Abstract
Earthquakes are natural disasters that cannot be determined precisely where and when they will occur. In cases where precautions are insufficient, large losses of life and property can occur. Minimizing the loss of life after an earthquake depends on the rapid identification of collapsed structures and the urgent delivery of rescue teams to heavily damaged structures. Within the scope of the study, damaged and destroyed buildings were automatically detected in a very short time after the earthquake by using the LiDAR point cloud data obtained with a single period flight and the cadastral map of the region. With the algorithm produced, the robust, damaged and destroyed building classes were detected with 98.98% and 98.56% accuracy rates by considering 3D geometric changes in two different study areas. After obtaining LiDAR data, the detection of damaged and collapsed buildings can be performed within two hours. These findings demonstrate the potential of the proposed approach to effectively detect damaged and destroyed buildings after a disaster. The map of damaged and collapsed buildings after the earthquake is produced without being dependent on radiometric changes. This process is carried out in a very short time with a high accuracy rate, which reveals the superiority of the study compared to the literature. The studies conducted with satellite images without 3D analysis capabilities, it is not possible to detect collapsed buildings with undamaged roofs. In contrast, the proposed LiDAR-based method can detect such damaged structures with high accuracy. The method accelerates the planning and implementation of post-earthquake rescue and relief operations. In addition, the fact that it can prevent loss of life due to late interventions increases the importance of the proposed study.
Published Version
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