Biogeography based land cover feature extraction

Recent developments in applied and heuristic optimization methods used for feature extraction from satellite images have been strongly influenced and inspired by natural and biological system. The findings of recent studies are showing strong evidence to the fact that some aspects of the biogeography can be applied to solve specific problems in science and engineering. The algorithm based on this paradigm, Biogeography Based Optimization is investigated in this paper by applying it to detect various features from multi-source satellite images. This algorithm is based on the geographical distribution of biological organisms. It is modeled after the immigration and emigration of species between islands in search of more friendly habitats. The original BBO algorithm does not have the inbuilt property of clustering. However, in this paper we have introduced a modified BBO algorithm. This recent and novel approach is used to make the clusters of different land cover features. The results indicate that highly accurate land-cover features can be extracted effectively when BBO is used, instead of other conventional classifiers.