Experimental Analysis of Geo-spatial Data to Evaluate Urban Greenspace: A Case Study in Dortmund, Germany

Abstract

Urban greenspace is of high importance for the general public from different points of view. Among others, it is beneficial for recreational activities as well as for cooling effects during summer in urban climate. Many studies investigate urban greenspace from perspectives related to environmental justice or health geography that are usually based on environmental and sociodemographic data of diverse scales or spatial levels of detail and often suffer from high degrees of generalization. To demonstrate the benefit of a higher degree of spatial detail, a representative part of the city of Dortmund (Germany) is selected as study area. A time series of freely available Sentinel-2 images and a freely available digital object height model (DOHM) are used to analyze and describe the spatio-temporal distribution of urban vegetation and its potential effects on the population. Doing so, the Sentinel-2 images are used for the calculation of vegetation indices to identify the active green period of different vegetation land covers. In addition to that, the three-dimensional appearance of vegetation is correlated with the green period to assume the relevance of green land covers for the general public. The results show that an appropriate selection of cloud-free satellite images is of importance for a greenspace analysis. The combination of high resolution 2D and 3D data sets, namely NDVI and plant height information, reveals the spatial distribution of well-equipped greenspace areas with high recreational and health potential as well as poorly-equipped areas in urban neighborhoods, that could be improved.