Applying fused multispectral and panchromatic data of Landsat

The article presents results of object oriented classification of Landsat ETM+ satellite image using fused multispectral and panchromatic data. Channels 2, 3 and 4 of the ETM+ image have been fused by applying PanSharp automatic algorithm (PCI Geomatica software) which preserves spectral characteristics of multispectral channels. Object oriented classification has been performed using eCognition software. On the basis of original and fused data, the rules of segmentation have been specified. Next, identification of land use and land cover classes has been tested. Mean values, standard deviations, ratio parameters of the objects, as well as Haralick texture functions have been analysed. Using membership functions and Standard Nearest Neighbor classification, 18 land use classes has been defined and classified. Panchromatic channel has been used for the purposes of recognition of built-up areas, as well as for extraction of the mixed forest class from broad-leaved and coniferous forest. Performed work has demonstrated that fused multispectral and panchromatic data do not have significant influence on the improvement of land use classes separation during classification process, but they are useful for satellite image segmentation process.