A. Valenzuela, A. Lopes, P. A. B. Araujo, M. Justina, Gabriel Claudino Budal Arins, Cassiano Ricardo Rech
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After removing duplicates and analyzing titles and abstracts, the review considered only 11 out of the 703 initial papers, which provided 100 environment indicators with varied definitions and metrics for estimating the Bikeability index. The census tract was the most used unit of the analysis found in the papers, which used GIS (Geographic Information System) data besides self-reported information on environmental characteristics. The results indicate that the most usual indicators relate to infrastructure – existence and width of bike lanes – destination, slope, speed limit, and connectivity and intersections. 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引用次数: 0
摘要
目的是通过建设性的方法学研究确定可骑自行车指数中使用的主要地理空间指标。该研究方案在PROSPERO注册,注册号为CRD42020166795,遵循PRISMA(系统评价和荟萃分析的首选报告项目)指南。选择了电子数据库Lilacs、PubMed、Science Direct、Scopus、SPORTDiscus、Trid和Web of Science中索引的原始研究。该审查还包括通过Google Scholar、OpenGrey、ProQuest获得的灰色文献,以及专家指出的参考文献和文件列表。在删除重复、分析标题和摘要后,该综述只考虑了703篇初始论文中的11篇,这些论文提供了100个环境指标,定义和指标各不相同,用于估算Bikeability指数。人口普查区是论文中使用最多的分析单位,除了自我报告的环境特征信息外,还使用了GIS(地理信息系统)数据。结果表明,最常见的指标与基础设施有关——自行车道的存在和宽度——目的地、坡度、限速、连通性和交叉路口。自行车友好型环境的创建和维护可以考虑在平坦和连接的街道上实施更多的基础设施,并改变社区的限速,特别是在十字路口密度低的地区,以减少事故并提高骑自行车者的安全意识。
Geospatial indicators of bikeability index as cyclefriendly city design: a systematic review
The aim was to identify the main geospatial indicators used in bikeability index through constructive methodological studies. The study protocol was registered in PROSPERO under the registration number CRD42020166795, following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guide. Original studies indexed in the electronic databases Lilacs, PubMed, Science Direct, Scopus, SPORTDiscus, Trid, and Web of Science were selected. The review also included grey literature through Google Scholar, OpenGrey, ProQuest, and a list of references and documents pointed out by experts. After removing duplicates and analyzing titles and abstracts, the review considered only 11 out of the 703 initial papers, which provided 100 environment indicators with varied definitions and metrics for estimating the Bikeability index. The census tract was the most used unit of the analysis found in the papers, which used GIS (Geographic Information System) data besides self-reported information on environmental characteristics. The results indicate that the most usual indicators relate to infrastructure – existence and width of bike lanes – destination, slope, speed limit, and connectivity and intersections. The creation and maintenance of bicycle-friendly environments could consider the implementation of more infrastructure on flat and connected streets with changes in speed limits in neighborhoods, especially in regions with low density of intersections, to decrease accidents and increase cyclists’ perception of safety.