Dynamic Model of Blended Biogeography Based Optimization for Land Cover Feature Extraction

Abstract

This paper presents a dynamic model of the blended biogeography based optimization (BBO) for land cover feature extraction. In the blended BBO, the habitats represent the candidate problem solutions and the species migration represents the sharing of features (SIVs) between candidate solutions according to the fitness of the habitats which is called their HSI value [9]. However, it is assumed that these SIVs i.e. the number of solution features, remain constant for every habitat [10] and the HSI for each habitat depends only on the immigration and the emigration rates of species [9]. This paper extends the blended BBO by considering the fact that the no. of SIVs or the decision variables may not remain constant for all candidate solutions (habitats) that are part of the Universal habitat. Since the characteristics of each habitat vary greatly hence, comparing all the habitats using the same set of SIVs may be misleading and also may not lead to an optimum solution. Hence, in our dynamic model, we consider the fact that HSI of a solution is affected by factors other than migration of SIVs i.e. solution features, also. These other factors can be modeled as several definitions of HSI of a habitat, each definition based on a different set of SIVs which simulates the effect of these other factors. We demonstrate the performance of the proposed model by running it on the real world problem of land cover feature extraction in a multi-spectral satellite image.