Application of Hierarchical Clustering for Creating Urban Green Space Typology

In the face of rapid urbanization and dynamic changes in the landscape, the role of urban green spaces gains in importance. Developing a compre-hensive, regionally tailored typology of urban green spaces is essential for capturing the full diversity of urban ecosystems. This study presents a novel approach to creating urban green space typology, integrating hier-archical cluster analysis as the primary method. This statistical approach utilizes numerous spatial data features, which are characteristics related to their function, morphology, and management. Using a clustering al-gorithm, elements were grouped into relatively homogeneous classes and the relationships between objects with scaled cluster distances were examined. The main result of this study is a hierarchical typology of ur-ban green spaces, distinguishing two groups and 11 types of urban green spaces. Despite the satisfactory overall results of the hierarchical cluster analysis, an extended typology was proposed because urban gardens are characterized by a very high degree of heterogeneity within a type.