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Remote Sensing
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Advances and Innovative Applications in Multi-temporal InSAR Technology
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Advances and Innovative Applications in Multi-temporal InSAR Technology

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

Deadline for manuscript submissions: 15 April 2025 | Viewed by 4053

Special Issue Editors

Dr. Hongyu Liang

E-Mail Website
Guest Editor
College of Surveying and Geo-Informatics, Tongji University, Shanghai, China
Interests: InSAR; multi-temporal InSAR; deformation analysis
Dr. Lei Xie

E-Mail Website
Guest Editor
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
Interests: SAR interferometry; deformation monitoring; geohazard modelling; geophysical parameter inversion
Dr. Songbo Wu

E-Mail Website
Guest Editor
Department of Land Surveying and Geo-Informatics, Research Institute for Land and Space, The Hong Kong Polytechnic University, Hong Kong 999077, China
Interests: SAR image processing; advanced SAR denoising method; InSAR; remote sensing; coastal hazards monitoring
Special Issues, Collections and Topics in MDPI journals
Dr. Guoqiang Shi

E-Mail Website
Guest Editor
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China
Interests: SAR image processing, urban geo-hazards; InSAR; remote sensing; infrastructure monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are delighted to announce the upcoming Special Issue titled “Advances and Innovative Applications in Multi-temporal InSAR Technology”. Multi-temporal InSAR (MT-InSAR) has proven to be a powerful geodetic tool across various fields such as ground subsidence, infrastructure monitoring, geohazard detection, and geophysical studies, thanks to its all-weather, high-resolution capabilities. This Special Issue will feature contributions from eminent and emerging researchers, offering a platform to highlight the latest developments in MT-InSAR for advanced methodologies and innovative applications.

Our goal with this Special Issue is to delve into frontier research concerning advanced MT-InSAR techniques and their innovative applications, including innovative algorithms, error corrections, artificial intelligence integration, infrastructure monitoring, geohazards monitoring, geophysical parameter inversion, coastal environment monitoring, and environmental impact assessment. By showcasing the latest advancements in InSAR technology, our Special Issue will serve as a valuable resource for academics, professionals, and policymakers involved in hazard monitoring and sustainable development. It is also poised to enrich the existing literature by providing insights into the practical implementation of MT-InSAR technology and applications for global sustainability challenges.

We welcome original research papers and review articles on a variety of topics within advanced MT-InSAR technology and its innovative applications, including but not limited to the following:

  • Development of MT-InSAR data processing algorithms.
  • Artificial intelligence enhancements in MT-InSAR.
  • Multiple-sensor integration with MT-InSAR.
  • Physical parameter investigation with MT-InSAR.
  • Progress in satellite SAR missions and InSAR observations.
  • MT-InSAR applications in geohazard detection.
  • MT-InSAR applications in infrastructure monitoring.
  • MT-InSAR applications in environmental monitoring.

We eagerly await your valuable contributions to this Special Issue.

Dr. Hongyu Liang
Dr. Lei Xie
Dr. Songbo Wu
Dr. Guoqiang Shi
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

  • SAR interferometry (InSAR)
  • advanced multi-temporal InSAR algorithms
  • error estimation and correction
  • deformation modelling
  • parameter inversion
  • data integration
  • infrastructure stability monitoring
  • geohazard detection
  • machine/deep learning

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Published Papers (2 papers)

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Research

21 pages, 13934 KiB  
Article
A Robust Tie-Points Matching Method with Regional Feature Representation for Synthetic Aperture Radar Images
by Yifan Zhang, Yan Zhu, Liqun Liu, Xun Du, Kun Han, Junhui Wu, Zhiqiang Li, Lingshuai Kong and Qiwei Lin
Remote Sens. 2024, 16(13), 2491; https://doi.org/10.3390/rs16132491 - 8 Jul 2024
Viewed by 1158
Abstract
The precise tie-points (TPs) on synthetic aperture radar (SAR) images are a critical cornerstone in the global digital elevation model (DEM) and digital ortho map (DOM) production process. While there are abundant studies on SAR TPs matching, improvement opportunities persist in large areas. [...] Read more.
The precise tie-points (TPs) on synthetic aperture radar (SAR) images are a critical cornerstone in the global digital elevation model (DEM) and digital ortho map (DOM) production process. While there are abundant studies on SAR TPs matching, improvement opportunities persist in large areas. The correspondences have pixel-level errors during geocoding, which result in misalignment between global products. Consequently, this paper proposed a robust method for SAR images TPs matching, which consists of three key steps: (1) interest point extraction based on the dynamic Harris area entropy (DHAE) grid; (2) adaptive determination of template size; (3) normalized cross correlation (NCC) template matching. DHAE is a regional texture information grid based on the SAR-Harris map, and it is achieved through dynamic block division. Generating the DHAE grid over SAR images enables the extraction of interest points that have regional feature representation and distribution uniformity. A variable-size matching template is adaptively determined based on DHAE to enhance template quality while maintaining computational efficiency. Subsequently, the NCC algorithm is employed to find subpixel-precise correspondences. The proposed method is applied on TPs matching in 57 Terra-SAR images, which cover a large geographical area. Furthermore, the overlapping area is partitioned into five segments according to different coverage types. The experimental results demonstrate that the proposed method outperforms other template matching methods. For all coverage types, the proposed method exhibits high-precision sub-pixel results that reach up to 38.64% in terms of the relative positioning error (RPE), particularly in texture-weak and large areas. Full article
(This article belongs to the Special Issue Advances and Innovative Applications in Multi-temporal InSAR Technology)
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17 pages, 18140 KiB  
Article
Life Cycle Mining Deformation Monitoring and Analysis Using Sentinel-1 and Radarsat-2 InSAR Time Series
by Zhi Ma, Xiaoqing Yang, Lei Xie and Wei Dong
Remote Sens. 2024, 16(13), 2335; https://doi.org/10.3390/rs16132335 - 26 Jun 2024
Viewed by 2009
Abstract
The life cycle of mining results in various patterns of surface deformation as it progresses through development, production, and reclamation. Therefore, the spatial–temporal patterns of ground deformation provide a crucial indicator to understand the mining activities, related geohazards, and environmental restoration. This study [...] Read more.
The life cycle of mining results in various patterns of surface deformation as it progresses through development, production, and reclamation. Therefore, the spatial–temporal patterns of ground deformation provide a crucial indicator to understand the mining activities, related geohazards, and environmental restoration. This study investigates the decadal deformation (2012–2022) of three coal mines during different stages of mines’ life cycles in Henan, China, using radar interferometry with Radarsat-2 and Sentinel-1 data. The results reveal multiple deformation patterns across different areas: the Changcun mine area changed from ground subsidence to uplift following the termination of exploitation in 2016; the Xiadian mine area has been continuously developing over the past decade, resulting in a cumulative subsidence of 55.6 mm; and the Liyuan mine area exhibits surface rebound at a rate of 7.9 mm/year since its closure in 2007. We also probe the mining geometry of the production process by using a rectangular model. This study highlights the significance of long-term InSAR observations and deformation modeling in elucidating the mining operation dynamics of small mining zones in their production, transition, and post-closure periods, thereby facilitating the management of small-scale mining. Full article
(This article belongs to the Special Issue Advances and Innovative Applications in Multi-temporal InSAR Technology)
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