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20 pages, 29641 KiB

Open AccessArticle

Slow Deformation Time-Series Monitoring for Urban Areas Based on the AWHPSPO Algorithm and TELM: A Case Study of Changsha, China

by Xuemin Xing, Jihang Zhang, Jun Zhu, Rui Zhang and Bin Liu

Remote Sens. 2023, 15(6), 1492; https://doi.org/10.3390/rs15061492 - 8 Mar 2023

Cited by 2 | Viewed by 1937

Abstract

Health monitoring is important for densely distributed urban infrastructures, particularly in cities undergoing rapid economic progress. Permanent scatterer interferometry (PSI) is an advanced remote sensing observation technique that is commonly used in urban infrastructure monitoring. However, the rapid construction of infrastructures may easily [...] Read more.

Health monitoring is important for densely distributed urban infrastructures, particularly in cities undergoing rapid economic progress. Permanent scatterer interferometry (PSI) is an advanced remote sensing observation technique that is commonly used in urban infrastructure monitoring. However, the rapid construction of infrastructures may easily cause a loss of coherence for radar interferometry, inducing a low density of effective permanent scatterer (PS) points, which is the main limitation of PSI. In order to address these problems, a novel time-series synthetic aperture radar interferometry (InSAR) process based on the adaptive window homogeneous pixel selection and phase optimization (AWHPSPO) algorithm and thermal expansion linear model (TELM) is proposed. Firstly, for homogeneous point selection, information on both the time-series intensity and deformation phases is considered, which can compensate for the defects of insufficient homogeneous samples and low phase quality in traditional distributed scatterer interferometric synthetic aperture radar (DS-InSAR) processing. Secondly, the physical, thermal expansion component, which reflects the material properties of the infrastructures, is introduced into the traditional linear model, which can more rationally reflect the temporal evolution of deformation variation, and the thermal expansion coefficients can be estimated simultaneously with the deformation parameters. In order to verify our proposed algorithm, the Orange Island area in Changsha City, China, was selected as the study area in this experiment. Three years of its historical time-series deformation fields and thermal expansion coefficients were regenerated. With the use of high-resolution TerraSAR-X radar satellite images, a maximum accumulated settlement of 12.3 mm and a minor uplift of 8.2 mm were detected. Crossvalidation with small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) results using Sentinel 1A data proved the reliability of AWHPSPO. The proposed algorithm can provide a reference for the control of the health and safety of urban infrastructures. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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22 pages, 40795 KiB

Open AccessArticle

Surface Subsidence Characteristics and Causes in Beijing (China) before and after COVID-19 by Sentinel-1A TS-InSAR

by Haiquan Sheng, Lv Zhou, Changjun Huang, Shubian Ma, Lingxiao Xian, Yukai Chen and Fei Yang

Remote Sens. 2023, 15(5), 1199; https://doi.org/10.3390/rs15051199 - 22 Feb 2023

Cited by 4 | Viewed by 2313

Abstract

Surface subsidence is a serious threat to human life, buildings and traffic in Beijing. Surface subsidence is closely related to human activities, and human activities in Beijing area showed a decreasing trend during the Corona Virus Disease 2019 (COVID-19). To study surface subsidence [...] Read more.

