2026-10-06 –, Bridge Cinema
Urban climate analysis increasingly relies on integrating heterogeneous geospatial datasets from multiple administrative levels, formats, and sources into a coherent and reproducible workflow. In this talk, we present our experience using QGIS as the central platform to harmonize and prepare urban geodata for the PALM city climate model as well as for evidence-based city planning.
Our work focuses on the practical challenges of handling diverse data types, with a technical emphasis on integrating CityGML datasets into PostgreSQL/PostGIS databases and utilizing QGIS for efficient management, visualization, and processing. We demonstrate how raw spatial data — including building footprints, land use, vegetation, and high-resolution imagery — can be transformed into consistent, model-ready inputs while maintaining traceability and reproducibility. A second focus is on deriving actionable urban planning recommendations from the analyses. We illustrate how to translate results into standardized climate analysis maps that depict city-wide climatic variables such as air and surface temperature, PET, wind fields, airflow, and the climatic functions of urban areas. Additionally, we show how clear action maps and practical planning guidelines can support decision‑making for non‑specialist administrators and political actors.
By showcasing a complete pipeline from raw geodata through QGIS-based preprocessing to climate simulation and interpretation of results, we illustrate how QGIS acts as a bridge between complex urban datasets and actionable insights for city planning. Attendees will profit from a practical application of QGIS in real large-scale urban climate adaptation projects, and how open-source tools can facilitate robust, reproducible, and scalable workflows that inform real-world decision-making. Our presentation is therefore aimed at attracting GIS practitioners, modelers, and urban planners to use and further develop QGIS not only as a mapping tool but as a versatile platform for data integration, simulation preparation and communication of results through standardized maps and planning principles for evidence-based city planning.
Dr. Sebastian Giersch (He/Him) is a software developer and meteorologist with a strong background in computational science, high-performance computing, and numerical modeling. He holds a PhD in Meteorology (2023) from Leibniz Universität Hannover, where he investigated dust devil-like vortices in convective boundary layers using large-eddy simulations, direct numerical simulations, and laboratory experiments at the Barrel of Ilmenau. His research combined numerical modeling and experimental studies to better understand the structure, development, and maintenance of turbulent atmospheric vortices.
Following his PhD, Sebastian shifted his focus to software development and joined EBP Deutschland GmbH in May 2024. He specializes in developing and managing geospatial workflows and in building custom, data-driven software with meteorological applications, covering both backend and frontend development.
During his univeristy carreer, he contributed to the development of the PALM model system for turbulence-resolving simulations, supported teaching and international workshops, and instructed scientists and students in advanced modeling techniques.
Sebastian has extensive programming experience in Fortran, Java, and Python, with a strong emphasis on reproducible, automated, and scalable computational workflows.. He values collaboration, clear communication, and knowledge sharing, and is passionate about combining scientific rigor with practical software solutions.