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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 AL-ZAHRA sub-area. Furthermore, the urban expansion areas on behalf the agricultural areas 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. The increase in spatial resolution from Landsat MSS (80m) to Landsat TM (30m), then to SPOT XS (20m) and SPOT Pan (10m); and recently very high resolutions images acquired by SPOT-5 (2.5m), IKONOS (1m) and Quikbird (0.61m) has made it possible to monitor the urban expansion and development at micro level and with a very high accuracy.

Urban expansion and its impacts on agricultural areas in Al-ZAHRA region, Libya using high resolution images