Surface subsidence is a serious threat to human life, buildings and traffic in Beijing. Surface subsidence is closely related to human activities, and human activities in Beijing area showed a decreasing trend during the Corona Virus Disease 2019 (COVID-19). To study surface subsidence in Beijing before and after the COVID-19 outbreak and its causes, a total of 51 Sentinel-1A SAR images covering Beijing from January 2018 to April 2022 were selected to derive subsidence information by Time Series Interferometry Synthetic Aperture Radar (TS-InSAR). The results of surface subsidence in Beijing demonstrate that Changping, Chaoyang, Tongzhou and Daxing Districts exhibited the most serious subsidence phenomenon before the COVID-19 outbreak. The four main subsidence areas form an anti-Beijing Bay that surrounds other important urban areas. The maximum subsidence rate reached −57.0 mm/year. After the COVID-19 outbreak, the main subsidence area was separated into three giant subsidence funnels and several small subsidence funnels. During this period, the maximum subsidence rate was reduced to −43.0 mm/year. Human activity decrease with the COVID-19 outbreak. This study effectively analysed the influence of natural factors on surface subsidence after excluding most of the human factors. The following conclusions are obtained from the analysis: (1) Groundwater level changes, Beijing’s geological structure and infrastructure construction are the main reasons for surface subsidence in Beijing. (2) Seasonal changes in rainfall and temperature indirectly affect groundwater level changes, thereby affecting surface subsidence in the area. (3) The COVID-19 outbreak in early 2020 reduced the payload of Beijing’s transportation facilities. It also slowed down the progress of various infrastructure construction projects in Beijing. These scenarios affected the pressure on the soft land base in Beijing and reduced the surface subsidence trend to some extent. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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17 pages, 10382 KiB

Open AccessArticle

Multitask Learning-Based for SAR Image Superpixel Generation

by Jiafei Liu, Qingsong Wang, Jianda Cheng, Deliang Xiang and Wenbo Jing

Remote Sens. 2022, 14(4), 899; https://doi.org/10.3390/rs14040899 - 14 Feb 2022

Cited by 5 | Viewed by 2552

Abstract

Most of the existing synthetic aperture radar (SAR) image superpixel generation methods are designed based on the raw SAR images or artificially designed features. However, such methods have the following limitations: (1) SAR images are severely affected by speckle noise, resulting in unstable [...] Read more.

Most of the existing synthetic aperture radar (SAR) image superpixel generation methods are designed based on the raw SAR images or artificially designed features. However, such methods have the following limitations: (1) SAR images are severely affected by speckle noise, resulting in unstable pixel distance estimation. (2) Artificially designed features cannot be well-adapted to complex SAR image scenes, such as the building regions. Aiming to overcome these shortcomings, we propose a multitask learning-based superpixel generation network (ML-SGN) for SAR images. ML-SGN firstly utilizes a multitask feature extractor to extract deep features, and constructs a high-dimensional feature space containing intensity information, deep semantic informantion, and spatial information. Then, we define an effective pixel distance measure based on the high-dimensional feature space. In addition, we design a differentiable soft assignment operation instead of the non-differentiable nearest neighbor operation, so that the differentiable Simple Linear Iterative Clustering (SLIC) and multitask feature extractor can be combined into an end-to-end superpixel generation network. Comprehensive evaluations are performed on two real SAR images with different bands, which demonstrate that our proposed method outperforms other state-of-the-art methods. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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19 pages, 8675 KiB

Open AccessArticle

A Most-Unfavorable-Condition Method for Bridge-Damage Detection and Analysis Using PSP-InSAR

by Runjie Wang, Jiameng Zhang and Xianglei Liu

Remote Sens. 2022, 14(1), 137; https://doi.org/10.3390/rs14010137 - 29 Dec 2021

Cited by 11 | Viewed by 2338

Abstract

The main contribution of this study is to provide a new idea to detect bridge damage by using PSP-InSAR technology. A most-unfavorable-condition method is proposed for bridge-damage detection and analysis. The method can determine the specific damaged location and occurrence time by using [...] Read more.

The main contribution of this study is to provide a new idea to detect bridge damage by using PSP-InSAR technology. A most-unfavorable-condition method is proposed for bridge-damage detection and analysis. The method can determine the specific damaged location and occurrence time by using the differential deformation values of persistent scatterer (PS) points on bridge piers. Taking Beijing Suzhou Bridge as an experimental area, 96 COSMO-SkyMed time-series SAR images were used from September 2011 to November 2017. Deformation values of PS points around Suzhou Bridge were acquired and analyzed. Experimental results show that in July 2017, the unusual maximum differential deformation value was 25.73 mm. It occurred between piers D₃ and D₄ of Suzhou Bridge, and it was deduced that the main girder between piers D₃ and D₄ may have been damaged in July 2017. As a validation, taking the differential deformation value between piers D₃ and D₄ as an input, the maximum tensile stress, and the maximum compressive stress were calculated as 2.1 MPa and 8.4 MPa, respectively, through a finite element model. The tensile stress exceeded the design value of the concrete, further confirming the damage of the girder between piers D₃ and D₄. Moreover, all results are consistent with the Suzhou Bridge damage information shown in existing records, which verify the accuracy and reliability of the proposed method. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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20 pages, 10041 KiB

