A rapid evaluation method of the seismic damage to buildings based on UAV images

Abstract

With the widespread application of UAVs in post-disaster damage evaluation, feature extraction and analysis based on drone images has become the main trend in seismic assessment. In this research, a fast assessment method that integrates object-oriented 2D classification and 3D assessment is proposed in the paper. Firstly, to segment the regional orthoimage, a multi-scale feature segmentation method is developed to segment the orthoimage of the region and the features are selected based on the attributes of ground objects. Meanwhile, a two-stage object-oriented hierarchical classification method is put forward to establish partition rules at different levels. The classification method takes the overall attributes of the object into account which reduces the amount of data correspondingly resulting in much higher efficiency and accuracy of feature extraction than the pixel-based method. In addition, the integrity of building’s top texture after classification is used as the first criterion to assess building seismic damage. Besides, a 3D elevation analysis method based on regional normalized digital surface model (nDSM) is developed by comparing digital surface model with digital elevation model to serve as the second criterion for determining the vertical changes in building. The proposed method is validated by a field test at the Beichuan earthquake site with an accuracy rate of 86.95 %. The experimental results show that the proposed method can meet the accuracy requirement of seismic assessment and has a high application value in the field of regional disaster evaluation.