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Synthetic Aperture Radar Interferometry Symposium 2024

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4610

Special Issue Editors

Prof. Dr. Mingsheng Liao

E-Mail Website
Guest Editor
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
Interests: remote sensing image processing and analysis; algorithms for interferometric SAR; integration and fusion of multi-source spatial information; applications of remote sensing data
Prof. Dr. Xinjian Shan

E-Mail Website
Guest Editor
Institute of Geology, Chinese Academy of Geological Sciences, Beijing, China
Interests: geodesy and surveying; volcanology; geology
Prof. Dr. Liming Jiang

E-Mail Website
Guest Editor
State Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
Interests: InSAR and image geodesy; global change and geological disaster monitoring and early warning
Dr. Jie Dong

E-Mail Website
Guest Editor
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Interests: early identification and monitoring of geological hazards; satellite-based/ground-based InSAR algorithms
Special Issues, Collections and Topics in MDPI journals
Dr. Menghua Li

E-Mail Website
Guest Editor
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China
Interests: InSAR; landslide monitoring with multi-source remote sensing data; pixel offset tracking
Dr. Wenyu Gong

E-Mail Website
Guest Editor
State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration, Beijing 100029, China
Interests: InSAR; time series analysis; crustal deformation; geophysical modeling; natural hazards
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The field of Synthetic Aperture Radar Interferometry (InSAR) has experienced significant global growth, with ongoing research and developments in missions, techniques, products, and applications. Concurrently, given the high demand for InSAR applications and the rapid expansion of related research, China has also been making notable strides in corresponding technologies. Our colleagues in China are enthusiastic about organizing a symposium dedicated to InSAR, to bring together research groups from the InSAR communities for collaboration and exchange. Wuhan University, in collaboration with other institutions, is hosting the Synthetic Aperture Radar Interferometry Symposium 2024, anticipating the participation of a majority of leading experts in the InSAR field. 

In collaboration with Remote Sensing, we hope this Special Issue will serve as a platform for in-depth discussions and exchanges covering various aspects of InSAR, including, but not limited to, systems and missions, theories and methodologies, data processing techniques, and applications in Earth observation.

(1) InSAR systems and missions:

  • New concepts and future missions.
  • Spaceborne InSAR.
  • Airborne InSAR.
  • Ground-based InSAR.
  • Lunar-based InSAR.

(2) InSAR theory and methods:

  • Multi-temporal InSAR.
  • Tomographic InSAR.
  • Polarimetric InSAR.
  • Bistatic InSAR.

(3) InSAR data processing techniques:

  • Advanced/intelligent InSAR processing and interpretation.
  • Multi-satellite multi-track InSAR data processing.
  • Wide-area InSAR high-performance computing.
  • InSAR data products and services.

(4) Applications of InSAR for earth observation:

  • Terrain measurement.
  • Earthquake cycle deformation.
  • Infrastructure health and safety.
  • Subsidence and groundwater.
  • Landslides and volcanic disasters.
  • Cryosphere changes and processes.
  • Other applications.

Prof. Dr. Mingsheng Liao
Prof. Dr. Xinjian Shan
Prof. Dr. Liming Jiang
Dr. Jie Dong
Dr. Menghua Li
Dr. Wenyu Gong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • synthetic aperture radar
  • interferometric synthetic aperture radar
  • surface deformation
  • earth observation
  • SAR interferometry symposium

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Published Papers (6 papers)

