Subpixel mapping of urban built-up areas using spatial-spectral information from satellite multispectral remote sensing imagery

Abstract

ABSTRACTA novel method for subpixel mapping of urban built-up areas (SMUBA) using spatial-spectral information from satellite multispectral remote sensing imagery is proposed. SMUBA contains two terms, a spatial term and a spectral term. First, a spatial attraction model is used to produce the spatial term. The Normalized difference built-up index is then utilized to obtain the spectral term. Finally, a particle swarm optimization algorithm is used to optimize the two terms and obtain the final mapping result. Since the spatial-spectral information of the urban built-up areas from multispectral imagery is fully utilized by the two terms, the final mapping result is improved. Experimental results on two Landsat 8 Operational Land Imager data show that SMUBA produces better mapping results than state-of-the-art subpixel mapping methods. Moreover, the proposed method does not need any prior shape information.