An object-based multisensoral approach for the derivation of urban land use structures in the city of Rostock, Germany

The present work is part of the Enviland-2 research project, which investigates the synergism between radar- and optical satellite data for ENVIronment and LAND use applications. The urban work package of Enviland aims at the combined analysis of RapidEye and TerraSAR-X data for the parameterization of different urban land use structures. This study focuses on the development of a transferable, object-based rule set for the derivation of urban land use structures at block level. The data base consists of RapidEye and TerraSAR-X imagery, as well as height information of a LiDAR nDSM (normalized Digital Surface Model) and object boundaries of ATKIS (Official Topographic Cartographic Information System) vector data for a study area in the city of Rostock, Germany. The classification of various land cover units forms the basis of the analysis. Therefore, an object-based land cover classification is implemented that uses feature level fusion to combine the information of all available input data. Besides spectral values also shape and context features are employed to characterize and extract specific land cover objects as indicators for the prevalent land use. The different land use structures are then determined by typical combinations and constellations of the extracted land use indicators and land cover proportions. Accuracy assessment is done by utilizing the available ATKIS information. From this analysis the land use structure classes residential, industrial/commercial, other built-up, allotments, sports facility, forest, grassland, other green spaces, squares/parking areas and water are distinguished with an overall accuracy of 63.2 %.