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However, some previous methodologies are restricted to using specific radar sensors. Others methods, such as machine learning algorithms, require training data, which are extremely difficult to obtain immediately after a disaster. This paper proposes a novel method to extract collapsed buildings based on the integration of satellite imagery, the spatial distribution of a demand parameter, fragility functions, and a geospatial building inventory. The proposed method is applicable regardless of the type of radar sensor and does not require any training data. The method was applied to extract buildings that collapsed during the 2011 Great East Japan Tsunami. 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