Land Cover Change Detection based on Homology Theory

We exploit homology theory (HT) for land cover change detection in remote sensing. Shape disclosure is achieved through the Vietoris-Rips simplicial complex constructor. We propose to use persistent homology to overcome the land cover change detection problem in remote sensing. Qualitative Features (Betti numbers) are computed from a series of simplicial complexes at each level of resolution. Local structures are unfolded gradually throughout the observation sequence generated from a pixel in the input image at two different points in time. The weighted Bottleneck distance is used to detect the change satellite images. Experimental results demonstrate the efficiency of our methodology when compared to some major state-of-the-art approaches.