Urban Climate, Climate Twins and Artificial Intelligence - A Contribution to an Integrated Planning Approach to Local Climate Resilience

For those responsible for urban and environmental planning, it is now more important than ever to find professional answers to climate problems in urban areas. In terms of urban planning, this means that environmental and urban climate issues need to be considered in more detail than in the past. This involves different levels. For example, at the level of area-based planning, the importance of small inner-city green spaces for the local climate needs to be specifically considered in urban redevelopment, especially in climate-sensitive neighbourhoods.

The combination of knowledge of the urban climate, the calculation of a “climate twin” and the use of AI enables an innovative, applied, planning-oriented urban climatology to use current planning based on a future local climate scenario, on the basis of knowledge of the "climate twin", its climate adaptability for future-oriented, climate-adapted designs and recommendations for action.

The presentation aims to present an approache, method, and application examples that use planning processes for climate adaptation measures with the help of planning-oriented, urban climatic investigation methods, AI-supported recognition and recording of local climatic phenomena to identify fields of action and to develop easily manageable building blocks that determine site-adapted recommendations for action and prepare them in such a way that they can be concretely implemented and, in particular, taken into account in municipal urban land-use planning. Such approaches and ideas enable an innovative, applied, planning-oriented urban climatology that can use its climate adaptability for future-oriented, climate-adapted designs and recommendations for action.

One tool for identifying these impacts is the calculation of “climate twins”. With the help of these climate equivalents, the climate research perspective creates an explanatory path that provides spatial planning with directional certainty and thus a perspective for the future. In addition, the spatial planning approach offers the opportunity to introduce further steps towards optimised urban adaptation to climate change into the scientific and practical planning discourse. This builds a bridge to applied, planning-oriented urban climatology, which is of immense relevance in this area of tension. Furthermore, an AI-based process will be developed that is able to carry out a climate inventory of settlements using satellite data. From this, the AI will generate an appropriate scenario that visually distinguishes different areas from each other. This AI-generated and spatially visualisable representation will enable the rapid identification of local climate risk areas.