“Multi temporal hyperspectral images are widely used in the field of change detection, but traditional algorithms rely on a large number of labeled samples, resulting in high costs. Experts proposed the JCDSSAN network, which effectively alleviates the problem of sample limitation through multi-scale spectral attention blocks and differential feature guidance strategies. Experimental verification shows that this method is superior to other hyperspectral change detection methods.”