Is Germany experiencing urban or suburban growth? Contrasting long-standing and novel urban gradient classifications

Understanding population shifts along urban-rural gradients is crucial for informed decision-making in sustainable spatial planning. Empirical accounts of urbanization and suburbanization rely on classification choices, typically derived from administrative units. Recently, novel classification approaches based on remote sensing and high-resolution population data have gained relevance. This trend, driven by methodological advancements, raises the question of whether these new approaches yield similar or different results in comparative analyses along urban-rural gradients. Our paper explores how classification choices affect assessments of population trends along the urban-rural gradient at both the national and subnational regional scales. We contrast three urban gradient classifications to analyze population change in 50 German metropolitan regions from 2011 to 2022. Results indicate that, at the national scale, observed trends in urban, suburban, and peri-urban areas are consistent across all classifications. For Germany, we find that urban areas have registered higher growth rates than suburban and peri-urban areas across all classifications. However, at the regional scale, observed trends partially depend on classification choices, suggesting that regional findings are particularly sensitive to the chosen classification scheme. The methodological framework presented here can also be applied to other geographical contexts for which similar data are available. • Examines how classification choices affect observed population change along urban–rural gradients. • Compares functional (long-standing) with gridded population and morphology-based (novel) urban classifications. • Analyzes 50 German metro regions for 2011–2022 relative population changes. • At the national scale, urban, suburban, and peri-urban change patterns are stable across classifications. • The morphology-based approach shows higher population growth in urban cores on average.