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For Central Europe urbanization and urban sprawl are the major processes concerning land-use and land-cover change that alter the characteristic and functioning of the landscape permanently. Against the background of the current sustainable development debate there is an increasing demand of reliable information about the future trends of these land-use developments. Remote Sensing provides the required data and methods for an operational monitoring of land-use/-cover changes. However for the prediction of future trends additional information and a deep understanding of the driving forces of land-use/-cover change is needed. Here we show an exemplary pathway for obtaining the required future land-use information using accurate and stable techniques. We acquired historical land-use information using Landsat imagery. The measured changes (e.g. an increase of urban areas of about 37% between 1984 and 2005) are driven by a variety of socio-economic causes that have been evaluated statistically. We used this information to calibrate a spatial predictive model that has been implemented in the generic modeling framework XULU (eXtendable Unified LandUse Modeling Platform).