Abstract:
Phase unwrapping (PU) is essential for extracting geophysical information from interferometric synthetic aperture radar (InSAR) data but is an ill-posed inverse problem due to its non-linearity and non-uniqueness. Recent advances in well-posed signal processing and AI-driven techniques present exciting opportunities to reconceptualize phase unwrapping as a mathematically rigorous and well-posed problem or to overcome its inherent ill-posedness.
This session seeks to bride methodological advancements with the evolving application demands in Earth observations, fostering the development of robust and scalable phase unwrapping solutions for geodesy, hazard monitoring, and environmental change analysis. We welcome submissions on, but not limited to, the following topics:
(1) Innovative Theory: Advanced theories and mathematical frameworks aimed at transforming ill-posed PU into a well-posed problem.
(2) Innovative Methodologies: Methodologies that implement well-posed phase unwrapping by harnessing multi-source/multi-modal data, physics-informed machine learning models, and hybrid approaches that integrate optimization, probabilistic inference, and signal processing techniques etc.
(3) Real-World Applications: Case studies about well-posed InSAR techniques for deformation monitoring and its role in natural disaster alarming and mitigation (e.g., landslide, tailings dam failure, volcanic eruption, and co-seismic activities etc.), topography reconstruction and height measurement etc.
(4) Key Challenges and Limitations: Critical examinations of current challenges and limitations in phase unwrapping, including but not limited to data quality, the influence of environmental factors (e.g., soil moisture, vegetation type, and land cover), computational challenges associated with scaling phase unwrapping algorithms for large-area or real-time monitoring applications, as well as potential strategies to mitigate these issues.
Session Chairs:
Prof. Hanwen Yu (University of Electronic Science and Technology of China, China),
Dr. Yan Yan (University of Electronic Science and Technology of China, China)