The strategic scale of urban planning and management is concerned with the planning and monitoring of general land use in a city, such as different types of residential, industrial and commercial areas. Because of the poor results of standard per-pixel-based classification methods in urban areas, visual interpretation of remote sensing data is often preferred. This paper empirically tests the ability of a novel method, called window-independent context segmentation, to extract information that is useful at the strategic scale of urban planning and management. The method is implemented in a theoretical framework that is a response to Bibby and Shepherd’s call for a new ontology in the application of geographic information systems and remote sensing to land use issues. In a case study using a SPOT5 satellite image of central Stockholm, the window-independent context segmentation method extracts urban features that correspond to the strategic scale of urban-planning and management and that differ in function and underlying planning theory and practice.