AI-Enhanced Synthetic Aperture Radar Imaging with Denoising and Super-Resolution for Coastal Protection
This project aims to develop physics-informed AI methods that reduce noise and sharpen satellite synthetic aperture radar (SAR) imagery, revealing fine-scale 3D features while preserving the accuracy needed for coastal science.
The protective performance of mangroves, seagrass beds and living shorelines depends on their 3D structure, density and changes over time. Ground surveys provide accurate measurements but cover limited areas, while current satellite radar cannot reliably distinguish fine layers such as the canopy, sub-canopy and ground. This makes it difficult to monitor dynamic coastal systems at the scale and frequency needed.
Research Approach
- The project will curate coastal datasets that combine SAR imagery,
optical satellite data and in-situ measurements for model
development and testing. - Physics-informed AI models will denoise imagery, improve
horizontal and vertical resolution and distinguish canopy,
sub-canopy and ground layers without sacrificing physical
accuracy. - Enhanced observations from multiple sensors will track
structural change and support assessments of wave
attenuation, sediment stabilisation and tidal dynamics.
Why This Matters
- Enables wider-area, all-weather and near-real-time monitoring
of nature-based and hybrid coastal protection. - Reveals small but important changes that conventional
satellite products or occasional field surveys may miss. - Gives planners stronger evidence to assess performance and
adapt coastal protection strategies over time.
Meet the Team
Meet the team behind the AI-Enhanced Synthetic Aperture Radar Imaging with Denoising and Super-Resolution for Coastal Protection project.
Principal Investigator (PI):
Dr Cheng Jun
Agency for Science, Technology
and Research (A*STAR),
Institute of Advanced Intelligence
and Computing (IAIC)
Download CFI's project booklet for more information on each project
CFI Singapore Tranche 1 and 2
If you wish to reach out regarding a specific project, please email CFI Singapore at cfisg@nus.edu.sg