Hybrid AI-physical Modeling for Penetration Bias Correction in X-band InSAR DEMs: A Greenland Case Study

Islam Mansour; Georg Fischer; Ronny Hänsch; Irena Hajnsek

doi:10.1109/CVPRW67362.2025.00205

Abstract

A hybrid AI-physical method to correct penetration bias in X-band InSAR DEMs over the Greenland Ice Sheet, parameterising the vertical structure function via machine learning.

Citation

@inproceedings{mansour2025hybridcvprw,
  title = {Hybrid AI-physical Modeling for Penetration Bias Correction in X-band InSAR DEMs: A Greenland Case Study},
  author = {Mansour, Islam and Fischer, Georg and Hänsch, Ronny and Hajnsek, Irena},
  booktitle = {2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  address = {Nashville, TN, USA},
  pages = {2175--2184},
  year = {2025},
  doi = {10.1109/CVPRW67362.2025.00205}
}