Evidence map›Paper›PMID 40448803›Full record

SynthesisCognitive processing2025

Evaluating the impact of urban street network topology on human spatial cognition: a systematic review.

Hamed Ahmadi, Meysam Argany, Abolfazl Ghanbari, Manijeh Firoozi

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Cognitive processing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hamed AhmadiDepartment of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran.
Meysam ArganyDepartment of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran. argany@ut.ac.ir.
Abolfazl GhanbariDepartment of Remote Sensing and GIS, Faculty of Planning and Environmental Sciences, University of Tabriz, Tabriz, Iran.
Manijeh FirooziDepartment of Remote Sensing and Geographic Information System, Faculty of Geography, University of Tehran, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

CognitionEnvironment DesignSpace PerceptionSpatial NavigationCitiesHumansHuman spatial cognitionStreet network topologySystematic reviewUrban environment

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.