This content presents how to apply interferometric analysis for damage detection. The case study is the Kumamoto earthquake in 2016. ALOS-2 images are used to calculate interferometric coherence, and estimate coherence change of images between before- and during earthquake to estimate possible degree of damage areas.

1. Center for Research and Application for Satellite Remote Sensing
Yamaguchi University
Earthquake Damage Detection Using
SAR Interferometric Coherence

2. Kumamoto Earthquake
• On 14 April 2016, series of earthquake occurred with 6.2 Mw. foreshock and 7.0 Mw. Mainshock.
The earthquakes affected large area and high number of damaged buildings and infrastructures.

3. • IMG-HH-ALOS2082062950-151130-UBSR1.1__D
• IMG-HH-ALOS2096552950-160307-UBSR1.1__D
• IMG-HH-ALOS2102762950-160418-UBSR1.1__D
• Get DEM from:
• https://topex.ucsd.edu/gmtsar/demgen/
ALOS-2 Images

4. SAR Interferometric Coherence
Correlation of interferogram pair is used to determine the quality of the interferometric measurement
The coherence is defined as the magnitude of the cross-correlation coefficient between two co-registered
complex images
Total decorrelation :
ϒ tot = ϒ Geom + ϒ DC + ϒ Vol + ϒ Thermal + ϒ Temporal + ϒ Process
ϒ Geom Baseline or geometric decorrelation
ϒ DC Dopper centroid
ϒ Vol Volume decorrelation
ϒ Thermal Thermal or system noise
ϒ Temporal Temporal terrain decorrelation
ϒ Process Processing induced decorrelation
ϒ Temporal → shows physical change in the terrain, affecting the scattering characteristics of the surface

5. SAR Interferometric Coherence
For quick response, interferometric coherence is useful and timely to support disaster management.
The interferometric coherence of pre- and co-event can be utilized for damage assessment
Plank, S. (2014). Rapid Damage Assessment by Means of Multi-Temporal SAR — A Comprehensive Review and Outlook to
Sentinel-1. Remote Sensing, 6(6), 4870–4906. https://doi.org/10.3390/rs6064870
ϒ_pre = pre-earthquake SAR image pair
ϒ_co = pre- and a co-earthquake image pair

6. Methodology
Pre-seismic coherence Co-seismic coherence
SAR Image
before earthquake
SAR Image
before earthquake
SAR Image
after earthquake
Damage threshold
Normalized change
Earthquakes
+1
-1
Less damage High damage
To improve visualization,
Optical image can be used for masking out vegetated area using
NDVI and reveal adverse impact on building area
Moreover, multi-temporal coherence can improve quality of result.

7. GMTSAR Installation
https://melihatbumi.files.wordpress.com/2017/10/how-to-install-
gmtsar.pdf
https://github.com/gmtsar/gmtsar/wiki

8. InSAR processing in GMTSAR
Use “p2p_ALOS2_SLC.csh” in GMTSAR

9. File preparing for GMTSAR processing

10. Pre-seismic interferometric results
Interferogra
m
Unwrap LOS Amplitude Coherence

11. Co-seismic interferometric results
Interferogra
m
Unwrap LOS Amplitude Coherence

12. Estimated damage area by coherence change in QGIS
1) Rename files
Rename “corr_ll.grd” of pre-seismic pair to “pre-seismic_corr” (.grd or tiff)
Rename “corr_ll.grd” of co-seismic pair to “co-seismic_corr” (.grd or tiff)
2) Open QGIS and add these files
3) Use raster calculator for normalized coherence change

13. Google earth image

14. Pre-seismic coherence

15. Co-seismic coherence

16. Normalized coherence change
Use raster calculator for
normalized coherence
change
( "pre-seismic_corr@1" - "co-seismic_corr@1" ) / ( "pre-seismic_corr@1" + "co-seismic_corr@1" )

17. Colorized analyzed result
+1
-1
Less damage High damage

19. Colorized analyzed result
To improve visualization, pre-seismic coherence and optical image (NDVI) can be used for masking out
vegetated area and reveal adverse impact on building area.
More information: https://www.mdpi.com/2220-9964/6/7/188/htm
+1
-1
Less damage High damage
non-building (mask low pre-
seismic out)
Vegetated area (by NDVI)