Mapping and characterization of forest and vegetation are particularly challenging in urban areas. High resolution imagery is needed for mapping and characterization purposes, due to the areal extent of urban forests, parks and recreational areas. Fusion techniques of panchromatic (1m resolution) and multiband (4m resolution) IKONOS data were used for mapping and characterization of land covering characteristics of urban green areas, allowing the identification of parks, tree areas and fields with a minimal mapping unit of 160 m2. Techniques, that integrate the fine details of the input data into the fused image, are used. Experimental results for different image fusion methods (Laplacian, Gradient pyramids, Principal Component Analysis and Wavelet transform) are also demonstrated in order to improve spatial resolution. Classification of urban areas, mapped with fused data, results in higher accuracies than when using a multiband approach with 4 m data alone. Furthermore, high spatial resolution data permitted to obtain new areal extents of green areas of the city, giving a better estimate of international indicators for a suitable green areas policy. Vegetation indexes derived from red and near infrared data IKONOS are used to evaluate vegetation conditions, which, along with their distribution, location and urban context, resulted in better indicators of green areas.