Urban areas are increasingly exposed to heat stress, making climate-sensitive planning more important than ever. As part of this effort, our team has recently started a new project focused on urban heat monitoring using multi-sensor Earth Observation approaches.
The research is embedded within SMART-TWIN, a project aimed at developing an AI-supported planning tool for climate-adapted urban development in Bavaria. Our work contributes to improving the data foundation for understanding and modelling urban heat dynamics, combining satellite-based observations with complementary sensor data to better capture spatial and temporal variability.
The remote sensing research in this project is covered by Antonio Castaneda-Gomez, who is working on thermal Earth Observation data integration and analysis and lead by Prof. Tobias Ullmann.
At the core of SMART-TWIN is the enhancement of an existing digital twin for the city of Würzburg by integrating the urban climate model PALM-4U through climatology approaches. This enables simulations of different urban planning scenarios, including changes in green and blue infrastructure, and their impacts on urban climate under present and future extreme weather conditions.
Würzburg serves as an ideal pilot site due to its warm and dry climate, dense urban structure, and relatively limited green spaces—factors that contribute to a pronounced urban heat island effect. Insights gained here are expected to be transferable to other cities across Bavaria with similar environmental and data conditions.
The SMART-TWIN project ultimately aims to support more informed, efficient, and climate-resilient urban planning. By combining advanced modelling with multi-sensor Earth Observation, we hope to contribute to practical tools that help cities better adapt to a warming climate.
The project is funded by the European Regional Development Fund (EFRE).
