Road extraction plays an important role in urban planning and city extension issues, as well as in road monitoring, traffic management and map updating. Technological advances may offer a wealth of data and techniques that could be implemented in road delineation and extraction, as well as in change detection projects. Among the various methods that have been developed for this purpose, remote sensing techniques and especially digital processing of satellite data could contribute significantly in this direction. This paper presents the study of a road network which concerns the city of Kastoria located in northwestern Greece and its surrounding area. The special character of the road network is closely related to the city’s cultural value which is depicted in its structure. Satellite images of various spatial resolutions were employed for digital processing. Landsat 8 imagery was used in order to detect and delineate the linear features through spatial enhancement, while Landsat 5 images were used to detect changes over time through visual interpretation. Semi-automatic techniques were applied to SPOTmaps products to extract the road network, while an object-oriented approach was applied to QuickBird imagery in order to combine the spatial components with spectral properties. Through semi-automatic digitization and object-oriented workflows, the export of the studied part of the road network in vector format was achieved, thus facilitating the process and reducing the required time. The resulted data are efficient in road network delineation and could be combined with other data for road maintenance and extension, change detection issues, as well as for cultural and touristic purposes.