This paper presents results of object-oriented classification of Landsat ETM+ satellite im-age conducted using eCognition software. The classified image was acquired on 7 May 2000. In this particular study, an area of 423 km2 within the borders of Legionowo Community near Warsaw is considered.

Prior to classification, segmentation of the Landsat ETM+ image is performed using panchro-matic channel, fused multispectral and panchromatic data. The applied methods of classification en-abled the identification of 18 land cover and land use classes. After the classification, generalization and raster to vector conversion, verification and accuracy assessment are performed by means of vis-ual interpretation. Overall accuracy of the classification reached 94.6%. The verification and classifi-cation results are combined to form the final database.

This is followed by comparing the object-oriented with traditional pixel-based classification. The latter is performed using the so-called hybrid classification based on both supervised and unsuper-vised classification approaches. The traditional pixel-based approach identified only 8 classes. Com-parison of the pixel-based classification with the database obtained using the object-oriented ap-proach revealed that the former reached 72% and 61% accuracy, according to the applied method.