Mapping of Vegetation Cover using Segment Based Classification of IKONOS Imagery

This study was performed to prove if the high resolution satellite imagery of IKONOS is suitable for preparing digital vegetation map which is becoming increasingly important in ecological science. Seven classes for forest area and five classes for non-forest area were taken for classification. Three methods, such as the pixel based classification, the segment based classification with majority principle, and the segment based classification with maximum likelihood, were applied to classify IKONOS imagery taken in April 2000. As a whole, the segment based classification shows better performance in classifying the high resolution satellite imagery of IKONOS. Through the comparison of accuracies and kappa values of the above 3 classification methods, the segment based classification with maximum likelihood was proved to be the best suitable for preparing the vegetation map with the help of IKONOS imagery. This is true not only from the viewpoint of accuracy, but also for the purpose of preparing a polygon based vegetation map. On the basis of the segment based classification with the maximum likelihood, a digital vegetation map in which each vegetation class is delimitated in the form of a polygon could be prepared.