Overview of Remote Sensing Image Change Detection

Remote sensing enables large-scale, non-contact observation of the Earth’s surface and plays a vital role in disaster response, environmental monitoring, and national security. As a core task in remote sensing interpretation, change detection identifies temporal changes from multi-temporal images to support dynamic land cover analysis and strategic decision-making. Classical methods based on manual features and statistical modeling often suffer from error propagation, limited representational capacity, poor generalization across complex or heterogeneous scenes. Computational intelligence, particularly deep learning, has proven to be an effective and efficient solution for overcoming these limitations. This chapter provides a systematic review of remote sensing image change detection, covering both the research background and the evolution of methods.