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Obtaining a dynamic population distribution is key to many decision-makingprocesses such as urban planning, disaster management and most importantlyhelping the government to better allocate socio-technical supply. For theaspiration of these objectives, good population data is essential. Thetraditional method of collecting population data through the census isexpensive and tedious. In recent years, statistical and machine learningmethods have been developed to estimate population distribution. Most of themethods use data sets that are either developed on a small scale or notpublicly available yet. Thus, the development and evaluation of new methodsbecome challenging. We fill this gap by providing a comprehensive data set forpopulation estimation in 98 European cities. The data set comprises a digitalelevation model, local climate zone, land use proportions, nighttime lights incombination with multi-spectral Sentinel-2 imagery, and data from the OpenStreet Map initiative. We anticipate that it would be a valuable addition tothe research community for the development of sophisticated approaches in thefield of population estimation.

So2Sat POP -- A Curated Benchmark Data Set for Population Estimation from Space on a Continental Scale