Change detection, a prominent research area in remote sensing, is pivotal in observing and
analyzing surface transformations. Despite significant advancements achieved through
deep learning-based methods, executing high-precision change detection in spatio-
temporally complex remote sensing scenarios still presents a substantial challenge. The
recent emergence of foundation models, with their powerful universality and generalization
capabilities, offers potential solutions. However, bridging the gap of data and tasks remains …