Cities are key to climate change mitigation and adaptation in an increasingly urbanized world. As climate, socio-economic, and physical compositions of cities are constantly changing, these need to be considered in their urban climate adaptation. To identify these changes, urban systems can be characterized by physical, functional, and social indicators. Multi-dimensional approaches are needed to capture changes of city form and function, including patterns of mobility, land use, land cover, economic activities, and human behaviour. In this article, we examine how urban structure types provide one way to differentiate cities in general and to what extent socio-economic criteria have been considered regarding the characterization of urban typologies. In addition, we analyse how urban structure types are used in local adaptation strategies and plans to derive recommendations and concrete targets for climate adaptation. To do this, we examine indicators, background data used, and cartographic information developed for and within such urban adaptation plans, focusing in particular on the German cities of Karlsruhe and Berlin. The comparative analysis provides new insights into how present adaptation plans consider physical and social structures, including issues of human vulnerability within cities. Based on the analysis we make recommendations on how to improve the consideration of both physical and socio-economic aspects of a city to support pathways for adaptation.

Heat stress is recognised among the key risks in the context of climate and societal changes. This study aims to explore the link between socio-economic and spatial factors contributing to the effects of extreme heat events in the city of Stuttgart. The paper presents some findings of the Citizens' Survey 2021 in the city of Stuttgart on some key variables such as experience with heat stress and access to green spaces. The analysis further gives special emphasis to relationships between these variables and socio-economic factors e.g. income levels with heat-related adaptation options. The survey data was analyzed using Statistical Package for Social Sciences (SPSS) and then exported to ArcGIS pro and linked with geographical data (shapefiles) of the city districts. The study provides new insights into the spatial variability of heat experience as well as the socio-economic profile that needs to be targeted for future heat adaptation planning in the city.