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
Abstract 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 deformati...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-05-01
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| Series: | Earth, Planets and Space |
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| Online Access: | https://doi.org/10.1186/s40623-022-01635-0 |
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| author | Taku Ozawa Yuji Himematsu |
| author_facet | Taku Ozawa Yuji Himematsu |
| author_sort | Taku Ozawa |
| collection | DOAJ |
| description | Abstract 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 < 0.2, the standard deviation was > 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 |
| first_indexed | 2024-12-12T12:49:41Z |
| format | Article |
| id | doaj.art-aa1bc627d8bb496da8c410fcf7800f73 |
| institution | Directory Open Access Journal |
| issn | 1880-5981 |
| language | English |
| last_indexed | 2024-12-12T12:49:41Z |
| publishDate | 2022-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Earth, Planets and Space |
| spelling | doaj.art-aa1bc627d8bb496da8c410fcf7800f732022-12-22T00:24:01ZengSpringerOpenEarth, Planets and Space1880-59812022-05-0174111110.1186/s40623-022-01635-0Impact of crustal deformation detection by the DSI (difference of split-band interferograms) method with PALSAR-2 data: a case study on the 2016 Kumamoto EarthquakeTaku Ozawa0Yuji Himematsu1National Research Institute for Earth Science and Disaster ResilienceNational Research Institute for Earth Science and Disaster ResilienceAbstract 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 < 0.2, the standard deviation was > 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 Abstracthttps://doi.org/10.1186/s40623-022-01635-0DSIDifference of split-band interferogramsInSARCrustal deformationThe 2016 Kumamoto Earthquake |
| spellingShingle | Taku Ozawa Yuji Himematsu 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 Earth, Planets and Space DSI Difference of split-band interferograms InSAR Crustal deformation The 2016 Kumamoto Earthquake |
| 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | DSI Difference of split-band interferograms InSAR Crustal deformation The 2016 Kumamoto Earthquake |
| url | https://doi.org/10.1186/s40623-022-01635-0 |
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