Project framework

  • Project duration: 04/01/2009-03/31/2012
  • Project funded by the national research fund of Luxembourg (Fonds National de la Recherche Luxembourg)
  • Project partners: University of Luxembourg, University of Trier, Centre de Recherche Public - Gabriel Lippmann, CEPS


  • High population growth in Luxembourg in comparison with other EU countries
  • Resulting construction activities require a sustainable planning strategy including less land consumption
  • Luxembourg's intention to mainly concentrate further construction activity on urbanized regions - with the city of Luxembourg as centre.
Siedlungsentwicklung in Luxemburg
Urban development in Luxembourg between 1990 and 2007 (satellite image)


  • Detecting opportunities of applying remote sensing data in the frame of micro-economic urban modeling
  • Expanding a micro-economic urban growth model by implementing parameters derived from these remotely sensed data
  • Creation of 3D spatial (urban) metrics (for comparing city extents from image classification and model simulation results)
  • Detection of favorable areas for future urban development considering Luxembourg’s regional planning intentions
  • Calculation of various city development scenarios by varying the model parameters (inhabitant’s preferences)

Project schedule

  • Creation of the 3D city model for the city of Luxembourg based on LIDAR data (march 2010)
  • Preprocessing of aerial and satellite imagery
  • Derivation of urban-rural-masks and rough land-use maps from aerial and satellite imagery using  image classification algorithms for 5 different points in time between 1990 and 2007
  • Based on urban-rural-masks, 3D city models  for all 5 classification dates were constructed referred to the recent 3D city model
  • Visibility analysis is performed by means of land-use data and the 3D city models and its results are linked with weighted preference (people enjoy e.g. seeing water bodies in close proximity of their parcel)
  • Implementation of the visibility preferences into the calculation of the inhabitant's utility inside the micro-economic urban growth model and expanding the model from an original 2D to a 3D model
  • To compare model results with classification results (urban-rural-mask) new 3D spatial metrics will be developed
  • Calibration of the model for the situation in Luxembourg and implementation of the parameter combination which offers the best match between classified urban-rural-masks and model simulation results when applying the 3D metrics
  • Calculation of scenarios and detection of favorable regions for further development