Martin Fleischmann

Martin Fleischmann, Krasen Samardzhiev, Anna Brázdová et al.

Built environment, formed of a plethora of patterns of building, streets, and plots, has a profound impact on how cities are perceived and function. While various methods exist to classify urban patterns, they often lack a strong theoretical foundation, are not scalable beyond a local level, or sacrifice detail for broader application. This paper introduces the Hierarchical Morphotope Classification (HiMoC), a novel, theory-driven, and computationally scalable method of classification of built form. HiMoC operationalises the idea of a morphotope - the smallest locality with a distinctive character - using a bespoke regionalisation method SA3 (Spatial Agglomerative Adaptive Aggregation), to delineate contiguous, morphologically distinct localities. These are further organised into a hierarchical taxonomic tree reflecting their dissimilarity based on morphometric profile derived from buildings and streets retrieved from open data, allowing flexible, interpretable classification of built fabric, that can be applied beyond a scale of a single country. The method is tested on a subset of countries of Central Europe, grouping over 90 million building footprints into over 500,000 morphotopes. The method extends the capabilities of available morphometric analyses, while offering a complementary perspective to existing large scale data products, which are focusing primarily on land use or use conceptual definition of urban fabric types. This theory-grounded, reproducible, unsupervised and scalable method facilitates a nuanced understanding of urban structure, with broad applications in urban planning, environmental analysis, and socio-spatial studies.

Anna Brazdova, Martin Fleischmann

Understanding the relationship between population and the built environment is essential for addresing socio-spatial inequalities. While researchers have long theorized these dynamics, empirical analyses remain limited. This study develops a scalable, spatially explicit framework to quantify the relationship between population and the built environment at the scale of local census tracts in Czechia. The approach integrates a fine-grained classification of the built environment with a comprehensive set of socio-demographic indicators. The methodology is structured to capture the overall strength and spatial variability of the relationship between the population and the built environment, in order to identify how built form and spatial distribution can reinforce or limit socio-spatial differentiation, using geographically weighted classification models. The results of the study show that population characteristics exhibit linear, spatially conditioned relationships with built form, emphasizing that spatial heterogeneity must be accounted for when assessing these relationships. The analysis of the relationship strength also reveals that some built form types are more socially selective than others, underscoring the importance of built form in reproducing social-spatial inequalities.