This study focuses on the way urban dynamic processes challenge existing monitoring approaches and how urban structure types (UST) support an effective urban management. Due to their microstructure and the instability of shape, the differentiation of settlement structures is substantially difficult. Hence, highly sophisticated data such as color infrared (CIR) orthophotos as well as methods of image analysis, e.g., segmentation of objects will be employed. It will be shown how an object-oriented analysis strategy with CIR aerial photographs can be used to detect and discriminate different urban structure types by describing typical characteristics of color, texture, shape, and context. The urban structure classification is characterized by identifying different types of buildings (different types of housing, industrial buildings, infrastructure) and open spaces (woodland, community gardens, parks), their structural composition in terms of the amount, connectivity, and distribution of impervious surfaces, green spaces, and other open spaces on an aggregated neighborhood scale. This investigation contributes to a transferable methodology to monitor the urban dynamics and structure on a local level.