  Obtaining a dynamic population distribution is key to many decision-making
processes such as urban planning, disaster management and most importantly
helping the government to better allocate socio-technical supply. For the
aspiration of these objectives, good population data is essential. The
traditional method of collecting population data through the census is
expensive and tedious. In recent years, statistical and machine learning
methods have been developed to estimate population distribution. Most of the
methods use data sets that are either developed on a small scale or not
publicly available yet. Thus, the development and evaluation of new methods
become challenging. We fill this gap by providing a comprehensive data set for
population estimation in 98 European cities. The data set comprises a digital
elevation model, local climate zone, land use proportions, nighttime lights in
combination with multi-spectral Sentinel-2 imagery, and data from the Open
Street Map initiative. We anticipate that it would be a valuable addition to
the research community for the development of sophisticated approaches in the
field of population estimation.
