近年来, 随着遥感平台和传感器的发展, 已经实现了对地球表面大部分区域的连续重复遥感观测, 积累了海量的多源、 多尺度、 多分辨率遥感数据。 这些数据详细记录了地表上各种地物的变化过程, 使得基于遥感影像的中长期变化检测等全球变化研究成为可能, 并极大地推动了遥感影像处理方法和应用的研究。 但是, 尽管许多学者已经开展了大量相关的研究工作, 目前基于多时相遥感影像的变化检测仍然面临许多挑战, 还没有形成相对完整、 成熟的理论体系, 对相关研究进展的系统性总结工作仍然相对缺乏。 回顾了多时相遥感变化检测方法的发展现状, 并根据输入数据类型和数量的不同将这些方法分成单时相分类比较法、 双时相比较法和时序分析法三类, 对其进展情况和特点分别进行总结分析, 然后就多时相遥感影像变化检测方法研究中现存的问题加以分析, 并尝试探讨了其发展趋势。

With the development of platforms and sensors, continuous repetition of remote sensing observation of the earth surface has been realized, and a mass of multi-source, multi-scale, multi-resolution remote sensing data has been accumulated. Those images have detailedly recorded the changing process of ground objects on the earth, which makes the long term global change research, such as change detection, based on remote sensing become possible, and greatly push forward the research on image processing and application. Although plenty of successful research has been reported, there are still enormous challenges in multi-temporal imagery change detection. A relatively complete mature theoretical system has not formed, and there is still a lack of systematic summary of research progress. Firstly, the current progress in change detection methods using multi-temporal remotely sensed imagery has been reviewed in this paper. Then, the methods are classified into three categories and summarized according to the type and amount of the input data, single-phase post-classification comparison, two-phase comparison, and time series analysis. After that, the possible existing problems in the current development of multi-temporal change detection are analyzed, and the development trend is discussed finally.