Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use

Integrative analysis of remote sensing data and socioeconomic information enables the transition of land cover and urban structures into a detailed functional model of urban land use. In this paper object based image analysis is used to derive a classification of urban structures. The implementation of ALS (Airborne Laser Scanning) significantly enhances the classification of optical imagery both in terms of accuracy as well as automation. Land cover types are additionally differentiated based on their relative height above ground resulting in a 3D building model. This model forms the basis for the integration of socioeconomic data for identifying urban functions. Buildings are split into sub-buildings by creating Thiessen polygons based on geocoded address point data. Company data is linked to this address information resulting in significant refinement of the functional classification and concrete identification of building use. By means of spatial disaggregation, raster population data is distributed to potential residential buildings. The relevant potential residential capacity is calculated under consideration of building use and ALS-based height information. These additional information sources guarantee a high accuracy of disaggregation and a further refinement of the functional 3D city model, independently confirmed by a quantitative accuracy assessment.