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Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake

Interferometric synthetic aperture radar (InSAR) is a useful tool for detecting surface deformations at high spatial resolutions. When InSAR is applied to large surface deformations, clear fringes with complicated phase gaps often appear in the interferograms. Although the surface deformations in su...

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Published in:Earth, planets, and space planets, and space, 2022-05, Vol.74 (1), p.1-11, Article 72
Main Authors: Ozawa, Taku, Himematsu, Yuji
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description Interferometric synthetic aperture radar (InSAR) is a useful tool for detecting surface deformations at high spatial resolutions. When InSAR is applied to large surface deformations, clear fringes with complicated phase gaps often appear in the interferograms. Although the surface deformations in such areas provide valuable data for earthquake research and disaster investigation, it is difficult to convert the complicated interferometric phase to surface deformation information because of the difficulties associated with phase unwrapping. To resolve these difficulties, we created multiple SAR pairs with different frequencies using a bandpass filter and calculated the difference between the interferograms generated from these SAR pairs (referred to as the DSI analysis in this study). Generally, the obtained difference corresponds to SAR observations using long-wavelength radar. Therefore, phase wrap is less likely to occur, simplifying phase unwrapping. We applied the DSI analysis to PALSAR-2 data pairs for the 2016 Kumamoto Earthquake and successfully identified large crustal deformations with complicated phase gaps in the vicinity of the surface ruptures. Comparing these results with the crustal deformations observed with global navigation satellite system measurements, the root-mean-squares of the differences were found to be approximately 4 cm. Although this accuracy was lower than that of conventional InSAR, it was nearly equivalent to that of offset-tracking analysis. It should be noted that the spatial resolution of the DSI analysis was significantly improved compared to that of offset-tracking analysis. A disadvantage of this method is that its detection accuracy is significantly degraded in zones with low coherence owing to noise amplification. The standard deviation of the noise component was approximately 2 cm for pixels with coherence > 0.7. However, for pixels with a coherence  10 cm, and the noise component occasionally exceeded 1 m. Despite its disadvantages, this method is effective for detecting large crustal deformations with high spatial resolution in areas where conventional InSAR processing is inappropriate. Graphical Abstract
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When InSAR is applied to large surface deformations, clear fringes with complicated phase gaps often appear in the interferograms. Although the surface deformations in such areas provide valuable data for earthquake research and disaster investigation, it is difficult to convert the complicated interferometric phase to surface deformation information because of the difficulties associated with phase unwrapping. To resolve these difficulties, we created multiple SAR pairs with different frequencies using a bandpass filter and calculated the difference between the interferograms generated from these SAR pairs (referred to as the DSI analysis in this study). Generally, the obtained difference corresponds to SAR observations using long-wavelength radar. Therefore, phase wrap is less likely to occur, simplifying phase unwrapping. We applied the DSI analysis to PALSAR-2 data pairs for the 2016 Kumamoto Earthquake and successfully identified large crustal deformations with complicated phase gaps in the vicinity of the surface ruptures. Comparing these results with the crustal deformations observed with global navigation satellite system measurements, the root-mean-squares of the differences were found to be approximately 4 cm. Although this accuracy was lower than that of conventional InSAR, it was nearly equivalent to that of offset-tracking analysis. It should be noted that the spatial resolution of the DSI analysis was significantly improved compared to that of offset-tracking analysis. A disadvantage of this method is that its detection accuracy is significantly degraded in zones with low coherence owing to noise amplification. The standard deviation of the noise component was approximately 2 cm for pixels with coherence &gt; 0.7. However, for pixels with a coherence &lt; 0.2, the standard deviation was &gt; 10 cm, and the noise component occasionally exceeded 1 m. Despite its disadvantages, this method is effective for detecting large crustal deformations with high spatial resolution in areas where conventional InSAR processing is inappropriate. Graphical Abstract</description><identifier>ISSN: 1880-5981</identifier><identifier>ISSN: 1343-8832</identifier><identifier>EISSN: 1880-5981</identifier><identifier>DOI: 10.1186/s40623-022-01635-0</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>6. 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When InSAR is applied to large surface deformations, clear fringes with complicated phase gaps often appear in the interferograms. Although the surface deformations in such areas provide valuable data for earthquake research and disaster investigation, it is difficult to convert the complicated interferometric phase to surface deformation information because of the difficulties associated with phase unwrapping. To resolve these difficulties, we created multiple SAR pairs with different frequencies using a bandpass filter and calculated the difference between the interferograms generated from these SAR pairs (referred to as the DSI analysis in this study). Generally, the obtained difference corresponds to SAR observations using long-wavelength radar. Therefore, phase wrap is less likely to occur, simplifying phase unwrapping. We applied the DSI analysis to PALSAR-2 data pairs for the 2016 Kumamoto Earthquake and successfully identified large crustal deformations with complicated phase gaps in the vicinity of the surface ruptures. Comparing these results with the crustal deformations observed with global navigation satellite system measurements, the root-mean-squares of the differences were found to be approximately 4 cm. Although this accuracy was lower than that of conventional InSAR, it was nearly equivalent to that of offset-tracking analysis. It should be noted that the spatial resolution of the DSI analysis was significantly improved compared to that of offset-tracking analysis. A disadvantage of this method is that its detection accuracy is significantly degraded in zones with low coherence owing to noise amplification. The standard deviation of the noise component was approximately 2 cm for pixels with coherence &gt; 0.7. However, for pixels with a coherence &lt; 0.2, the standard deviation was &gt; 10 cm, and the noise component occasionally exceeded 1 m. Despite its disadvantages, this method is effective for detecting large crustal deformations with high spatial resolution in areas where conventional InSAR processing is inappropriate. Graphical Abstract</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1186/s40623-022-01635-0</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-2040-6572</orcidid><oa>free_for_read</oa></addata></record>
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subjects 6. Geodesy
Artificial satellites in remote sensing
Bandpass filters
Coherence
Crustal deformation
Deformation effects
Deformations (Mechanics)
Difference of split-band interferograms
DSI
Earth and Environmental Science
Earth Sciences
Earthquakes
Express Letter
Geology
Geophysics/Geodesy
Global navigation satellite system
InSAR
Interferometric synthetic aperture radar
Interferometry
Japan
Navigation satellites
Navigation systems
Noise
Noise standards
Observations
Phase unwrapping
Pixels
Radar
Satellite observation
Seismic activity
Spatial resolution
Standard deviation
Synthetic aperture radar
Synthetic aperture radar interferometry
The 2016 Kumamoto Earthquake
Tracking
title Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto Earthquake
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