Conference Agenda

Global urbanization has led to the emergence of large metropolitan areas with increasingly complex spatial structures, further challenging their sustainability and planning. Unlike medium-sized and smaller cities, these urban regions tend to exhibit multiple urban centers of similar size or a nested set of subcenters. Despite growing interest, the identification of subcenters and their relative importance remains inconsistent due to conceptual ambiguities, diverse data sources, spatial scales, and methodological variations across cases. In particular, local density or single cut-off approaches do not account for the fact that subcenters are heterogeneous in size within cities, notably along the internal general accessibility gradient, and for the fact that the relative importance of a subcenter vary depending on the overall size of a city, i.e. across the hierarchy of cities.

This study proposes a comparable and globally applicable framework to identify urban subcenters based on population density input. We employ a radial (center-periphery) analysis combined with urban scaling to account for both internal and across cities heterogeneities. First, a baseline profile is established for each city by modeling its population (exponential) decline from the main center toward the periphery, after accounting for its total population size (i.e. radial distance and density rescaling). Second, rings are identified that exhibit unexpectedly high average population density compared to the rescaled baseline gradient. Third, spatial filtering and a gravity-based allocation procedure are applied within each of these rings to identify subcenters and describe their population importance. The framework is applied to a global dataset of cities and the output compared to standard cut-off or local filtering approaches.

Urban expansion builds on rich and easily accessible arable land, which is a concern for agricultural production, in a context of global climate change. It also affects ecosystems, contributing to the biodiversity crisis, and human health, for instance through air pollution. Soil sealing is linked to an increased flood risk as well. Worldwide measures aim to alleviate the impacts of urban expansion and sprawl, in small and large cities. However, the link between urban extent and population size is still unclear, as the literature displays contradictory results on this matter.

In this work, we uncover a radial scaling law governing built-up land in 1800+ global urban areas, of more than 300,000 inhabitants each (gathering more than 30% of the world population in total). We use for this UN World Urbanization Prospects and Copernicus' GHSL built land data for the year 2020. We study these urban areas through a mix of radial (center-periphery) analysis and scaling laws, a method which we refer as radial scaling analysis. We observe that world cities have homothetic (or isometric) radial land use profiles, and that built-up footprint is proportional to total population. We obtain these results through two independant but coherent analyses. On the one hand, through a rescaling of radial built land profiles, which provides a nice data collapse. And on the other hand, through non-linear regression methods, which additionally show that the mathematical shape of these profiles is roughly exponential.

The spatial scaling law which we observe is important for the understanding and the definition of urban areas, to help build a science of cities using robust empirical stylized facts, and to make cities more sustainable. It implies that small and large urban areas have similar internal (radial) structures, and that built-up area per capita is constant across city sizes. This suggests that efforts to curb land take (for instance in the frame of no net land take NNLT objectives) are needed equally in large and small cities. These results also lead us to define a new scale-free indicator of urban built land per capita, which captures the remaining variations. At the national scale, we find that these variations are very strongly correlated to wealth, measured by gross domestic product per capita. This very strong link means that land take on the one side and economic activity (measured by gross domestic product) on the other side are quite fundamentally intertwined in our societies -- which is not very encouraging for NNLT objectives. This actually suggests a pick between economic development and sustainability.

Defining an 'urban boundary' is crucial for urban planning as it is used to measure population and urban extension for global sustainable initiatives, such as the UN Sustainable Development Goals (SDGs). With one of the highest levels of urbanization, projected to reach 90% by 2050, with urban population contained in a few primary megacities, Latin America presents a critical case for accurately defining urban boundaries.

Since data on built-up areas are more reliably and regularly available than population, built-up areas are used an indirect measure of population footprints. We employed clustering methods on the Global Human Settlement Layer (GHSL) surface built-up areas and population and identified contiguous built-up and population footprints for all cities across 19 countries of the region. We then compared these '' new'' city footprints against the UN defined Urban Centers. Then we focus on the 65 most populated cities of Latin America and compare our new city definition results against their administrative boundary and the UN Urban Centers definitions.

