Samenvatting

Within the Cool Neighbourhoods project, heat stress is assessed using the Physiological Equivalent Temperature (PET), a thermal comfort indicator that combines meteorological conditions with spatial and environmental variables. PET-based heat stress maps provide insight into spatial differences in thermal comfort at the neighbourhood level and form an important input for evaluating the effectiveness of cooling interventions.

The tool uses the provided datasets to generate the necessary maps required to calculate the PET. For more information on PET map generation refer to (2.4). It also considers user placed objects on the map such as trees, fountains and ponds to evaluate how those objects will affect the PET in an area.

The PET results are made available through a web application with a frontend interface, backend API orchestration layer and QGIS Server for geospatial processing. The frontend communicates with the backend API via REST endpoints, which delegate requests to QGIS Server for the map rendering. This architecture enables municipalities, researchers and other stakeholders to visualise and analyse heat stress patterns within neighbourhoods through interactive mapping and spatial analysis tools.

The current PET heat stress map generation workflow is not fully automated. A previous development phase established the technical foundation. The PET map generation pipeline is implemented using QGIS/PyQGIS in a headless environment and organized in a layered code structure. Many processing steps are already automated, which confirms that the pipeline can be executed programmatically. The remaining limitation is that the pipeline is still missing the automated generation of the wind speed map, more specifically the wind-reduction map used to accurately generate the wind speed map. It is an essential part 2 of the PET map generation which involves multiple geospatial operations and intermediate layers and still requires manual preparation.

This was due to the time constraint on the previous group, caused by the complexity of generating this map. As a result, the workflow cannot yet be executed from start to finish as a single automated process. Because these wind-related stages are not automated, execution of the PET workflow is operationally fragile, time-consuming and difficult to reproduce consistently. Furthermore, it greatly limits the potential for expanding this project beyond the city of Middelburg. The core engineering problem is therefore the lack of a fully automated end-to-end pipeline in which wind-related data preparation and wind reduction modelling are made automated.