Multi-Temporal InSAR and Machine Learning for Geohazard Monitoring: A Systematic Review with Emphasis on Noise Mitigation and Model Transferability Article

Alonso-Diaz, Alex, Fontes, Miguel, Teixeira, Ana Claudia et al. (2026). Multi-Temporal InSAR and Machine Learning for Geohazard Monitoring: A Systematic Review with Emphasis on Noise Mitigation and Model Transferability . REMOTE SENSING, 18(9), 10.3390/rs18091356

cited authors

  • Alonso-Diaz, Alex; Fontes, Miguel; Teixeira, Ana Claudia; Wdowinski, Shimon; Sousa, Joaquim J

authors

publication date

  • April 28, 2026

published in

keywords

  • DEFORMATION
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • Geology
  • Geosciences, Multidisciplinary
  • Imaging Science & Photographic Technology
  • Interferometric Synthetic Aperture Radar (InSAR)
  • LAND SUBSIDENCE
  • Life Sciences & Biomedicine
  • PS-InSAR
  • Physical Sciences
  • Remote Sensing
  • SBAS
  • SUSCEPTIBILITY
  • Science & Technology
  • Technology
  • atmospheric phase screen
  • deep learning
  • machine learning
  • model transferability
  • multi-temporal InSAR
  • temporal decorrelation
  • time-series forecasting

Digital Object Identifier (DOI)

publisher

  • MDPI

volume

  • 18

issue

  • 9