Mapping Highly Heterogeneous Impervious Surface in the Urban-Rural Fringe using Integrated Hard and Soft Classification from Incorporating Spectral and Texture Features

Abstract

In this paper, an innovative method of integrating hard and soft classification, extended support vector machines, is introduced to map impervious surface in urban-rural fringe area, where is experiencing dramatic land cover change. The proposed method incorporates the variance texture information as an effective indicator to represent the heterogeneity of urban-rural fringe and possesses the merits of hard and soft classification to map both pure pixels and mixed pixels of impervious surface. The better performance compared with conventional hard and soft method was demonstrated in urban-rural fringe area, Beijing.