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Research

12 pages, 4947 KiB  
Communication
Fault Kinematics of the 2022 Delingha Mw 5.6 and Mw 5.7 Earthquakes Revealed by InSAR Observations
by Xuening Wang, Donglin Wu, Lian Liu, Chenglong Li, Yongliang Bai and Xing Huang
Remote Sens. 2024, 16(22), 4237; https://doi.org/10.3390/rs16224237 - 14 Nov 2024
Viewed by 224
Abstract
Between January and April 2022, three moderate earthquakes (Mw 5.6 on 23 January, Mw 5.7 on 25 March, and Mw 5.1 on 15 April) struck the Hala Lake area of Delingha, Qinghai, China. Their seismogenic faults are poorly mapped, resulting in an unclear [...] Read more.
Between January and April 2022, three moderate earthquakes (Mw 5.6 on 23 January, Mw 5.7 on 25 March, and Mw 5.1 on 15 April) struck the Hala Lake area of Delingha, Qinghai, China. Their seismogenic faults are poorly mapped, resulting in an unclear understanding of their kinematics and regional seismotectonics. In this study, we employed Interferometric Synthetic Aperture Radar (InSAR) observations to reconstruct the coseismic deformation fields of the Mw 5.6 and 5.7 events. We then utilized a Bayesian inversion algorithm to delineate the fault geometries of the two events, and further resolved their coseismic fault slip. Our results reveal that these earthquakes ruptured different fault planes: the fault plane of the Mw 5.6 event dips westward at an angle of 60°, while the Mw 5.7 event ruptured as a nearly vertical fault with a dipping angle of 89°. The finite-fault slip inversions further demonstrate that the coseismic rupture of the Mw 5.6 event was predominantly concentrated between depths of 2 km and 7 km, with a maximum slip of 0.18 m; in contrast, the Mw 5.7 event was mainly concentrated between depths of 2 km and 9 km, with a maximum slip of 0.4 m. We calculated the coseismic Coulomb failure stress change (ΔCFS) induced by these two earthquakes. Integrating the analysis of ΔCFS and the spatial distribution of aftershocks, we argue that the sequence earthquakes were triggered by the proceeding earthquakes. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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24 pages, 16222 KiB  
Article
Monitoring and Analysis of Surface Deformation in the Buzhaoba Open-Pit Mine Based on SBAS-InSAR Technology
by Yu Zheng, Zhifang Zhao, Min Zeng, Dingyi Zhou, Xiaotong Su and Dingshuai Liu
Remote Sens. 2024, 16(22), 4177; https://doi.org/10.3390/rs16224177 - 8 Nov 2024
Viewed by 467
Abstract
The Buzhaoba open-pit mine is an important lignite production base in Yunnan Province, China. As mining activities have continued to progress, varying degrees of deformation have occurred in different areas of the Buzhaoba open-pit mine, threatening normal coal production and mine safety. To [...] Read more.
The Buzhaoba open-pit mine is an important lignite production base in Yunnan Province, China. As mining activities have continued to progress, varying degrees of deformation have occurred in different areas of the Buzhaoba open-pit mine, threatening normal coal production and mine safety. To comprehensively investigate the characteristics of surface deformation and its influencing factors at the Buzhaoba open-pit mine, this study employed the following methods: first, the SBAS-InSAR technique was used to process 86 Sentinel-1A ascending and descending orbit remote sensing images from 2020 to 2023, obtaining LOS surface deformation information for the mining area; second, leveling observation data were used to validate the accuracy of the SBAS-InSAR results, and based on the principle of two-dimensional deformation decomposition, the east–west and vertical surface deformation information of the mining area was obtained; finally, the temporal variation characteristics and influencing factors of the Buzhaoba open-pit mine were analyzed. The study results indicate that (1) the maximum LOS surface deformation rates in the ascending and descending orbits of the mining area were −42.1 mm/a and −114.0 mm/a, respectively; (2) the correlation coefficient between the SBAS-InSAR monitoring results and the leveling observation results was 0.938, confirming the reliability of the SBAS-InSAR monitoring results; (3) the maximum east–west and vertical deformation rates obtained from the two-dimensional deformation decomposition were −103.4 mm/a and −189.2 mm/a, respectively, with the surface deformation in the east–west direction being more pronounced; (4) internal factors such as stratigraphic lithology and geological structures, as well as atmospheric rainfall, have a certain degree of influence on the surface deformation of the Buzhaoba open-pit mine. Therefore, the research results of this study can provide important data support and theoretical references for safety management and disaster prevention in the mining area. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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21 pages, 23010 KiB  
Article
Three-Dimensional Reconstruction of Partially Coherent Scatterers Using Iterative Sub-Network Generation Method
