Operational earthquake-induced building damage assessment using CNN-based direct remote sensing change detection on superpixel level

• Published in: International journal of applied earth observation and geoinformation Vol. 112; p. 102899
• Main Authors: Qing, Yuanzhao, Ming, Dongping, Wen, Qi, Weng, Qihao, Xu, Lu, Chen, Yangyang, Zhang, Yi, Zeng, Beichen
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2022; Elsevier
• Subjects: Building damage detection and assessment; case studies; Convolutional neural network; Direct change detection; disaster preparedness; Earthquake damage index; earthquakes; geophysics; neural networks; Remote sensing; spatial data; Building damage detection and assessment; Convolutional neural network; Remote sensing; Direct change detection; Earthquake damage index

•Superpixel-based direct change detection is capable of finding damages efficiently.•Extra feature enhancement bands accelerate the process of damage assessment.•Channel-expanded CNN model benefits simultaneous building damage analysis.•The potential of the proposed method in post-earthquake emergen...