Monitoring urban expansion using SVM classification approach in Khenifra city (Morocco)

Urban expansion is a major process in developing countries such as Morocco. Since their appearance in the 1970s, digital remote-sensing space sensors have been used to provide images with spatial and spectral resolutions that are adequate to comprehend the phenomenon of urban expansion. Become real tools for cities management and planning, through the many applications. Using Landsat images, we studied Khenifra’s (Moroccan city) urban area evolution and extension to quantify its impact on current landscape. A supervised classification using support vector machines (SVM) was employed to extract the urban state in three periods 1991, 2000 and 2017. The results reveal a clear progression of total occupied urban space from 12% in 2000 until 36% in 2017. This expansion is unevenly distributed in space, and at slightly different rates depending on the period considered. This phenomenon of significant urban expansion is largely related to population growth and the rural exodus.