Maintenance of spatial data with photointerpretation is very demanding in terms of time and personnel, therefore tendencies of data owners for the automation of this process are very high. Despite extensive research on automatic extraction of spatial data, these methods are still not in practical use.
In the thesis, I examined the possibility of using object-based image analysis for extraction of the built-up areas with remote sensing data. An analysis of the impact of spatial, spectral and temporal resolution, image filtering and transformation on the quality of object-based image analysis, has been carried out. Based on the results of the analysis the optimal resolution and image pre-processing has been proposed. An overview of buildings, topography, land cover and land use spatial databases in Slovenia is given. The possibility of introducing automated processes in the maintenance process of specific spatial data has been assessed. Object based image analysis has been used for extraction of buildings contours and other built-up areas. This single data layer of buildings and other built-up areas is used for change detection in comparison to registered data in different databases. Completeness of detected changes is very high (more than 80%). The major advantage of proposed automated change detection in the spatial data maintenance process is that the automatically identified changes direct the operator to capture only data on the areas where change exists and so significantly reduces the amount of work.