A citizen science toolkit to collect human perceptions of urban environments using open street view images
Not on the map. Why?
Abstract (arXiv)
Street View Imagery (SVI) is a valuable data source for studies (e.g., environmental assessments, green space identification or land cover classification). While commercial SVI is available, such providers commonly restrict copying or reuse in ways necessary for research. Open SVI datasets are readily available from less restrictive sources, such as Mapillary, but due to the heterogeneity of the images, these require substantial preprocessing, filtering, and careful quality checks. We present an efficient method for automated downloading, processing, cropping, and filtering open SVI, to be used in a survey of human perceptions of the streets portrayed in these images. We demonstrate our open-source reusable SVI preparation and smartphone-friendly perception-survey software with Amsterdam (Netherlands) as the case study. Using a citizen science approach, we collected from 331 people 22,637 ratings about their perceptions for various criteria. We have published our software in a public repository for future re-use and reproducibility.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 8 of its 65 references that are in the map. First posted on arXiv 29 Feb 2024.
Builds on
8 of 65 references.
References · 8
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2016The Cityscapes Dataset for Semantic Urban Scene Understandingcited by 4,427
- 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
- 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
- 2023Semantic Segmentation using Vision Transformers: A surveycited by 73
- 2016Deep Learning the City : Quantifying Urban Perception At A Global Scalecited by 65
- 2023Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalizationcited by 41
- 2024To use or not to use proprietary street view images in (health and place) research? That is the questioncited by 10
Built on by
Citing papers per year: 2024: 3; 2025: 3; 2026: 3.
9 papers.
- 2024Coverage and Bias of Street View Imagery in Mapping the Urban Environmentcited by 11
- 2025OpenFACADES: An Open Framework for Architectural Caption and Attribute Data Enrichment via Street View Imagerycited by 8
- 2024Urban Safety Perception Assessments via Integrating Multimodal Large Language Models with Street View Imagescited by 7
- 2024ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Sciencecited by 3
- 2025Street Review: A Participatory AI-Based Framework for Assessing Streetscape Inclusivitycited by 3
- 2025From Drone Imagery to Livability Mapping: AI-powered Environment Perception in Rural Chinacited by 0
- 2026URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centrescited by 0
- 2026Cross-View Urban Sensing: Mapping Subjective Streetscape Perception via AlphaEarth Embeddings and Urban Contextcited by 0
- 2026From Pixels to Policy: A Multi-Agent System for Intervention and Geo-Spatial Decision Supportcited by 0
- 2026From Pixels to Policy: A Multi-Agent System for Intervention and Geo-Spatial Decision Support1 Oct 2026
- 2026Cross-View Urban Sensing: Mapping Subjective Streetscape Perception via AlphaEarth Embeddings and Urban Context17 Aug 2026
- 2026URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centres30 Jan 2026
- 2025From Drone Imagery to Livability Mapping: AI-powered Environment Perception in Rural China29 Aug 2025
- 2025Street Review: A Participatory AI-Based Framework for Assessing Streetscape Inclusivity14 Aug 2025
- 2025OpenFACADES: An Open Framework for Architectural Caption and Attribute Data Enrichment via Street View Imagery1 Apr 2025
- 2024ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science24 Dec 2024
- 2024Coverage and Bias of Street View Imagery in Mapping the Urban Environment22 Sep 2024
- 2024Urban Safety Perception Assessments via Integrating Multimodal Large Language Models with Street View Images29 Jul 2024