The traditional spectral-based remote sensing image change detection methods usually adopt spectral mean, brightness, standard deviation and other features for difference calculation. However, these features have a certain degree of correlation, resulting in a lot of false detection of change detection results, and the selection of threshold has a greater impact on the change detection results. The traditional detection methods using spectral features are mostly based on pixels, and the detection results have salt and pepper phenomenon. In order to solve these problems, an object-oriented spectral component substitution change detection method is proposed, which mainly uses the single-band spectrum of two-phase images for combination substitution, so as to highlight the change information. The change information is extracted by classification method. The experimental results show that the change detection accuracy of proposed method can reach 86%. The proposed method is simple and effective, and it can effectively assist land use change monitoring, geographical and national conditions cover change monitoring and other production projects.