High accelerating rate of the urban changes and the urban area growth especially in developing countries calls for efficient and fast techniques for map revision and updating with required accuracy. Updating of outdated maps are today laborious task, long, no exempt of errors and several years separate map versions. The availability of QuickBird images with 0.6 m panchromatic and 2.4 m multispectral opened a new era heralding a promising future for producing and updating of large scale digital map. Because in this images details of buildings, shadows, roads, vehicles, individual trees, and even aggregates of people are visible. The goal of this paper is to present cartographic updating using satellite images based on utilisation of change detection techniques. We compare between two methods of change detection and map updating firstly, updating directly from rectified image using visual change detection and manual updating, secondly, updating from classified image(automatic change detection) .comparison was made between the various techniques of classification weather unsupervised classification or supervised classification such as Maximum likelihood classification algorithm, Minimum Distance classification technique, Mahalanobis distance, feature space. The obtained results are tabulated and analyzed and the best one which is the Maximum likelihood was then used for updating.
It is important to consider and evaluate questions such as area dimension, methodology ,quickness and easily, updating quality in order to show should one chose the manual approach or automatic approach?.
The amount or percentage of features added or disturbed on the surface, plus their rate of change may assist in the selection of the method of change detection. It was found that the time used for on screen digitizing was less than for classification but for large areas and bigger database on screen digitizing will not be suitable and will need more time .In this case classification is much faster