journals RESEARCH ON METHODS OF HIGH COHERENT TARGET EXTRACTION IN URBAN AREA BASED ON PSINSAR TECHNOLOGY

2018 ◽  
Vol XLII-3 ◽  
pp. 901-908 ◽  
Author(s):  
N. Li ◽  
J. Wu
Keyword(s):  
Urban Area ◽  
Ground Deformation ◽  
Extraction Methods ◽  
Deformation Monitoring ◽  
New Method ◽  
Ground Subsidence ◽  
Threshold Method ◽  
High Quality ◽  
Accurate Identification ◽  
Persistent Scatterers

PSInSAR technology has been widely applied in ground deformation monitoring. Accurate identification of Persistent Scatterers (PS) is key to the success of PSInSAR data processing. In this paper, the theoretic models and specific algorithms of PS point extraction methods are summarized and the characteristics and applicable conditions of each method, such as Coherence Coefficient Threshold method, Amplitude Threshold method, Dispersion of Amplitude method, Dispersion of Intensity method, are analyzed. Based on the merits and demerits of different methods, an improved method for PS point extraction in urban area is proposed, that uses simultaneously backscattering characteristic, amplitude and phase stability to find PS point in all pixels. Shanghai city is chosen as an example area for checking the improvements of the new method. The results show that the PS points extracted by the new method have high quality, high stability and meet the strong scattering characteristics. Based on these high quality PS points, the deformation rate along the line-of-sight (LOS) in the central urban area of Shanghai is obtained by using 35 COSMO-SkyMed X-band SAR images acquired from 2008 to 2010 and it varies from −14.6 mm/year to 4.9 mm/year. There is a large sedimentation funnel in the cross boundary of Hongkou and Yangpu district with a maximum sedimentation rate of more than 14 mm per year. The obtained ground subsidence rates are also compared with the result of spirit leveling and show good consistent. Our new method for PS point extraction is more reasonable, and can improve the accuracy of the obtained deformation results.

scholarly journals Surface Deformation Monitoring in Zhengzhou City from 2014 to 2016 Using Time-Series InSAR

2018 ◽  
Vol 10 (11) ◽  
pp. 1731 ◽  
Author(s):  
Zhengjia Zhang ◽  
Chao Wang ◽  
Mengmeng Wang ◽  
Ziwei Wang ◽  
Hong Zhang
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Urban Expansion ◽  
Correction Method ◽  
Deformation Monitoring ◽  
Ground Subsidence ◽  
Significant Information ◽  
Persistent Scatterers ◽  
Deformation Parameters

In recent years, with the development of urban expansion in Zhengzhou city, the underground resources, such as underground water and coal mining, have been exploited greatly, which have resulted in ground subsidence and several environmental issues. In order to study the spatial distribution and temporal changes of ground subsidence of Zhengzhou city, the Interferometric Synthetic Aperture Radar (InSAR) time series analysis technique combining persistent scatterers (PSs) and distributed scatterers (DSs) was proposed and applied. In particular, the orbit and topographic related atmospheric phase errors have been corrected by a phase ramp correction method. Furthermore, the deformation parameters of PSs and DSs are retrieved based on a layered strategy. The deformation and DEM error of PSs are first estimated using conventional PSI method. Then the deformation parameters of DSs are retrieved using an adaptive searching window based on the initial results of PSs. Experimental results show that ground deformation of the study area could be retrieved by the proposed method and the ground deformation is widespread and unevenly distributed with large differences. The deformation rate ranges from −55 to 10 mm/year, and the standard deviation of the results is about 8 mm/year. The observed InSAR results reveal that most of the subsidence areas are in the north and northeast of Zhengzhou city. Furthermore, it is found that the possible factors resulting in the ground subsidence include sediment consolidation, water exploitation, and urban expansion. The result could provide significant information to serve the land subsidence mitigation in Zhengzhou city.

scholarly journals Subsidence Monitoring of Fill Area in Yan’an New District Based on Sentinel-1A Time Series Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 3044
Author(s):  
Mingjie Liao ◽  
Rui Zhang ◽  
Jichao Lv ◽  
Bin Yu ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Ground Deformation ◽  
Dynamic Change ◽  
Deformation Monitoring ◽  
Chinese Loess Plateau ◽  
Ground Subsidence ◽  
Shanxi Province ◽  
Environment Change ◽  
Loess Area

