Comparison of Pixel-based and Object-oriented Classification Approaches Using Landsat-7 Etm Spectral Bands

In this study, land cover types in Zonguldak test area were analysed on the basis of the classification results acquired using the pixelbased and object-oriented image analysis approaches. Landsat-7 ETM with 6 spectral bands was used to carry out the image classification and ground truth data were collected from the available maps, aerial photographs, personal knowledge and communication with the local people. In pixel-based image analysis, firstly unsupervised classification based ISODATA algorithm was realised to provide priori knowledge on the possible candidate spectral classes exist in the experimental area. Then supervised classification was performed using the three different approaches of minimum-distance, paralellepiped and maximum-likelihood. On the other hand, object-oriented image analysis was evaluated through the eCognition software. During the implementation, several different sets of parameters were tested for image segmentation and nearest neigbour was used as the classifier. Outcome from the classification works show that the object-oriented approach gave more accurate results (including higher producer’s and user’s accuracy for most of the land cover classes) than those achieved by pixel-based classification algorithms. * Corresponding author.