Application of Multi-Sensor Images to Improve the Capabilities of PSI (Persistent Scatterer Interferometry)
Doctoral Candidate: Maria C. Ramlie
Supervisor: Michele Crossetto
Host institution: CTTC
Output type: literature review and summary research topic
Research Questions:
1. How to mitigate the common problems with PSI techniques such as vegetation?
2. How to improve the accuracy of PSI technique when it comes to ground deformation monitoring?
3. How will this technique perform in terms of geo-energies related project and other cases that involves ground deformation such as landslide?
Brief Summary of Research:
PSI (Persistent Scatterer Interferometry) is a very powerful remote sensing method that utilizes the Persistent Scatterer by exploiting multiple images captured by SAR (Synthetic Aperture Radar). The technique can detect millimeter scale of ground deformation, making it ideal for every projects or cases that requires effective and efficient monitoring. While it aims to be generally used for every case that involves ground deformation, in this project the main concentration is on geo-energy projects. Geo-energy often imply injecting (and/or extracting) fluids into (from) the subsurface and by this information we know that movement or deformation will occur. There is a phenomena called induced seismicity, that has been detected in some geo-energy projects.
However, PSI can still encounter some issues that can affect the accuracy. Major issue of this technique is the vegetation cover. Usually, there are fewer persistent scatterer that can be detected in heavily vegetated areas. This can be mitigated by using X-band sensor, considered a high resolution sensor. Another aspect that can improve the accuracy of PSI is by having a large set of data.
With this idea in mind, this research proposes a technique to combine multiple images that sourced from different sensors such as Sentinel-1, TerraSAR-X, COSMO-SKYMED, NISAR, and SAOCOM. This is not an easy feat as these sensors provide different properties, example the band and wavelength of Sentinel-1 (C-band) versus TerraSAR-X (X-band). This requires attention and priority to be able to combine the images. Successfully implementing this technique could improve ground deformation monitoring , offering more insights for a wide range of applications. This technique could also lead to a better monitoring and management ground monitoring related projects, ensuring their safety, efficiency, and awareness. Through continued research and collaboration, we can unlock the full potential of this innovative approach, driving progress towards a more sustainable and resilient future.
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