Modelling land use change with an integrated impact analysis on Ecosystem Services. The case of Berlin. (DFG)
use change with an integrated impact analysis on Ecosystem Services.
The case of
Research Foundation (DFG)|
Lead:||Prof. Dr. Birgit Kleinschmit
project, funded by the DFG (German Research Foundation) is part of the
research program Urban Ecology Berlin. The aim of the project is the
implementation of an urban land use change (LUC) model on an entire
city level. This implies the integration of relevant ecological
processes as well as their influence on LUC.
Through a ex-post consideration of Berlin´s LUC within the last 20 years, the coherences of effects between participating dependent and independent variables will be identified and evaluated.
Subsequently, the results are going to be transferred into a spatial GIS-based model, a so called Cellular Automata, while taking into account established model approaches. The derivation of appropriate scenarios leads to future perspectives of the urban development of Berlin.
The case study area will include Berlin as well as its closer surroundings. Thereby, relevant city-suburban relations for the future urban development are taken into account.
The resulting model will be specifically used to investigate the main factors of LUC and its strength in a metropolitan area. Furthermore, the chosen scenarios will expose the future predicted occupation of open land quantitatively and qualitatively, which will be analyzed taking into account urban sprawl development. In particular, the progress of the sealing rate will be decisive. Moreover, it is intended to extrapolate the potentials of an inner-city consolidation in terms of Reubanization. The integration of an ecological dimension will be used to comprehend the consequences of LUC on the micro-climate.
The spatial explicit study on the small-scale city level requires the use of high-resolution data. Therefore, existing multi-temporal GIS data offered by the senate department for urban development will represent the basis for the model calibration.