In recent years, many cities in the Chinese loess plateau (especially in Shanxi province) have encountered ground subsidence problems due to the construction of underground projects and the exploitation of underground resources. With the completion of the world’s largest geotechnical project, called “mountain excavation and city construction,” in a collapsible loess area, the Yan’an city also appeared to have uneven ground subsidence. To obtain the spatial distribution characteristics and the time-series evolution trend of the subsidence, we selected Yan’an New District (YAND) as the specific study area and presented an improved time-series InSAR (TS-InSAR) method for experimental research. Based on 89 Sentinel-1A images collected between December 2017 to December 2020, we conducted comprehensive research and analysis on the spatial and temporal evolution of surface subsidence in YAND. The monitoring results showed that the YAND is relatively stable in general, with deformation rates mainly in the range of −10 to 10 mm/yr. However, three significant subsidence funnels existed in the fill area, with a maximum subsidence rate of 100 mm/yr. From 2017 to 2020, the subsidence funnels enlarged, and their subsidence rates accelerated. Further analysis proved that the main factors induced the severe ground subsidence in the study area, including the compressibility and collapsibility of loess, rapid urban construction, geological environment change, traffic circulation load, and dynamic change of groundwater. The experimental results indicated that the improved TS-InSAR method is adaptive to monitoring uneven subsidence of deep loess area. Moreover, related data and information would provide reference to the large-scale ground deformation monitoring and in similar loess areas.

scholarly journals Copernicus Sentinel-1 MT-InSAR, GNSS and Seismic Monitoring of Deformation Patterns and Trends at the Methana Volcano, Greece

2020 ◽  
Vol 10 (18) ◽  
pp. 6445 ◽  
Author(s):  
Theodoros Gatsios ◽  
Francesca Cigna ◽  
Deodato Tapete ◽  
Vassilis Sakkas ◽  
Kyriaki Pavlou ◽  
...  
Keyword(s):  
Land Surface ◽  
Surface Deformation ◽  
Ground Deformation ◽  
Local Population ◽  
Seasonal Fluctuation ◽  
Satellite System ◽  
Deformation Monitoring ◽  
Persistent Scatterers ◽  
Geothermal Activity ◽  
Global Navigation Satellite

The Methana volcano in Greece belongs to the western part of the Hellenic Volcanic Arc, where the African and Eurasian tectonic plates converge at a rate of approximately 3 cm/year. While volcanic hazard in Methana is considered low, the neotectonic basin constituting the Saronic Gulf area is seismically active and there is evidence of local geothermal activity. Monitoring is therefore crucial to characterize any activity at the volcano that could impact the local population. This study aims to detect surface deformation in the whole Methana peninsula based on a long stack of 99 Sentinel-1 C-band Synthetic Aperture Radar (SAR) images in interferometric wide swath mode acquired in March 2015–August 2019. A Multi-Temporal Interferometric SAR (MT-InSAR) processing approach is exploited using the Interferometric Point Target Analysis (IPTA) method, involving the extraction of a network of targets including both Persistent Scatterers (PS) and Distributed Scatterers (DS) to augment the monitoring capability across the varied land cover of the peninsula. Satellite geodetic data from 2006–2019 Global Positioning System (GPS) benchmark surveying are used to calibrate and validate the MT-InSAR results. Deformation monitoring records from permanent Global Navigation Satellite System (GNSS) stations, two of which were installed within the peninsula in 2004 (METH) and 2019 (MTNA), are also exploited for interpretation of the regional deformation scenario. Geological, topographic, and 2006–2019 seismological data enable better understanding of the ground deformation observed. Line-of-sight displacement velocities of the over 4700 PS and 6200 DS within the peninsula are from −18.1 to +7.5 mm/year. The MT-InSAR data suggest a complex displacement pattern across the volcano edifice, including local-scale land surface processes. In Methana town, ground stability is found on volcanoclasts and limestone for the majority of the urban area footprint while some deformation is observed in the suburban zones. At the Mavri Petra andesitic dome, time series of the exceptionally dense PS/DS network across blocks of agglomerate and cinder reveal seasonal fluctuation (5 mm amplitude) overlapping the long-term stable trend. Given the steepness of the slopes along the eastern flank of the volcano, displacement patterns may indicate mass movements. The GNSS, seismological and MT-InSAR analyses lead to a first account of deformation processes and their temporal evolution over the last years for Methana, thus providing initial information to feed into the volcano baseline hazard assessment and monitoring system.