Open AccessArticle

Long-Term Subsidence Monitoring of the Alluvial Plain of the Scheldt River in Antwerp (Belgium) Using Radar Interferometry

by Pierre-Yves Declercq, Pierre Gérard, Eric Pirard, Jan Walstra and Xavier Devleeschouwer

Remote Sens. 2021, 13(6), 1160; https://doi.org/10.3390/rs13061160 - 18 Mar 2021

Cited by 8 | Viewed by 3727

Abstract

The coupled effects of climate change, sea-level rise, and land sinking in estuaries/alluvial plains prone to inundation and flooding mean that reliable estimation of land movements/subsidence is becoming more crucial. During the last few decades, land subsidence has been monitored by precise and [...] Read more.

The coupled effects of climate change, sea-level rise, and land sinking in estuaries/alluvial plains prone to inundation and flooding mean that reliable estimation of land movements/subsidence is becoming more crucial. During the last few decades, land subsidence has been monitored by precise and continuous geodetic measurements either from space or using terrestrial techniques. Among them, the Persistent Scaterrer Interferometry (PSInSAR) technique is used on the entire Belgian territory to detect, map and interpret the identified ground movements observed since 1992. Here the research focuses on one of the biggest cities in Belgium that became the second European harbour with giant docks and the deepening of the Scheldt river allowing the navigation of the largest container vessels. The areas along the embankments of the Scheldt river and the harbour facilities are associated to Holocene fluviatile deposits overlain by recent landfills. These sedimentary deposits and human-made landfills are affected by important and ongoing land subsidence phenomena. The land subsidence process is highlighted by an annual average Line of Sight (LOS) velocity of about −3.4 mm/year during the years 1992–2001 (ERS1/2 datasets), followed by an annual average LOS velocity of about −2.71 mm/year and −2.11 mm/year, respectively, during the years 2003–2010 (ENVISAT) and 2016–2019 (Sentinel 1A). The Synthetic Aperture Radar (SAR) imagery data indicate a progressive decrease in the average annual velocities on a global scale independently of important local variations in different districts along the Scheldt river. On the contrary, the city centre and the old historic centre of Antwerp are not affected by negative LOS velocities, indicating stable ground conditions. A geological interpretation of this difference in settlement behaviour between the different areas is provided. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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24 pages, 9474 KiB

Open AccessArticle

Sentinel-1 Data for Underground Processes Recognition in Bucharest City, Romania

by Alina Radutu, Guri Venvik, Traian Ghibus and Constantin Radu Gogu

Remote Sens. 2020, 12(24), 4054; https://doi.org/10.3390/rs12244054 - 11 Dec 2020

Cited by 2 | Viewed by 3324

Abstract

Urban areas are strongly influenced by the different processes affecting the underground and implicitly the terrestrial surface. Land subsidence can be one of the effects of the urban processes. The identification of the vulnerable areas of the city, prone to subsidence, can be [...] Read more.

