Based on the development of a multi-criteria rating system, the webapp "meinGrün" will serve as an information- and decision-support tool for the accessibility and the use of urban green spaces. The assessment itself happens via urban ecosystem service indicators such as the climate regulation of vegetation or cultural functions of recreational infrastructures (e.g. park benches, playgrounds). For indicator calculation, a novel database as well as innovative methods of information acquisition will be tested (e.g. new measurement concepts for quantifying climate services of urban green spaces). By applying modern clustering procedures, novel generalization and aggregation algorithms will be developed, tested and validated to extract information from social media data (e.g. Flickr, Instagram, Twitter) by using machine learning methods and probabilistic data structures. Information on the physical structure and amenities of green spaces are retrieved from open geo-data as well as recent remote sensing data from the Sentinel-Mission (Copernicus-Program). This data will be combined with user-generated data concerning the perception of the citizens. Furthermore, it will be investigated which user-specific preferences are important for the individual visit of green spaces, and those preferences can be assessed. This way, a homogeneous database will be created to provide relevant information on urban green spaces and their uses.
Data and tools to be developed and provided by the meinGrün project