Multi-Indicator Approach for Characterising Urban Green Space Provision at City and City-District Level in Germany

Abstract

This paper addresses the question of how a sustainable urban development can be supported through simple measured quantities in the context of the specific provision of green space and open space. The specific provision of green space is analysed based on a combination of six indicators that describe, on the one hand, the access of inhabitants to green spaces and on the other hand, the settlement character as well as the strong anthropogenic imprint on the urban landscape. The indicators were calculated and combined in a 9-cell matrix for classifying the areas studied. The implementation was carried out at two scales for all German cities with at least 50,000 inhabitants as well as exemplarily for city districts of eight big cities. The calculated indicator values for representing green characteristics decrease with increasing number of inhabitants, whereas the opposite relationship was obtained for the indicators of the grey characteristics. We show how the approach provides an in-depth morphological assessment of German cities ranking their scores from low to the high presence of grey/green characteristics.

From City- to Site-Dimension: Assessing the Urban Ecosystem Services of Different Types of Green Infrastructure

“…The correct application of this concept has the potential to better exploit the multiple benefits of urban ecosystems, so that urban planning can be more closely oriented to natural conditions and resources [13][14][15]. Furthermore, the development of standards and indicators to assess and describe ES in urban contexts can help politicians, urban planners as well as practitioners create ecological and sustainable cities [16]. While we can already point to a few practical examples of the successful integration of ES-related subjects into diverse planning documents and tools, there are still several unresolved problems limiting a more general implementation [17].…”

“…One limiting factor is the lack of information on urban ecosystems on different spatial scales and their services. The poor quality of available spatial or other relevant data on small, local scales often complicates the integration of ES into planning frameworks or decision-making processes [13][14][15][16][17][18][19][20]. A further limitation is the lack of suitable methods to assess ES at such spatial scales; hitherto, most assessment methods have referred to the global, national or regional scale.…”

Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

“…These potential problems should be analyzed and if necessary addressed by developing suitable methods to guarantee the production of consistent maps of public urban green spaces across multiple cities. This would be an important step towards facilitating accessibility analyses on urban green spaces across different cities [11,83] for which suitable data sets are not available yet. In addition, the urban green spaces derived using this methodology could also be of interest for the OSM community by raising awareness for a lack of completeness or inconsistent mapping practices in regard to urban green spaces.…”

Analysis of the Practice of Dengue Prevention and Sustainable Control with Multi-attribute Decision-making

“…The purpose of this study is to explore the ranking of factors affecting the dengue fever epidemic by GRA, and uses grey multi-attribute decision-making analysis and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to predict which areas of Tainan may become prevalent areas for dengue fever. The findings can can provide reference for the prevention and control of dengue fever to government departments, vector mosquito control operators, and environmental remediation workers, before and after the occurrence of dengue fever cases, in the hope of reducing the risk and scale of dengue fever through prevention and treatment measures [9][10][11][12][13][14].…”