Professor for Geoinformatics
The goal of the Geoinformatics Lab is to develop innovative computational methods for modeling, analysing and simulating human geo-spatial behavior. The focus is on
- processes using spatial cognition such as geographic space appropriation, perception and wayfinding
- dynamic complex systems such as multi-modal transportation networks
Such human-environment interactions may best be understood using a bottom-up perspective, ie. through implementing generative models while at the same time corroborating the usefulness of the models by analysing using a top-down perspective. We are currently exploring several methodologies, i.e., we work with agent-based modelling, geosimulation, classical spatio-temporal analysis, GIS models and extensions as well as GeoAI-methods.
News
Female convents in early modern Mexico (project)
For the reconstruction of three female convents in the city of Oaxaca, Mexico, Prof Timpf collects geodata together with a group of geoinformatics and geography students with expertise in GIS, surveying, CAD, photogrammetry and drone flight. The project was initiated by Dr. Franziska Neff from the UNAM in Mexico in collaboration with Dr. Pia Heberer from the institute of computer science as well as given support by Prof. Theo Ungerer.
[Geoinformatics]
Best full paper award at LBS2023
Eva Nuhn, Kai Hamburger and Sabine Timpf won the best full paper award for for their paper on “Mapping olfactory cues for wayfinding – A theoretical approach and an empirical study" at the International Conference on Location Based Services (LBS 2023), which took place in Ghent, Belgium on 20-22 November 2023.
[Geoinformatics]
Best Short Paper Award, AGILE 2023
Irada Ismayilova and Sabine Timpf won the best short paper award for the paper tittled "Semantic Identification of Urban Green Spaces: Forest" at the AGILE 2023 (Association of Geographic Informtion Laboratories in Europe) conference, held in Delft, Netherlands.
The article explores semantic characteristics of urban forests in the cities of Augsburg and Wuerzbug, and utilizes these characteristics as unique forest Identifiers. Using Rule-based classification technique, forest relevant bio-physical as well as spatial pattern rules are extracted. Finally, these rules are used to accurately map forests in both cities.
The published article is available at: https://agile-giss.copernicus.org/articles/4/28/2023/
[Geoinformatics]
