Study on the behaviour of BBO over natural terrain features

In recent years the remote sensing image classification has become a global research area for acquiring the geo-spatial information from satellite data. In this paper we have tried to explore the behavior of Biogeography-Based Optimization (BBO) over different terrain features of a satellite image. The findings of recent studies are showing strong evidence to the fact that various classifiers perform differently when applied to images having different natural terrain features. BBO has a way of sharing information between solutions depending on the migration mechanisms of ecosystem. The motivation of this paper is to use this feature of BBO for finding more accurate results. The approach followed involves making the clusters of different land cover features. The results indicate that highly accurate Homogeneous land-cover features are extracted when BBO is used, instead of other conventional classifiers.