Advances in InSAR Processing: Algorithmic Developments and Diverse Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 29 July 2025 | Viewed by 518
Special Issue Editors
Interests: InSAR algorithm development; geohazard monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: landscape evolution; geophysical hazards; archaeology; cultural heritage; remote sensing; earth observation; InSAR; landslides; land subsidence; ground instability
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The field of interferometric synthetic aperture radar (InSAR) continues to evolve, driven by significant advances in processing algorithms that are enhancing accuracy and broadening the range of applications. This Special Issue will focus on the latest algorithmic advancements in InSAR that are crucial for achieving millimetric accuracy in ground deformation measurements. Key developments include phase unwrapping techniques, persistent scatterer InSAR (PS-InSAR), small baseline subset (SBAS), advanced atmospheric correction techniques, including tropospheric and ionospheric delay correction, and non-closure phase bias correction.
Additionally, the recent application of deep learning techniques in InSAR is revolutionizing how we approach error detection, correction, and data processing. Notably, deep learning has been applied to improve phase unwrapping algorithms, significantly enhancing accuracy in complex areas with high noise or decorrelation. These techniques are also utilized in multi-temporal InSAR processing, automatic displacement detection, and hazard classification, enabling more efficient and precise monitoring of slow-moving hazards, such as land subsidence, volcanic deformation, and landslides.
This Special Issue will highlight how these algorithmic innovations are broadening the scope of InSAR applications. These include climate change studies, soil moisture estimation, coastal monitoring, structural health monitoring, and multi-hazard risk assessment, further enhancing the ability to monitor and assess complex geophysical processes.
Dr. Yasser Maghsoudi
Dr. Francesca Cigna
Guest Editors
Manuscript Submission Information
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Keywords
- InSAR algorithm development
- phase unwrapping
- deep learning
- ground deformation
- persistent scatterer InSAR (PS-InSAR)
- small baseline subset (SBAS)
- atmospheric correction
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