The paper summarises the multiple benefits of urban green spaces for city dwellers and provides an overview of proximity approaches and common key parameters for green-space quantification in cities. We propose indicators for the assessment of the ecosystem service 'recreation in the city' on a national scale. The calculation procedure, which takes into account the best available data sets in Germany, is explained. The determination of threshold values regarding green-space standards comprising type, size and distance is crucial to such studies. The results, the degree of provision with public green spaces in all German cities with more than 50,000 inhabitants (n = 182) and their accessibility, are presented. In total, green spaces are accessible for daily recreation for 74.3% of the inhabitants in German cities, which means that underprovision affects 8.1 million city dwellers. Some indicator details are shown for the examples of Wiesbaden and Stuttgart. Finally, we discuss the approach and values of the proposed and quantified indicators in a German and European context.

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Information on the distribution and dynamics of dwellings and their inhabitants is essential to support decision-making in various fields such as energy provision, land use planning, risk assessment and disaster management. However, as various different of approaches to estimate the current distribution of population and dwellings exists, further evidence on past dynamics is needed for a better understanding of urban processes. This article therefore addresses the question of whether and how accurately historical distributions of dwellings and inhabitants can be reconstructed with commonly available geodata from national mapping and cadastral agencies. For this purpose, an approach for the automatic derivation of such information is presented. The data basis is constituted by a current digital landscape model and a 3D building model combined with historical land use information automatically extracted from historical topographic maps. For this purpose, methods of image processing, machine learning, change detection and dasymetric mapping are applied. The results for a study area in Germany show that it is possible to automatically derive decadal historical patterns of population and dwellings from 1950 to 2011 at the level of a 100 m grid with slight underestimations and acceptable standard deviations. By a differentiated analysis we were able to quantify the errors for different urban structure types.

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The obligations of the EU Biodiversity Strategy 2020 are generating a need to create national maps and monitoring systems for the state of biodiversity and ecosystem services (ES) on the basis of indicators. The paper gives an overview of the ecosystem services indicators being developed for Germany in the context of ongoing research projects. Additionally, it provides the indicator specifications, which are aligned with the EU MAES framework concepts (initiative on Mapping and Assessment of Ecosystems and their Services).We illustrate aspects of data selection, calculation and negotiation procedures, results and target values in general and by way of examples. The German indicator-based approach presents measures and sums up ES in their spatial expression and temporal change and compares them with objectives. As far as possible, this is carried out according to the demand-supply concept. A prioritization of ES classes to be processed was carried out in the framework of an expert-based assessment CICES classes (Common International Classification of Ecosystem Services) were most relevant for Germany in recent years. We proposed a total of 51 indicators, of which 14 indicators for 4 ES classes were accepted, implemented and published by the end of 2016. The development of ES maps and the indicator-based assessment on a national scale is a process. Consequently, the necessary further steps are shown.

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