Bruno Adriano is currently a postdoctoral researcher at Geoinformatics Unit, the RIKEN Center for Advanced Intelligence Project (AIP), Japan. His research is focused on the fusion of remote sensing technologies and high-performance numerical simulation for disaster management.
He is a member of the Japan Society of Civil Engineers JSCE (2013) and the IEEE (2014).
|2018 Jun||-||Present||Postdoctoral Researcher, RIKEN AIP, Japan|
|2016 Apr||-||2018 Mar||JSPS Research Fellow, Tohoku University, Japan|
|2013 Apr||-||2016 Mar||Ph.D. in Civil Engineering, Tohoku University, Japan|
S. Karimzadeh, M. Matsuoka, M. Miyajima, B. Adriano, A. Fallahi, and J. Karashi,
Sequential SAR Coherence Method for the Monitoring of Buildings in Sarpole-Zahab, Iran
Remote Sensing, vol. 10, no. 8, pp. 1255, 2018.
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Abstract: In this study, we used fifty-six synthetic aperture radar (SAR) images acquired from the Sentinel-1 C-band satellite with a regular period of 12 days (except for one image) to produce sequential phase correlation (sequential coherence) maps for the town of Sarpole-Zahab in western Iran, which experienced a magnitude 7.3 earthquake on 12 November 2017. The preseismic condition of the buildings in the town was assessed based on a long sequential SAR coherence (LSSC) method, in which we considered 55 of the 56 images to produce a coherence decay model with climatic and temporal parameters. The coseismic condition of the buildings was assessed with 3 later images and normalized RGB visualization using the short sequential SAR coherence (SSSC) method. Discriminant analysis between the completely collapsed and uncollapsed buildings was also performed for approximately 700 randomly selected buildings (for each category) by considering the heights of the buildings and the SSSC results. Finally, the area and volume of debris were calculated based on a fusion of a discriminant map and a 3D vector map of the town.