by Xiantao Wang, Zhen Dong, Youjun Wang, Xing Chen and Anxi Yu
Remote Sens. 2024, 16(19), 3707; https://doi.org/10.3390/rs16193707 - 5 Oct 2024
Viewed by 525
Abstract
Synthetic aperture radar tomography (TomoSAR) has gained significant attention for three-dimensional (3D) imaging in urban environments. A notable limitation of traditional TomoSAR approaches is their primary focus on persistent scatterers (PSs), disregarding targets with temporal decorrelated characteristics. Temporal variations in coherence, especially in [...] Read more.
Synthetic aperture radar tomography (TomoSAR) has gained significant attention for three-dimensional (3D) imaging in urban environments. A notable limitation of traditional TomoSAR approaches is their primary focus on persistent scatterers (PSs), disregarding targets with temporal decorrelated characteristics. Temporal variations in coherence, especially in urban areas due to the dense population of buildings and artificial structures, can lead to a reduction in detectable PSs and suboptimal 3D reconstruction performance. The concept of partially coherent scatterers (PCSs) has been proven effective by capturing the partial temporal coherence of targets across the entire time baseline. In this study, an novel approach based on an iterative sub-network generation method is introduced to leverage PCSs for enhanced 3D reconstruction in dynamic environments. We propose a coherence constraint iterative variance analysis approach to determine the optimal temporal baseline range that accurately reflects the interferometric coherence of PCSs. Utilizing the selected PCSs, a 3D imaging technique that incorporates the iterative generation of sub-networks into the SAR tomography process is developed. By employing the PS reference network as a foundation, we accurately invert PCSs through the iterative generation of local star-shaped networks, ensuring a comprehensive coverage of PCSs in study areas. The effectiveness of this method for the height estimation of PCSs is validated using the TerraSAR-X dataset. Compared with traditional PS-based TomoSAR, the proposed approach demonstrates that PCS-based elevation results complement those from PSs, significantly improving 3D reconstruction in evolving urban settings. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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14 pages, 374883 KiB  
Article
Revisiting the 2017 Jiuzhaigou (Sichuan, China) Earthquake: Implications for Slip Inversions Based on InSAR Data
by Zhengwen Sun and Yingwen Zhao
Remote Sens. 2024, 16(18), 3406; https://doi.org/10.3390/rs16183406 - 13 Sep 2024
Viewed by 598
Abstract
The 2017 Jiuzhaigou earthquake (Ms = 7.0) struck the eastern Tibetan Plateau and caused extensive concern. However, the reported slip models of this earthquake have distinct discrepancies and cannot provide a good fit for GPS data. The Jiuzhaigou earthquake also presents a good [...] Read more.
The 2017 Jiuzhaigou earthquake (Ms = 7.0) struck the eastern Tibetan Plateau and caused extensive concern. However, the reported slip models of this earthquake have distinct discrepancies and cannot provide a good fit for GPS data. The Jiuzhaigou earthquake also presents a good opportunity to investigate the question of how to avoid overfitting of InSAR observations for co-seismic slip inversions. To comprehend this shock, we first used pre-seismic satellite optical images to extract a surface trace of the seismogenic fault, which constitutes the northern segment of the Huya Fault. Then, we collected GPS observations as well as to measure the co-seismic displacements. Lastly, joint inversions were carried out to obtain the slip distribution. Our results showed that the released moment was 5.3 × 1018 N m, equivalent to Mw 6.4 with a rigidity of 30 GPa. The maximum slip at a depth of ~6.8 km reached up to 1.12 m, dominated by left-lateral strike-slip. The largest potential surface rupture occurred in the center of the seismogenic fault with strike- and dip-slip components of 0.4 m and 0.2 m, respectively. Comparison with the focal mechanisms of the 1973 Ms 6.5 earthquake and the 1976 triplet of earthquakes (Mw > 6) on the middle and south segments of the Huya Fault indicated different regional motion and slip mechanisms on the three segments. The distribution of co-seismic landslides had a strong correlation with surface displacements rather than surface rupture. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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25 pages, 8750 KiB  
Article
Liaohe Oilfield Reservoir Parameters Inversion Based on Composite Dislocation Model Utilizing Two-Dimensional Time-Series InSAR Observations
by Hang Jiang, Rui Zhang, Bo Zhang, Kangyi Chen, Anmengyun Liu, Ting Wang, Bing Yu and Lin Deng
Remote Sens. 2024, 16(17), 3314; https://doi.org/10.3390/rs16173314 - 6 Sep 2024
Viewed by 677
Abstract
