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Monitoring Subsidence Area with the Use of Satellite Radar Images and Deep Transfer Learning.

Sensors (Basel, Switzerland)·2022
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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
PubMed
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.

Keywords:
circlet transformellipse detectionsubsidence troughs

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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.