Urban green areas and indicators: Dresden

Description: The data set contains all publicly accessible green spaces of the city of Dresden including an attribute table with 38 different indicators. The green spaces and indicator values are the central data base for the assessment of green areas according to criteria or suitability for certain activities using the my Grün-App (app.meingruen.org). The green space polygons were generated using an automatic approach, which was developed in Ludwig et al. (2021) is described in more detail. The formation is based on assumptions about physical barriers, in particular the road, rail, and water networks, as well as limits of certain neighbouring land use class combinations. For Dresden, the green space polygons were formed by a combined processing of OpenStreetmap and urban data, especially a geometry on statistical blocks, parks and green areas, playgrounds, cemeteries, small gardens and forests. Indicators were processed by the Leibniz Institute for Ecological Spatial Development, the Heidelberg Institute for Geoinformation Technology at Heidelberg University and the Institute of Cartography at TU Dresden. The data bases and calculation rules used for the calculation of the indicators are documented in the metadata description. # References: Cakir, S.; Hecht, R.; Krellenberg, K. (2021): Sensitivity analysis in multi-criteria evaluation of the suitability of urban green spaces for recreational activities. In: Agile GIScience Series, 2, 22 (2021) https://doi.org/10.5194/agile-giss-2-22-2021 Hecht, R.; Artmann, M.; Brzoska, P. et al. (2021): A web app to generate and disseminate new knowledge on urban green space qualities and their accessibility. ISPRS Annals (accepted) Krellenberg, K.; Artmann, M.; Stanley, C.; Hecht, R. (2021): What to do in, and what to expect from, urban green spaces — Indicator-based approach to assess cultural ecosystem services. In: Urban Forestry & Urban Greening (2021) 59: 126986 https://doi.org/10.1016/j.ufug.2021.126986 Krellenberg, K.; Hecht, R. (2021): Generate new knowledge about urban green with a mobile app. In: GIS.business — the magazine for geoinformation (2021) 3/2021, pp. 41-43 https://doi.org/10.21241/ssoar.73701 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