scholarly journals Nationwide urban ground deformation monitoring in Japan using Sentinel-1 LiCSAR products and LiCSBAS

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yu Morishita
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Urban Areas ◽  
Ground Deformation ◽  
Processing System ◽  
Economic Loss ◽  
Deformation Monitoring ◽  
Ground Subsidence ◽  
Detection Mechanism ◽  
Series Analysis

AbstractGround subsidence in urban areas is a significant problem because it increases flood risk, damages buildings and infrastructure, and results in economic loss. Continual monitoring of ground deformation is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. The Sentinel-1 satellite constellation has globally and freely provided frequent and abundant SAR data and enabled nationwide deformation monitoring through InSAR time series analysis. LiCSAR, an automatic Sentinel-1 interferometric processing system, has produced abundant interferograms with global coverage, and the products are freely accessible and downloadable through a web portal. LiCSBAS, an open source InSAR time series analysis package integrated with LiCSAR, enables users to obtain the deformation time series easily and quickly. In this study, spatially and temporally detailed deformation time series and velocities from the LiCSAR products using LiCSBAS for 73 major urban areas in Japan during 2014–2020 were derived. All LiCSBAS processing was automatically performed using predefined parameters. Many deformation signals with various temporal and spatial features, such as linear subsidence in Hirosaki, Kujyukuri, Niigata, and Kanazawa, episodic subsidence in Sanjo, annual vertical fluctuation in Hirosaki, Yamagata, Yonezawa, Ojiya, and Nogi, and linear uplift in Chofu were detected. Unknown small nonlinear uplift signals were found in Nara and Osaka in 2018. Complex postseismic deformations from the 2016 Kumamoto earthquake were also revealed. All the deformation data obtained in this study are available on an open repository and are expected to be used for further research, investigation, or interpretation. This nationwide monitoring approach using the LiCSAR products and LiCSBAS is easy to implement and applicable to other areas worldwide.

scholarly journals Long-Term Ground Settlements over Mined-Out Region Induced by Railway Construction and Operation

2019 ◽  
Vol 11 (3) ◽  
pp. 875
Author(s):  
Shuo Jiang ◽  
Yimin Wang
Keyword(s):  
Ground Deformation ◽  
Lateral Displacement ◽  
Rapid Development ◽  
Deformation Monitoring ◽  
Ground Subsidence ◽  
Ground Settlement ◽  
Railway Construction ◽  
Train Operation ◽  
Ground Settlements

With the rapid development of railway construction and the massive exploitation of mineral resources, many railway projects have had to cross mining areas and their caverns. However, the settlement of the ground surface may cause severe damage to human-built structures and lead to the loss of human lives. The research on ground deformation monitoring over caverns is undoubtedly important and has a guiding role in railway design. Settlement observation points were set up around the mine, establishing a ground subsidence monitoring level network that has been in operation for 11 years. The ground settlement and lateral displacement along the designed railway were studied. A finite element model was established to predict the long-term ground settlements over the mined-out region induced by designed railway embankment construction and train operation. The results show that the predicted ground settlement induced by railway embankment construction is smaller than the ground settlement induced by the mined-out cavity. One train pass-by has an insignificant impact on the safety of train operation. However, when the number of train pass-bys increases to 10,000,000 times and 20,000,000 times, the cumulative deformations of the ground at different depths are quite large, which may affect the safety of the railway operation. Thus, it is necessary to deal with settlement issues when designing railway construction.

scholarly journals Using PS-InSAR with Sentinel-1 Images for Deformation Monitoring in Northeast Algeria

Geosciences ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 315
Author(s):  
Omar Beladam ◽  
Timo Balz ◽  
Bahaa Mohamadi ◽  
Mahdjoub Abdalhak
Keyword(s):  
Ground Deformation ◽  
Regional Scale ◽  
Deformation Monitoring ◽  
Slope Instability ◽  
Radar Interferometry ◽  
Persistent Scatterer Interferometry ◽  
Accurate Identification ◽  
The North ◽  
Persistent Scatterer ◽  
Ground Deformation Monitoring

