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Damage detection using high-resolution SAR imagery in the 2009 L'Aquila, Italy, earthquake

Pralhad Uprety, Fumio Yamazaki and Fabio Dell'Acqua
Damage detection using high-resolution SAR imagery in the 2009 L'Aquila, Italy, earthquake
Earthquake Spectra (November 2013) 29 (4): 1521-1535

Abstract

Satellite remote sensing is being used to monitor disaster-affected areas for post-disaster reconnaissance and recovery. One of the special features of Synthetic Aperture Radar (SAR) is that it can operate day and night and penetrate the cloud cover because of which it is being widely used in emergency situations. Building damage detection for the 6 April 2009 L'Aquila, Italy, earthquake was conducted using high-resolution TerraSAR-X images obtained before and after the event. The correlation coefficient and the difference of backscatter coefficients of the pre- and post-event images were calculated in a similar way as Matsuoka and Yamazaki (2004). The threshold value of the correlation coefficient was suggested and used in detecting building damage. The results were compared with ground truth data and a post-event optical image. Based on the study, building damage could be observed in an urban setting of L'Aquila with overall accuracy of 89.8% and Kappa coefficient of 0.45.


ISSN: 8755-2930
EISSN: 1944-8201
Serial Title: Earthquake Spectra
Serial Volume: 29
Serial Issue: 4
Title: Damage detection using high-resolution SAR imagery in the 2009 L'Aquila, Italy, earthquake
Affiliation: Chiba University, Department of Urban Environment System, Chiba, Japan
Pages: 1521-1535
Published: 201311
Text Language: English
Publisher: Earthquake Engineering Research Institute, Berkeley, CA, United States
References: 30
Accession Number: 2021-002093
Categories: SeismologyApplied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 1 table
N42°21'00" - N42°21'00", E13°24'00" - E13°24'00"
Secondary Affiliation: University of Pavia, ITA, Italy
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2020, American Geosciences Institute. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 2021
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