To address the industry’s demand for sustainable oilfield development and safe production, it is crucial to enhance the scientific rigor and accuracy of monitoring ground stability and reservoir parameter inversion. For the above purposes, this paper proposes a technical solution that employs two-dimensional [...] Read more.
To address the industry’s demand for sustainable oilfield development and safe production, it is crucial to enhance the scientific rigor and accuracy of monitoring ground stability and reservoir parameter inversion. For the above purposes, this paper proposes a technical solution that employs two-dimensional time-series ground deformation monitoring based on ascending and descending Interferometric Synthetic Aperture Radar (InSAR) technique first, and the composite dislocation model (CDM) is utilized to achieve high-precision reservoir parameter inversion. To validate the feasibility of this method, the Liaohe Oilfield is selected as a typical study area, and the Sentinel-1 ascending and descending Synthetic Aperture Radar (SAR) images obtained from January 2020 to December 2023 are utilized to acquire the ground deformation in various line of sight (LOS) directions based on Multitemporal Interferometric Synthetic Aperture Radar (MT-InSAR). Subsequently, by integrating the ascending and descending MT-InSAR observations, we solved for two-dimensional ground deformation, deriving a time series of vertical and east-west deformations. Furthermore, reservoir parameter inversion and modeling in the subsidence trough area were conducted using the CDM and nonlinear Bayesian inversion method. The experimental results indicate the presence of uneven subsidence troughs in the Shuguang and Huanxiling oilfields within the study area, with a continuous subsidence trend observed in recent years. Among them, the subsidence of the Shuguang oilfield is more significant and shows prominent characteristics of single-source center subsidence accompanied by centripetal horizontal displacement, the maximum vertical subsidence rate reaches 221 mm/yr, and the maximum eastward and westward deformation is more than 90 mm/yr. Supported by the two-dimensional deformation field, we conducted a comparative analysis between the Mogi, Ellipsoidal, and Okada models in terms of reservoir parameter inversion, model fitting efficacy, and residual distribution. The results confirmed that the CDM offers the best adaptability and highest accuracy in reservoir parameter inversion. The proposed technical methods and experimental results can provide valuable references for scientific planning and production safety assurance in related oilfields. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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23 pages, 14119 KiB  
Article
Construction of High-Precision and Complete Images of a Subsidence Basin in Sand Dune Mining Areas by InSAR-UAV-LiDAR Heterogeneous Data Integration
by Rui Wang, Shiqiao Huang, Yibo He, Kan Wu, Yuanyuan Gu, Qimin He, Huineng Yan and Jing Yang
Remote Sens. 2024, 16(15), 2752; https://doi.org/10.3390/rs16152752 - 27 Jul 2024
Viewed by 841
Abstract
Affected by geological factors, the scale of surface deformation in a hilly semi-desertification mining area varies. Meanwhile, there is certain dense vegetation on the ground, so it is difficult to construct a high-precision and complete image of a subsidence basin by using a [...] Read more.
Affected by geological factors, the scale of surface deformation in a hilly semi-desertification mining area varies. Meanwhile, there is certain dense vegetation on the ground, so it is difficult to construct a high-precision and complete image of a subsidence basin by using a single monitoring method, and hence the laws of the deformation and inversion of mining parameters cannot be known. Therefore, we firstly propose conducting collaborative monitoring by using InSAR (Interferometric Synthetic Aperture Radar), UAV (unmanned aerial vehicle), and 3DTLS (three-dimensional terrestrial laser scanning). The time-series complete surface subsidence basin is constructed by fusing heterogeneous data. In this paper, SBAS-InSAR (Small Baseline Subset) technology, which has the characteristics of reducing the time and space discorrelation, is used to obtain the small-scale deformation of the subsidence basin, oblique photogrammetry and 3D-TLS with strong penetrating power are used to obtain the anomaly and large-scale deformation, and the local polynomial interpolation based on the weight of heterogeneous data is used to construct a complete and high-precision subsidence basin. Compared with GNSS (Global Navigation Satellite System) monitoring data, the mean square errors of 1.442 m, 0.090 m, 0.072 m are obtained. The root mean square error of the high-precision image of the subsidence basin data is 0.040 m, accounting for 1.4% of the maximum subsidence value. The high-precision image of complete subsidence basin data can provide reliable support for the study of surface subsidence law and mining parameter inversion. Full article
(This article belongs to the Special Issue Synthetic Aperture Radar Interferometry Symposium 2024)
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