Constantine city, Algeria, and its surroundings have always been affected by natural and human-induced slope instability and subsidence. Neogene clay-conglomeratic formations, which form the largest part of Constantine city, are extremely sensitive to the presence of water, which makes them susceptible to landslides. Fast and accurate identification and monitoring of the main areas facing existing or potential hazardous risks at a regional scale, as well as measuring the amount of displacement is essential for the conservation and sustainable development of Constantine. In the last three decades, the application of radar interferometry techniques for the measurement of millimeter-level terrain motions has become one of the most powerful tools for ground deformation monitoring due to its large coverage and low costs. Persistent scatterer interferometry (PS-InSAR) has a demonstrated potential for monitoring a range of hazard event scenarios and tracking their spatiotemporal evolution. We demonstrate the efficiency of Sentinel-1 data for deformation monitoring in Constantine located in the northeast of Algeria, and how an array of information such as geological maps and ground-measurements are integrated for deformation mapping. We conclude this article with a discussion of the potential of advanced differential radar interferometry approaches and their applicability for structural and ground deformation monitoring, including the advantages and challenges of these approaches in the north of Algeria.

scholarly journals Measuring Urban Subsidence in the Rome Metropolitan Area (Italy) with Sentinel-1 SNAP-StaMPS Persistent Scatterer Interferometry

2019 ◽  
Vol 11 (2) ◽  
pp. 129 ◽  
Author(s):  
José Delgado Blasco ◽  
Michael Foumelis ◽  
Chris Stewart ◽  
Andrew Hooper
Keyword(s):  
Ground Deformation ◽  
European Space Agency ◽  
Vertical Motion ◽  
Automatic Processing ◽  
Deformation Monitoring ◽  
Geographical Information ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Processing Chain ◽  
Persistent Scatterer

Land subsidence in urban environments is an increasingly prominent aspect in the monitoring and maintenance of urban infrastructures. In this study we update the subsidence information over Rome and its surroundings (already the subject of past research with other sensors) for the first time using Copernicus Sentinel-1 data and open source tools. With this aim, we have developed a fully automatic processing chain for land deformation monitoring using the European Space Agency (ESA) SentiNel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). We have applied this automatic processing chain to more than 160 Sentinel-1A images over ascending and descending orbits to depict primarily the Line-Of-Sight ground deformation rates. Results of both geometries were then combined to compute the actual vertical motion component, which resulted in more than 2 million point targets, over their common area. Deformation measurements are in agreement with past studies over the city of Rome, identifying main subsidence areas in: (i) Fiumicino; (ii) along the Tiber River; (iii) Ostia and coastal area; (iv) Ostiense quarter; and (v) Tivoli area. Finally, post-processing of Persistent Scatterer Inteferometry (PSI) results, in a Geographical Information System (GIS) environment, for the extraction of ground displacements on urban infrastructures (including road networks, buildings and bridges) is considered.

scholarly journals PSInSAR Processing for Volcanic Ground Deformation Monitoring Over Fogo Island

Proceedings ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 3 ◽  
Author(s):  
Arun Babu ◽  
Shashi Kumar
Keyword(s):  
Phase Difference ◽  
Volcanic Eruption ◽  
Ground Deformation ◽  
Natural Disturbance ◽  
Volcanic Field ◽  
Deformation Monitoring ◽  
Line Of Sight ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Fogo Volcano

Persistent Scatterer Interferometry Synthetic Aperture Radar (PSInSAR) has been widely used in the precise measurement of ground deformation due to anthropogenic and natural disturbance of the earth’s surface. The present study has utilized the spaceborne C-band Sentinel-1 data for PSInSAR processing to generate a displacement map due to the volcanic eruption of Pico do Fogo volcano of the Fogo Island. An eruption was recorded in the year 2014–2015 and the Fogo volcano became active on 23 November 2014. It was observed that the intensity of the volcanic eruption during 2014–2015 had approached the intensity of the volcanic eruption of 1951, which was recorded as one of the strongest eruptions on the island. The volcanic eruption continued for 77 days and it stopped on 8 February 2015. To find the mean line-of-sight displacement from PSInSAR processing, a total of seven Single Look Complex (SLC) products of Sentinel-1 data in the interferometric mode were used. The SLC product of the SAR data that was acquired before the start of the volcanic eruption was chosen as the master image and all the remaining six slave images were precisely coregistered. The selection of Persistent Scatterers (PSs) is the most important step in PSInSAR processing. The initial set of PSs was identified by amplitude stability index and phase analysis was performed to estimate the phase stability of each resolution cell. After PS identification, 3D phase unwrapping was performed. The unwrapping step involved the low-pass filtering of the complex phase difference and time series in the frequency domain using a Gaussian window. The phase difference between each filtered data point was then calculated. The unwrapped phase of the interferogram was used to generate a displacement map for the volcanic field. The PSInSAR-based line-of-sight displacement was measured in the range of −34 mm to +35 mm and the standard deviation of the displacement ranged from +2 mm to +30 mm.

