Inhaltszusammenfassung

Geospatial data often build the basis for planning decisions in smart cities. In the decision-making process, geospatial relationships have not yet been fully considered and represented. The aim of our research is to investigate these geospatial relationships. This paper presents a four-step process to identify geospatial key factors in smart city use cases. We further develop and evaluate an existing metric to measure the impact of geospatial factors in urban area. For this, we use three var...Geospatial data often build the basis for planning decisions in smart cities. In the decision-making process, geospatial relationships have not yet been fully considered and represented. The aim of our research is to investigate these geospatial relationships. This paper presents a four-step process to identify geospatial key factors in smart city use cases. We further develop and evaluate an existing metric to measure the impact of geospatial factors in urban area. For this, we use three variables to characterise distance decay, opening hours and an attractiveness weight for customers depends on the use case. The use case of this study is off-street parking over a period of four years in Mainz, Germany. The results show temporal relationships between parking and geospatial factors. Consequently, our research indicates the impact of different factors on car parks. This knowledge enriches decisions for sustainable planning in cities.» weiterlesen» einklappen

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Klassifikation

DDC Sachgruppe:
Ingenieurwissenschaften