Usage and perception indicators of urban green spaces in Dresden

The data set contains all publicly accessible green spaces in the city of Dresden including an attribute table with three main indicators for the use and perception of urban green spaces (popularity_indicator, aesthetics_indicator and animals_indicator) derived from social media. In addition to these three main values, the attribute table contains an additional 18 statistical values, which were calculated by the intersection of the green spaces with classified social media data and are documented in the metadata description. The green space polygons were generated using an automatic approach, which was developed in Ludwig et al. (2021) is described in more detail. The green spaces and indicator values are part of the central data base (Cakir et al., 2021) for the assessment of green areas in Dresden according to criteria or suitability for certain activities using the myGrün app (app.meingruen.org). The popularity of urban green spaces in Dresden was measured by the density of location-based social media posts. The processing of the data for green spaces is described and described in a notebook (pub.zih.tu-dresden.de/~s7398234/vis/zielgeometrien-intersect_v6.html). The aesthetic indicator describes the aesthetic value of urban green spaces in Dresden and was conceptualised and measured based on the density of aesthetic-related social media posts. For the identification of social media posts that relate to the aesthetic value of urban green spaces, a novel methodology has been developed, based on unsupervised text classification and targeted filtering of social media posts, described in more detail in Gugulica & Burghardt, 2021 — in progress. The animal indicator shows the presence of wild animals in urban green areas in Dresden. The quantification of the animal indicator is based on the basic assumption that densities of social media posts related to wildlife and wildlife photography may reflect the demand for wildlife observation and display hotspots for this activity. In order to identify the relevant social media posts for the calculation of the indicator, the above methodology, which is based on unsupervised text classification and targeted filtering of social media posts, was used in more detail in Gugulica & Burghardt, 2021. For the quantification of popularity, aesthetics and animals indicators of urban green spaces in Dresden, location-based social media data from Instagram, Flickr and Twitter (including photos with text and text messages) were used. The data was identified using embedded location information and a custom bounding box and retrieved and collected via the API provided by each of the platforms. Only publicly available social media posts published between 1 January 2015 and 31 October 2020 were taken into account and stored as a CSV file along with meta information such as user ID, coordinates, captions, and upload dates. Duplicates were removed and after the dataset was intertwined with the target polygons, the final dataset for Dresden included 782.310 social media posts (59,101 tweets, 664,925 Instagram posts and 58,284 Flickr posts). The choice of platforms was mainly determined by the popularity of social media channels and the specificity of the respective content. In order to cover a wider user spectrum, the three data sources were combined, resulting in more robust results due to the increased data width. References: Cakir, S., Schorcht, M., Stanley, C., Rieche, T., Ludwig, C., Gugulica, M., Dunkel, A., Hecht, R. (2021). Urban green areas and indicators: Dresden (Version 2021) [Data set]. Leibniz Institute of Ecological Urban and Regional Development, Weberplatz 1, 01217 Dresden, Germany. https://doi.org/10.26084/IOERFDZ-DATA-DE-2021-1 Ludwig, C.; Hecht, R.; Lautenbach, S.; Schorcht, M.; Zipf, A. (2021): Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions. In: ISPRS International Journal of Geo-Information 10 (2021) 4, p. 251 https://doi.org/10.3390/ijgi10040251