摘要
Background: Cycling as a means of transport contributes to public health in terms of increasing the physical activity behaviour and reducing air pollution. In comparison to walking, cycling-spe cific environmental characteristics have been less investigated. The aim of this study was to develop, based on geographic information systems (GIS) data, a bikeability index for a mid-sized European city, to examine the predictive validity of the index and to visualize the bicycle-friendliness of the city by creating a bikeability map. Methods: Using GIS data, we assessed the environmental characteristics of 278 bicycle trips in the city of Graz, Austria. Characteristics which differed significantly between the actually taken and shortest possible routes were used to form an additive bikeability index and the bikeability map for 100 m × 100 m cells. The relationship between the cycling behaviour and the bikeability index around the home environment was examined to assess the predictive validity of the index. Results: Three environmental components (cycling infrastructure, bicycle pathways and green areas) were positively related, and two components (main roads, and topography) were negatively related to the actually used route. These components formed the bikeability index, which was positively correlated with cycling behaviour (OR: 1.08, 95% CI 1.01 - 1.17). The final outcome is a high-resolution coloured map indicating the degree of bicycle-friendliness in the city of Graz. Conclusion: Mapping based on the bikeability index helps to visualize the bicycle-friendliness of an urban area. Therefore, it should be a useful tool for the planning as well as for the evaluation of the transport environments in cities.
Background: Cycling as a means of transport contributes to public health in terms of increasing the physical activity behaviour and reducing air pollution. In comparison to walking, cycling-spe cific environmental characteristics have been less investigated. The aim of this study was to develop, based on geographic information systems (GIS) data, a bikeability index for a mid-sized European city, to examine the predictive validity of the index and to visualize the bicycle-friendliness of the city by creating a bikeability map. Methods: Using GIS data, we assessed the environmental characteristics of 278 bicycle trips in the city of Graz, Austria. Characteristics which differed significantly between the actually taken and shortest possible routes were used to form an additive bikeability index and the bikeability map for 100 m × 100 m cells. The relationship between the cycling behaviour and the bikeability index around the home environment was examined to assess the predictive validity of the index. Results: Three environmental components (cycling infrastructure, bicycle pathways and green areas) were positively related, and two components (main roads, and topography) were negatively related to the actually used route. These components formed the bikeability index, which was positively correlated with cycling behaviour (OR: 1.08, 95% CI 1.01 - 1.17). The final outcome is a high-resolution coloured map indicating the degree of bicycle-friendliness in the city of Graz. Conclusion: Mapping based on the bikeability index helps to visualize the bicycle-friendliness of an urban area. Therefore, it should be a useful tool for the planning as well as for the evaluation of the transport environments in cities.