scholarly journals A Research on Landslides Automatic Extraction Model Based on the Improved Mask R-CNN

2021 ◽  
Vol 10 (3) ◽  
pp. 168
Author(s):  
Peng Liu ◽  
Yongming Wei ◽  
Qinjun Wang ◽  
Jingjing Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Remote Sensing Data ◽  
Extraction Methods ◽  
New Method ◽  
Detection Accuracy ◽  
Sufficient Information ◽  
Automatic Extraction ◽  
Emergency Rescue ◽  
Feature Pyramid ◽  
High Level ◽  
Extraction Model

Landslides are the most common and destructive secondary geological hazards caused by earthquakes. It is difficult to extract landslides automatically based on remote sensing data, which is import for the scenario of disaster emergency rescue. The literature review showed that the current landslides extraction methods mostly depend on expert interpretation which was low automation and thus was unable to provide sufficient information for earthquake rescue in time. To solve the above problem, an end-to-end improved Mask R-CNN model was proposed. The main innovations of this paper were (1) replacing the feature extraction layer with an effective ResNeXt module to extract the landslides. (2) Increasing the bottom-up channel in the feature pyramid network to make full use of low-level positioning and high-level semantic information. (3) Adding edge losses to the loss function to improve the accuracy of the landslide boundary detection accuracy. At the end of this paper, Jiuzhaigou County, Sichuan Province, was used as the study area to evaluate the new model. Results showed that the new method had a precision of 95.8%, a recall of 93.1%, and an overall accuracy (OA) of 94.7%. Compared with the traditional Mask R-CNN model, they have been significantly improved by 13.9%, 13.4%, and 9.9%, respectively. It was proved that the new method was effective in the landslides automatic extraction.

scholarly journals InSAR Multitemporal Data over Persistent Scatterers to Detect Floodwater in Urban Areas: A Case Study in Beletweyne, Somalia

2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Luca Pulvirenti ◽  
Marco Chini ◽  
Nazzareno Pierdicca
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
The Other ◽  
Spatial Average ◽  
Calibration Data ◽  
Suburban Areas ◽  
Persistent Scatterers ◽  
Optical Images ◽  
Interferometric Phase ◽  
Multitemporal Data

A stack of Sentinel-1 InSAR data in an urban area where flood events recurrently occur, namely Beletweyne town in Somalia, has been analyzed. From this analysis, a novel method to deal with the problem of flood mapping in urban areas has been derived. The approach assumes the availability of a map of persistent scatterers (PSs) inside the urban settlement and is based on the analysis of the temporal trend of the InSAR coherence and the spatial average of the exponential of the InSAR phase in each PS. Both interferometric products are expected to have high and stable values in the PSs; therefore, anomalous decreases may indicate that floodwater is present in an urban area. The stack of Sentinel-1 data has been divided into two subsets. The first one has been used as a calibration set to identify the PSs and determine, for each PS, reference values of the coherence and the spatial average of the exponential of the interferometric phase under standard non-flooded conditions. The other subset has been used for validation purposes. Flood maps produced by UNOSAT, analyzing very-high-resolution optical images of the floods that occurred in Beletweyne in April–May 2018, October–November 2019, and April–May 2020, have been used as reference data. In particular, the map of the April–May 2018 flood has been used for training purposes together with the subset of Sentinel-1 calibration data, whilst the other two maps have been used to validate the products generated by applying the proposed method. The main product is a binary map of flooded PSs that complements the floodwater map of rural/suburban areas produced by applying a well-consolidated algorithm based on intensity data. In addition, a flood severity map that labels the different districts of Beletweyne, as not, partially, or totally flooded has been generated to consolidate the validation. The results have confirmed the effectiveness of the proposed method.

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