According to the unmanned aerial vehicle aerial image change detection algorithm based on semantic segmentation, an unmanned aerial vehicle is used for shooting the same place in two different time periods to collect image data, an original image is obtained, and the algorithm is characterized by comprising the following steps that S1, making a label coding set; S2, making a training set; S3, training to generate a semantic segmentation network; S4, obtaining two semantic segmentation result images; and S5, obtaining a change detection result. According to the algorithm, the semantic level characteristics of the image are fully utilized, some auxiliary training sets are constructed for training, so that the trained network can learn some generalized characteristics, and the final detectioneffect is higher than that of the traditional manual characteristic. According to the method, the final change result can judge whether the change occurs or not, the change category can be detected,16 change categories can be recognized at present, and some requirements for change detection in actual research problems are better met.