By contrasting these different urban boundaries, the study identifies values and rates of urban sprawl. Results show that administrative boundaries and UN definitions fail to reflect real urban population distributions and built footprint growth patterns. To address this a new extended urban boundary is proposed based on the contiguous clustering results over Degree of Urbanization (DEGURBA) definitions.

Finally we perform comparative rank size analysis for population distributions and built-up areas comparing these new, administrative area, and the UN Urban Centers definitions. We find that boundary definitions strongly affect calculations. In general, at the whole country level, the UN defined Urban Centers distributions had significantly lower Zipf exponents (-0.19 (Peru) to -0.84 (Brazil)). In contrast, with the new definitions, the exponent values are significantly higher, ranging from -0.88(Peru) to -1.17 (Brazil).

In land consumption ratios we found that countries have concentrated their populations in their Urban Centers, but their built-up areas have not followed the same trend. The urban centers have become denser, but the built-up areas have sprawled with low densities, bringing overall densities down.

Over 70% of the population is concentrated in a few Urban Centers and the built-up footprint accounts for only 35% of the total in these areas. Except for Mexico and Panama, land consumption more than doubles for every country when suburban areas and sprawl are included in the city definitions.

The research identifies two primary forms of suburban expansion: Compact Urban Cores: Characteristic of smaller Latin American countries, where fewer dominant Urban Centers are surrounded by sparsely populated suburbs, leading to marked density declines and higher land consumption rates. Polycentric Urban Structures: Seen primarily in Brazil and Mexico, these cities feature multiple densely populated hubs surrounded by relatively denser suburbs, resulting in less extreme density loss and more balanced land consumption ratios.

This research highlights significant gaps between administratively and standard defined urban areas and actual population and built-up footprints, underscoring the limitations of static thresholds and administrative boundaries in capturing the complexities of evolving urbanization dynamics.

Urban sprawl has become a defining feature of global urbanization. In regions such as Europe, North America, India, and China, built-up areas have expanded more rapidly than population growth - more so than in other parts of the world. This suggests that the drivers of sprawl have already surpassed population growth as the leading factor in land expansion. Continued population and economic growth, especially in developing and emerging countries, indicate a trend toward low-density development. These developments pose a challenge to achieving Sustainable Development Goal (SDG) target 11.3, which seeks to ensure that land consumption does not exceed population growth. Urban sprawl is associated with various environmental and social issues and undermines the broader goal of SDG 11: the creation of inclusive, safe, resilient, and sustainable cities. Despite its importance, long-term knowledge about global sprawl patterns remains limited.

Urban sprawl is defined as the decentralization of housing, employment, and economic activity into suburban and rural areas, characterized by scattered development, low use-density, and high per capita land consumption. This includes detached housing, dispersed retail, and large-scale commercial structures. The “Weighted Urban Proliferation” (WUP) indicator - used by the European Environment Agency (EEA) and incorporated into Switzerland’s environmental monitoring - offers a robust, spatially continuous method for quantifying sprawl over time.

This study applies the WUP metric using the GHSL Data Package 2023 to assess global urban sprawl from 1990 to 2020. The analysis uses a spatial resolution of 100 meters and is conducted in five-year intervals. The dataset combines harmonized satellite-derived data on built-up surfaces with grid-based population estimates derived from national censuses. The sample includes all urban agglomerations with over 300,000 inhabitants as of 2018, based on UN World Urbanization Prospects. The most represented countries are China, India, the United States, Russia, and Brazil.

A major contribution of this study is the inclusion of a population-based perspective on urban sprawl. In addition to tracking land use change, we estimate how the number of people living in highly sprawled areas has evolved over time. This approach highlights the human dimension of sprawl and allows for connections to key indicators such as energy use per capita, emissions, infrastructure costs, and access to services. Understanding population distribution within sprawled zones provides policymakers with actionable insights—supporting targeted interventions, improved service provision, and the promotion of more compact urban growth.

By combining high-resolution built-up area data with harmonized population grids, this approach generates globally comparable insights into the scale and nature of urban sprawl. While census-based datasets have inherent limitations, the method supports robust medium-scale analysis and is particularly valuable in data-scarce contexts. It can inform more effective urban planning and policy-making in response to ongoing and future urbanization challenges.