The image pre-processing and data preparation were carried out; these included image rectification and mosaicking. The image-to-map procedures were applied to the "IKONOS Pan sharpened" images using set of ground control point’s area that appeared in the same place, both in the imagery and known locations in corresponding map and urban plan used as ancillary information in the rectification process. The rectified datasets were then mosaicked thus producing the entire study area from 1 set of the raw IKONOS data and 20 sets of Spot-5 images as supported data (Figure 2).Image classification was then applied to the pre-processed image and the land use classes map of the entire study area was produced. Supervised classifications techniques were chosen for this study, which was performed using object-based classifier in e-Cognition software system. The system enabled all fine details of the land cover to be classified and later merged accordingly to form the classes in accordance to urban land use classes used in urban planning practice.