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Center for Research and Application for Satellite Remote Sensing
Yamaguchi University
Differential SAR Interferometry Using
Sentinel-1 Data for Kumamoto Earthquake
Sentinel-1 data
• The Sentinel-1 mission comprises a constellation of two polar-orbiting satellites,
operating day and night performing C-band synthetic aperture radar imaging,
enabling them to acquire imagery regardless of the weather.
• Sentinel-1A images in this material were downloaded in Interferometric Wide (IW)
swath mode derived from the Copernicus Open Access Hub
(https://scihub.copernicus.eu/). This mode is a main acquisition mode of Sentinel-
1A. It covers with 250 kilometers swath at 5 meters by 20 meters spatial resolution
(single look). IW mode captures three sub-swaths using Terrain Observation with
Progressive Scans SAR (TOPSAR).
https://sentinel.esa.int/web/sentinel/missions/sentinel-1
SAR Data
• Master: S1A_IW_SLC__1SSV_20160408T091355_20160408T091430_010728_01001F_83EB
• Slave: S1A_IW_SLC__1SSV_20160420T091355_20160420T091423_010903_010569_F9CE
Source: https://scihub.copernicus.eu/dhus/#/home
Open data
• File → Import → SAR Sensors → SENTINEL-1
Preview images
• Radar → Coregistration → S1 TOPS Coregistration → S1 TOPS Coregistration
Read = master Read(2) = slave
Write output in your directory
Output
S1A_IW_SLC__1SSV_20160408T091355_20
160408T091430_010728_01001F_83EB
S1A_IW_SLC__1SSV_20160420T091355_20
160420T091423_010903_010569_F9CE
• Interferometric → products → Interferogram formation
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
Sentinel-1 TOPS → S-1 TOPS Deburst
Before deburst After deburst
Interferometric → products → Topographic phase removal
Remove topographic phase
Interferometric → Filtering → Goldsten Phase Filtering
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
After filter
Before filter
• Geo-coding → Terrain correction → Range-Doppler Terrain
Correction
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake

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Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake

  • 1. Center for Research and Application for Satellite Remote Sensing Yamaguchi University Differential SAR Interferometry Using Sentinel-1 Data for Kumamoto Earthquake
  • 2. Sentinel-1 data • The Sentinel-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band synthetic aperture radar imaging, enabling them to acquire imagery regardless of the weather. • Sentinel-1A images in this material were downloaded in Interferometric Wide (IW) swath mode derived from the Copernicus Open Access Hub (https://scihub.copernicus.eu/). This mode is a main acquisition mode of Sentinel- 1A. It covers with 250 kilometers swath at 5 meters by 20 meters spatial resolution (single look). IW mode captures three sub-swaths using Terrain Observation with Progressive Scans SAR (TOPSAR). https://sentinel.esa.int/web/sentinel/missions/sentinel-1
  • 3. SAR Data • Master: S1A_IW_SLC__1SSV_20160408T091355_20160408T091430_010728_01001F_83EB • Slave: S1A_IW_SLC__1SSV_20160420T091355_20160420T091423_010903_010569_F9CE Source: https://scihub.copernicus.eu/dhus/#/home
  • 4. Open data • File → Import → SAR Sensors → SENTINEL-1 Preview images
  • 5. • Radar → Coregistration → S1 TOPS Coregistration → S1 TOPS Coregistration
  • 6. Read = master Read(2) = slave Write output in your directory Output S1A_IW_SLC__1SSV_20160408T091355_20 160408T091430_010728_01001F_83EB S1A_IW_SLC__1SSV_20160420T091355_20 160420T091423_010903_010569_F9CE
  • 7. • Interferometric → products → Interferogram formation
  • 10. Sentinel-1 TOPS → S-1 TOPS Deburst
  • 12. Interferometric → products → Topographic phase removal
  • 14. Interferometric → Filtering → Goldsten Phase Filtering
  • 17. • Geo-coding → Terrain correction → Range-Doppler Terrain Correction