Automatic Extraction of Built-up Areas Using EOS-04 SAR Data

Earth Observation Satellite-04 (EOS-04) is a SAR satellite launched by ISRO on February 14, 2022. Man-made features like built-up areas appear very bright in the SAR images due to high backscatter. This study outlines a methodology framework for the EOS-04 SAR data for automatic extraction of built-up areas. The built-up areas are extracted using the speckle divergence algorithm in single and quad polarization data of the EOS-04 SAR satellite. In quad polarization data, Yamaguchi decomposition with extended volume scattering (S4R) has been done and speckle divergence algorithm has been applied to the Helix component for extracting built-up areas. The detection performance has been assessed and the built areas are extracted with an overall accuracy of 76% to 92%.

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Publication Details

Published
2024-12-02
DOI
https://doi.org/10.1109/ingarss61818.2024.10983973
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
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article

Automatic Extraction of Built-up Areas Using EOS-04 SAR Data

Ashish Dutta, Ashish Joshi
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Automatic Extraction of Built-up Areas Using EOS-04 SAR Data

Ashish Dutta, Ashish Joshi
article en

Abstract

Earth Observation Satellite-04 (EOS-04) is a SAR satellite launched by ISRO on February 14, 2022. Man-made features like built-up areas appear very bright in the SAR images due to high backscatter. This study outlines a methodology framework for the EOS-04 SAR data for automatic extraction of built-up areas. The built-up areas are extracted using the speckle divergence algorithm in single and quad polarization data of the EOS-04 SAR satellite. In quad polarization data, Yamaguchi decomposition with extended volume scattering (S4R) has been done and speckle divergence algorithm has been applied to the Helix component for extracting built-up areas. The detection performance has been assessed and the built areas are extracted with an overall accuracy of 76% to 92%.

Indian Institute of Remote Sensing (IN)
Openalex Percentile: Top 51%
Synthetic Aperture Radar (SAR) Applications and Techniques
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