Urban areas are strongly influenced by the different processes affecting the underground and implicitly the terrestrial surface. Land subsidence can be one of the effects of the urban processes. The identification of the vulnerable areas of the city, prone to subsidence, can be of great help for a sustainable urban planning. Using Sentinel-1 data, by the PSI (persistent scatterer interferometry) technique, a vertical displacements map of Bucharest city has been prepared. It covers the time interval 2014–2018. Based on this map, several subsidence areas have been identified. One of them, holding a thick layer of debris from urban constructions, was analyzed in detail, on the basis of an accurate local geological model and by correlating the local displacements with the urban groundwater system hydraulic heads. The properties of the anthropogenic layer have been characterized by complementary geotechnical and hydrogeological studies. A dynamic instability pattern, highlighted by PSI results, has been put into evidence when related to this type of anthropogenic layer. This thick anthropogenic layer and its connections to the urban aquifer system have to be further analyzed, when the procedures of urban planning and design invoke constructive operations modifying the aquifer dynamics. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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23 pages, 3789 KiB

Open AccessFeature PaperArticle

Change Detection Based on the Coefficient of Variation in SAR Time-Series of Urban Areas

by Elise Colin Koeniguer and Jean-Marie Nicolas

Remote Sens. 2020, 12(13), 2089; https://doi.org/10.3390/rs12132089 - 30 Jun 2020

Cited by 30 | Viewed by 6101

Abstract

This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria [...] Read more.

This paper discusses change detection in SAR time-series. First, several statistical properties of the coefficient of variation highlight its pertinence for change detection. Subsequently, several criteria are proposed. The coefficient of variation is suggested to detect any kind of change. Furthermore, several criteria that are based on ratios of coefficients of variations are proposed to detect long events, such as construction test sites, or point-event, such as vehicles. These detection methods are first evaluated on theoretical statistical simulations to determine the scenarios where they can deliver the best results. The simulations demonstrate the greater sensitivity of the coefficient of variation to speckle mixtures, as in the case of agricultural plots. Conversely, they also demonstrate the greater specificity of the other criteria for the cases addressed: very short event or longer-term changes. Subsequently, detection performance is assessed on real data for different types of scenes and sensors (Sentinel-1, UAVSAR). In particular, a quantitative evaluation is performed with a comparison of our solutions with baseline methods. The proposed criteria achieve the best performance, with reduced computational complexity. On Sentinel-1 images containing mainly construction test sites, our best criterion reaches a probability of change detection of 90% for a false alarm rate that is equal to 5%. On UAVSAR images containing boats, the criteria proposed for short events achieve a probability of detection equal to 90% of all pixels belonging to the boats, for a false alarm rate that is equal to 2%. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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10 pages, 18638 KiB

Open AccessLetter

The Combined Effect of Orientation Angle and Material on PolSAR Images of Urban Areas

by Laetitia Thirion-Lefevre, Régis Guinvarc’h and Elise Colin-Koeniguer

Remote Sens. 2020, 12(10), 1632; https://doi.org/10.3390/rs12101632 - 20 May 2020

Cited by 8 | Viewed by 2907

Abstract

Polarimetric Synthetic Aperture Radar (PolSAR) images containing cities may exhibit misclassified areas when using polarimetric decompositions. Several articles relate this problem to the effects of orientation between the facades of buildings and the acquisition trajectory. Materials also play a role in polarimetric behavior. [...] Read more.

Polarimetric Synthetic Aperture Radar (PolSAR) images containing cities may exhibit misclassified areas when using polarimetric decompositions. Several articles relate this problem to the effects of orientation between the facades of buildings and the acquisition trajectory. Materials also play a role in polarimetric behavior. This paper deals with this combined effect of material and orientation. It analyzes different sets of data, airborne or space-borne, at L-, C- and X-bands, and for different orientation angles. It shows that considering dielectric dihedral rather than metallic in the polarimetric mechanism of double-bounce has a very important impact on the differences of intensities between the channels HH and VV. This difference is very important for small angles of orientation, and then decreases for large angles. Furthermore, the curves of the ratios between polarimetric intensities as a function of the orientation angle vary little with the materials and the frequencies encountered in all the scenarios envisaged. The signal of the ratio VV/HH raises a plateau around −1 dB for orientations higher than 30°. We also observe a plateau for HV/HH, but with a value around −5 dB. Full article

(This article belongs to the Special Issue Applications of SAR Images for Urban Areas)

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