Articles | Volume 23, issue 2
https://doi.org/10.5194/nhess-23-789-2023
https://doi.org/10.5194/nhess-23-789-2023
Research article
 | 
23 Feb 2023
Research article |  | 23 Feb 2023

Earthquake building damage detection based on synthetic-aperture-radar imagery and machine learning

Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun

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Short summary
This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets including high-resolution building inventories, while also leveraging recent advances in machine-learning algorithms. For three out of the four recent earthquakes studied, the machine-learning framework is able to identify over 50 % or nearly half of the damaged buildings successfully.
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