Ahmadi Hamed, Argany Meysam, Ghanbari Abolfazl, Firoozi Manijeh
Department of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran.
Department of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran.
Cogn Process. 2025 May 31. doi: 10.1007/s10339-025-01279-4.
Numerous studies have demonstrated that variations in streets' topological characteristics impact the degree to which people perceive the structure of urban environments. Accordingly, this systematic review aimed to evaluate how the topological parameters affect human spatial cognition, and also analyze the study methods used in studies. The PRISMA reporting guidelines were used in this regard. We systematically searched the Web of Science and Scopus until April 19, 2024. Two researchers independently screened the title, abstract, and full text for the eligibility criteria. A total of 39 articles met our eligibility criteria. The Mixed Methods Appraisal Tool was used to assess the quality of the included articles. The studies have followed four objectives: wayfinding, pedestrian volume, route choice, and spatial representation. Quantitative descriptive, quantitative non-randomized, and observational methodologies were mostly employed. The evaluations mostly used space syntax theory, and accordingly, Depthmap, DepthmapX, and GIS-based toolboxes were used to analyze the topological parameters. Base and blank maps, street photos, and questionnaires have been used in many studies as experiment tools, while virtual reality tools have been less considered. The control variables have been rarely applied in the evaluations. The results indicated that integrated streets and streets with high choice values enhance human spatial cognition. Dense and intelligible street networks and streets with high-directional connectivity also enhance human spatial cognition; however, very few studies evaluated these parameters' influence. The results of evaluating the impact of the other parameters were very heterogeneous. The heterogeneity was mainly related to differences in the study designs, trip purpose, objectives, and spatial scales. Seldom studies have compared how different topological parameters influence spatial cognition. In conclusion, further research, especially experimental quantitative randomized controlled trials, is warranted to discover the impact of street network topology on human spatial cognition.
众多研究表明,街道拓扑特征的变化会影响人们对城市环境结构的感知程度。因此,本系统综述旨在评估拓扑参数如何影响人类空间认知,并分析相关研究中使用的研究方法。在此方面采用了PRISMA报告指南。我们在2024年4月19日前系统检索了Web of Science和Scopus数据库。两名研究人员独立筛选标题、摘要和全文以确定是否符合纳入标准。共有39篇文章符合我们的纳入标准。使用混合方法评估工具来评估纳入文章的质量。这些研究遵循了四个目标:寻路、行人流量、路线选择和空间表征。大多采用了定量描述、定量非随机和观察性方法。评估大多使用空间句法理论,因此,使用Depthmap、DepthmapX和基于GIS的工具箱来分析拓扑参数。许多研究使用基础地图和空白地图、街道照片和问卷作为实验工具,而较少考虑虚拟现实工具。评估中很少应用控制变量。结果表明,整合度高的街道和具有高选择值的街道可增强人类空间认知。密集且可理解的街道网络以及具有高方向连通性的街道也能增强人类空间认知;然而,很少有研究评估这些参数的影响。评估其他参数影响的结果差异很大。异质性主要与研究设计、出行目的、目标和空间尺度的差异有关。很少有研究比较不同拓扑参数如何影响空间认知。总之,有必要进行进一步研究,尤其是实验性定量随机对照试验,以发现街道网络拓扑对人类空间认知的影响。