Suitability of remote sensing based surface information for a three-dimensional urban microclimate model

Urban microclimate models can provide knowledge on the climate, however, most microclimate studies use assumptions and generalizations to define the model area. Remote sensing based data products provide an alternative allowing both the detailed spatial and thematic scale required by urban climate models. This study shows how microclimate simulations for a series of real world urban areas can be supported by using remote sensing data. In an automated process, urban surface information has been derived using airborne hyperspectral data and height information. Results have been integrated into the urban microclimate model ENVI-met and multiple microclimate simulations have been carried out. The impact of the RS-based surface information and the suitability of the applied data and techniques are tested and evaluated. The simulation results show consistent patterns for air temperature, surface temperature and humidity, indicating the plausibility of the approach. Further, the analysis shows the importance of high quality height data, detailed surface material information and albedo.

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