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OBJECT BASED CLASSIFICATION TECHNIQUES IN URBAN CHANGE PLANNING

Rapid growing of population, a reliable solution is essential to monitor the changes and make the digital map revised. The need of fast decision making and complete control on problems is one of the biggest disturbances of organizers that necessitate the use of up to date information. Most traditional pixel-based classifications are based on the digital number of each pixel. The high spatial resolution images provide more details such as color, size, shape and texture. So the object-oriented processing become of interest. This paper focuses on an automatic change detection method based on object based classification techniques. The first step of the object-oriented processing is the segmentation. Next the object based classification with use of spectral, textural and structural parameters will be used to classify the imagery. Lastly Some Structural Rules such as the ratio of areas and Homogeneity parameters are used to compare the classification image objects and the old digital map to detect the changes. The proposed methodology was tested on a 1:2000 scale digital map of the city of Qom in Iran by using Quick Bird scenes. The visual investigation and the accuracy assessment of the obtained results demonstrate the high capability of this method.