Pith. sign in

REVIEW 2 cited by

City-Wide Perceptions of Neighbourhood Quality using Street View Images

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2211.12139 v2 pith:AE64YKID submitted 2022-11-22 cs.CV cs.CY

classification cs.CVcs.CY
keywords perceptionsqualityimagesneighbourhoodacrossassessmentcitiescollection
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

The interactions of individuals with city neighbourhoods is determined, in part, by the perceived quality of urban environments. Perceived neighbourhood quality is a core component of urban vitality, influencing social cohesion, sense of community, safety, activity and mental health of residents. Large-scale assessment of perceptions of neighbourhood quality was pioneered by the Place Pulse projects. Researchers demonstrated the efficacy of crowd-sourcing perception ratings of image pairs across 56 cities and training a model to predict perceptions from street-view images. Variation across cities may limit Place Pulse's usefulness for assessing within-city perceptions. In this paper, we set forth a protocol for city-specific dataset collection for the perception: 'On which street would you prefer to walk?'. This paper describes our methodology, based in London, including collection of images and ratings, web development, model training and mapping. Assessment of within-city perceptions of neighbourhoods can identify inequities, inform planning priorities, and identify temporal dynamics. Code available: https://emilymuller1991.github.io/urban-perceptions/.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Artifacts of Idiosyncracy in Global Street View Data

    cs.CV 2025-05 conditional novelty 6.0 of 10

    Street view coverage deviates from uniform road coverage in most of the 28 studied cities, and binary coverage percentages do not reveal these distributional biases.

  2. ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science

    cs.CV 2024-12 conditional novelty 6.0 of 10

    ZenSVI provides an integrated, documented Python pipeline for acquiring, cleaning, analyzing, and visualizing street view imagery for urban science.

Pith tools