1. Introduction Most cities in Europe, even those with a decreasing population, tend to spread out with a growing urbanization. The constant growth of cities reveals sustainability issues in the housing and transport sectors by challenging the spatial organization of cities, for example by increasing travel times (Weiss et al., 2018) and car use. Cities are major sources of pollution, even more in the context of climate change and the health of city residents. Moreover, heavy urbanization and the constant increase in built-up area create profound environmental consequences (impacts on fauna and flora, urban heat islands...). The desire to have a more sustainable management of urban space, for example by reducing artificial land use, has been at the heart of urban development policies for decades now. To gain a deeper understanding of built-up land in urban areas, it is important to compare cities and identify general forms and patterns on a large scale. 2. Methods and data We use a comparative analysis of the evolution of built-up area in the largest European cities, focusing on center-periphery organization. The objective is to analyze how urban structure changes with distance from the main center. The center-periphery analysis constitutes the first spatial differentiation for cities (Guérois and Pumain, 2008). We use urban scaling laws to compare cities that are difficult to match in terms of size. Urban scaling laws make it possible to transform a set of objects from one spatial scale to another without changing their structure, thus facilitating comparative analyses of cities (Batty, 2015). The large corpus of cities to be treated reinforces the relevance of the use of this approach. This study focuses on built-up area in 2020, in 786 European urban areas with more than 50,000 inhabitants. We use GHSL built-up data (a globally harmonized database) at a spatial resolution of 100m. The built-up area is expressed as a continuous value representing the proportion of building footprint in the total cell size. We use Urban Atlas 2018 population values for each urban area. To enable comparisons across our extensive dataset, we designate the city hall as the reference geographical center. Then, concentric rings of 200 m are made around the city hall to calculate the share of built-up area in these rings. The average share of built-up land in the city center of European cities is 37.5%, irrespective of city size. 3. Results The main result of this work is that the center-periphery organization of built-up land successions occurs at the same rate if we cancel out the size effect of urban areas. Thus, the built-up area per inhabitant is generally the same for all cities and is proportional to the population. These results are quite similar to those found by Lemoy and Caruso (2020) if only the built-up area is considered. Indeed, they study artificial land uses in European urban areas with Urban Atlas 2006 data. Up to the first 30 kilometers, there is a fairly significant decrease in the built-up area. There is a common (exponential) characteristic shape that is more or less the same in all cities. It is a fundamental characteristic of the internal structure of cities, which can be measured by a characteristic decrease distance l. However, coastal cities have on average a characteristically low distance l. This indicates that the share of built-up land decreases rapidly away from the city center. In contrast, polycentric cities have a high characteristic distance l, which indicates that the share of built-up land decreases more slowly away from the city center. This is because the share of built-up areas of several large agglomerations is taken into account in the data. Coastal cities stand out in the analysis because the presence of water near the city center is a major source of divergence from general behavior. It is therefore necessary to add large aquatic areas to the analysis in order to treat coastal cities satisfactorily. We use OpenStreetMap data for seas, and HydroSHEDS data for water bodies of at least 10 hectares in size. We then cut the GHSL raster across these two layers to remove areas covered by water. This shows that coastal cities are less exceptional in the analysis of results. These urban scaling laws point interesting phenomena: some cities stand out. Notably, two large countries stand out: French cities have more built-up areas than the average while Spanish cities have less, especially in the first 10-30 kilometers (rescaled distance with London as reference). According to the first analysis, in France, there are fewer people per household than in Spain (2.1 people in France in 2019 and 2.5 people in Spain). There are also characteristics specific to France, such as commercial areas on the outskirts of urban areas or a large number of concerted development zones.