Geodata-based number of floor estimation for urban residential buildings as an input parameter for energy modelling

The demand for energy has significantly increased worldwide due to various reasons such as urbanization and population growth. With this increase of energy demand and urban CO2 emissions, cities and municipalities are adopting decarbonization strategies in order to promote sustainable energy consumption as well as achieve lower carbon emission. Urban building energy modeling (UBEM) is a computational framework designed to analyze and predict energy consumption in an urban context. One of the major obstacles in developing UBEM is the lack of comprehensive and reliable input data. The number of floors is an essential input parameter for UBEM for which few open data is available. We propose an approach that combines 3D city models, cadaster data and oblique aerial imagery to estimate the number of floors for individual buildings on a city level. To test our approach, we created a test dataset that includes seven hundred and thirty-three residential buildings in the cities Soest and Düsseldorf in Germany. Five hundred and fifty-three buildings have been suitable to estimate the number of floors using our approach. We compared the results of our method to a geometrical approach that estimates the number of floors by assuming a standard floor height for all buildings. Our approach significantly outperforms the geometrical approach by correctly estimating the number of floors for 60% of the buildings in the test dataset to the geometrical approach that resulted in 14% of the buildings correctly estimated. Moreover, our approach results in less deviation from the correct number of floors and less underestimation compared to the geometrical approach.