Research Project: meinGrün
meinGrün - information and navigation on urban green spaces in cities
In the project meinGrün
partners from science, local practice and business develop the basics for novel, interactive information offers. The aim is to describe green spaces in cities more precisely and to show how they can be reached easily. Users of green areas can rate these and municipalities receive indications of potential for improvement.
If cities are to guarantee a high quality of life despite growth and densification, green spaces play a decisive role. They provide a variety of ecological services, for example, have a positive effect on the urban climate and biodiversity, people can experience nature and relax. So it would be good if citizens know where they can find green spaces near them, which ecosystem services they provide, and which infrastructure such as banks, restaurants or sanitary facilities they offer. How to easily reach the parks, playgrounds, brownfields and other green areas - preferably on foot, by bike or by public transport - is also important information.
So far, there is still lack of such information. The project meinGrün
is now developing the data bases and technical prerequisites to change this.
New information density through combined data
The project partners will investigate and test how different data can be combined and condensed into an unprecedented wealth of information on green spaces in cities. The researchers want to combine open geodata from the administration with the latest remote sensing data from the space program Copernicus. Added to this are user-generated data such as those provided by OpenStreetMap or social media channels such as Twitter or Instagram.
This new wealth of data should serve as the basis for various user-friendly applications. How this can work, the partners show on the mobile app myGrün
. They will develop them during the project and test them in the pilot cities of Dresden and Heidelberg.
Use existing data, generate new ones
With the app, users should quickly find out which green spaces are in their environment and which best fit their wishes. Parents with children can quickly find the suitable playground nearby, young people the green area with skating rink, older people the park with enough benches and barrier-free access. The app will also point the way to the green areas - for example, it can be particularly quiet and green according to personal wishes.
Users can also use the app to add information about the green areas themselves. Defects and wishes can be recorded as well as positive characteristics. These user-generated data make it possible for urban planning to further develop the green areas as well as the pedestrian and cycle paths network in line with demand.
It is important to develop innovative methods for obtaining, analyzing and structuring the data and making it usable for the intended purposes. The goal is that not only the pilot cities of Dresden and Heidelberg use them, but also other cities can apply the created data infrastructure and resulting tools in a practice-oriented way.
The work at the Heidelberg Institute for Geoinformation Technology (HeiGIT) at the University of Heidelberg is particularly concerned with identifying optimal routes to the green spaces. Optimal means here a personalizable combination of criteria such as "greenness" and beauty of the route, time and slope. In addition, allergy sufferers have the opportunity to avoid locations of certain tree species along the route. Here, the HeiGIT operated OpenRoutService is used, which is based on the free world map OpenStreetMap. In addition, HeiGIT coordinates the integration of data services, routing service and the app, and is involved in green space assessment, indicator development and user feedback integration.
Funding:
The project is funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the research initiative mFUND, which deals with digital data-based applications for Mobility 4.0.
Preliminary work GIScienceHD / HeiGIT:
Experimental prototype studies (for Germany) in OpenRouteService on healthy pedestrian routes, especially considering:


Publications:
- Hecht, R.; Brzoska, P.; Burghardt, D.; Cakir, S.; Dunkel, A.; Gildhorn, K.; Gröbe, M.; Gugulica, M.; Kreutzarek, N.; Lautenbach, S.; Ludwig, C.; Lümkemann, D.; Meinel, G.; Rothert, S.; Schorcht, M.; Sonnenbichler, A.; Stanley, C.; Tenikl, J.; Wurm, M.; Zipf, A. (2021): Informationen und Navigation zu urbanen Grünflächen in Städten: Abschlussbericht und Handbuch zum mFUND-Projekt: meinGrün. Leibniz-Institut für ökologische Raumentwicklung, Dresden.
- Ludwig, C., Fendrich, S., & Zipf, A. (2020): Regional variations of context‐based association rules in OpenStreetMap. Transactions in GIS.
- Lautenbach, S., Ludwig, C., Fendrich, S., Novack, T., Marx, S., Oleś, A. & Zipf, A. (2020): "Optimal ans Ziel: Routing-Dienste auf Basis neutzergenerierter Geodaten - Herausforderungen und Lösungsansätze für globale Datensätze” In: Zagel, B., & Loidl, M. (eds.) Geo-IT in Mobilität und Verkehr: Geoinformatik als Grundlage für moderne Verkehrsplanung und Mobilitätsmanagement, 89 - 108. Wichmann.
- Ludwig, C., Hecht, R., Lautenbach, S., Schorcht, M., & Zipf, A. (2019): Assessing the Completeness of Urban Green Spaces in OpenStreetMap. Editors, 21.
- Ludwig, C., & Zipf, A. (2019): Exploring regional differences in the representation of urban green spaces in OpenStreetMap.
- Novack, T.; Wang, Z.; Zipf, A. (2018): A System for Generating Customized Pleasant Pedestrian Routes Based on OpenStreetMap Data. Sensors 2018, 18, 3794.