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Automatic Subsidence Troughs Detection in SAR Interferograms Using Circlet Transform
Justyna Bała1, Maciej Dwornik1, Anna Franczyk1
1Department of Geoinformatics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland.
Sensors (Basel, Switzerland)
|April 3, 2021
Summary
A new circlet transform method automatically detects subsidence troughs in satellite radar images. This automated approach is 20% more effective than traditional Hough transform methods for identifying these geological features.
Area of Science:
- Geosciences
- Remote Sensing
- Geophysics
Background:
- Subsidence trough detection is crucial for monitoring ground deformation.
- Traditional methods like the Hough transform have limitations in accuracy and automation.
Purpose of the Study:
- To present an automated method for detecting subsidence troughs using synthetic aperture radar (SAR) interferograms.
- To evaluate the effectiveness of the circlet transform for this application.
Main Methods:
- The study utilizes the circlet transform, which analyzes image gradients directly.
- The method is adaptable to non-circular or fragmented shapes, unlike traditional circle detection algorithms.
- Processing is automated, eliminating the need for segmentation or edge detection.
Main Results:
- The circlet transform method demonstrated a 20% higher detection effectiveness compared to the Hough transform.
- The method successfully identified subsidence troughs in a differential interferogram from the Upper Silesian Coal Basin.
Conclusions:
- The proposed circlet transform offers a more reliable and efficient automated solution for subsidence trough detection.
- This advancement improves the monitoring of ground deformation using SAR data.
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