期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B4
页码：1118-1122
出版社：Copernicus Publications
摘要：In this study, land cover types in Zonguldak test area were analysed on the basis of the classification results acquired using the pixel- based 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
关键词：Remote Sensing; Land Cover; Classification; Landsat; Multispectral
