Image change detection is an important application of remote sensing technology. It is a process ascertaining the changes of specific features within a certain time interval. This paper presents an object-oriented image change detection methodology to detect the changes and analyze aerial remote sensing data of Sanaa sub-area. Furthermore, the urban growth (sprawl) in the study area is monitored and analyzed. A rule-based classification technique is applied by using fuzzy functions, aiming to extract information of the urban spatial structure. Finally the classification accuracy of the used images was assessed with parameters of overall accuracy, and kappa statistic.