Assessing Pedestrian Accessibility to Urban Land Surface Temperature Cold Spots in Bavarian Cities

As climate change intensifies, European cities must adapt to increasingly frequent and severe heatwaves. Urban heat is not only an environmental concern but a key challenge for spatial justice, public health, and long-term resilience. For sensible adaptation strategies, planners require spatially detailed and comparable information to understand where heat accumulates, where cooling potential exists, and how equitably these cool spaces are accessible to different population groups. Recent advances in Earth observation and the availability of the German Census data at a spatial gridding of 100-m offer opportunities to integrate high-resolution environmental and demographic data into planning processes in a way that is consistent across cities of very different sizes and spatial configurations. This study presents a scalable framework that combines satellite-derived Land Surface Temperature (LST) with population data to analyse urban heat patterns and the accessibility of naturally cool areas (cold spots) across all cities in Bavaria, ranging from small historic towns and medium-sized regional centres to large urban municipalities. Multi-year Landsat composites are processed to the harmonised 100-m grid aligned with the national census grid, enabling consistent and methodologically comparable cross-city analyses. Local Getis–Ord Gi* statistics are used to identify spatial clusters of unusually warm and cool surfaces within each city, creating a coherent thermal surface vulnerability indicator which can be compared across different urban systems. To contextualize the spatial distribution of cold spots, we link them to sociodemographic data from the census grid and to walking-time accessibility. For each city, we derive population-weighted indicators that quantify how well different social groups (such as elderly people, children, and immigrants) can reach cold spots. These indicators reveal how accessibility inequalities vary not only between socio-demographic groups but also between various city sizes. This allows us to identify where targeted planning interventions are needed. By applying this workflow to the full set of Bavarian cities, the study offers a state-wide, high-resolution comparison of urban heat structures and socially differentiated access to cooling. The results demonstrate how remote sensing, geospatial analyses, and census microdata can strengthen evidence-based planning, support climate-resilient urban design, and contribute to more equitable access to cooling in cities of all sizes.