Understanding urban perception with visual data: A systematic review

Cities, Journal Year: 2024, Volume and Issue: 152, P. 105169 - 105169

Published: June 21, 2024

Language: Английский

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Urban Visual Intelligence: Studying Cities with Artificial Intelligence and Street-Level Imagery

Annals of the American Association of Geographers, Journal Year: 2024, Volume and Issue: 114(5), P. 876 - 897

Published: April 8, 2024

The visual dimension of cities has been a fundamental subject in urban studies since the pioneering work late-nineteenth- to mid-twentieth-century scholars such as Camillo Sitte, Kevin Lynch, Rudolf Arnheim, and Jane Jacobs. Several decades later, big data artificial intelligence (AI) are revolutionizing how people move, sense, interact with cities. This article reviews literature on appearance function illustrate information used understand them. A conceptual framework, intelligence, is introduced systematically elaborate new image sources AI techniques reshaping way researchers perceive measure cities, enabling study physical environment its interactions socioeconomic at various scales. argues that these approaches would allow revisit classic theories themes potentially help create environments align human behaviors aspirations today's AI-driven data-centric era.

Language: Английский

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Global Streetscapes — A comprehensive dataset of 10 million street-level images across 688 cities for urban science and analytics

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 215, P. 216 - 238

Published: July 16, 2024

Language: Английский

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Accessing eye-level greenness visibility from open-source street view images: A methodological development and implementation in multi-city and multi-country contexts

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 103, P. 105262 - 105262

Published: Feb. 8, 2024

The urban natural environment provides numerous benefits, including augmenting the aesthetic appeal of landscapes and improving mental well-being. While diverse methods have been used to evaluate greenery, assessment eye-level greenness visibility using street-view level images is emerging due its greater compatibility with human perception. Many existing studies predominantly rely on proprietary street view provider such as Google Street View (GSV) data; usage restrictions lack alignment FAIR (Findability, Accessibility, Interoperability, Reusability) principles present challenges in at scale. Therefore, incorporating Volunteered Imagery (VSVI) platforms, Mapillary, a promising alternative. In this study, we scalable reproducible methodological framework for utilising Mapillary Green Index (GVI) image segmentation approach completeness usefulness data geographical contexts, eleven cities (i.e., Amsterdam, Barcelona, Buenos Aires, City Melbourne, Dhaka, Ho Chi Minh, Kampala, Kobe, Mexico City, Seattle, Tel Aviv). We also use globally available satellite-based vegetation indices (e.g., Normalised Difference Vegetation Index-NDVI) estimate GVI locations where are unavailable. Our demonstrates applicability assessments, although revelling considerable disparities availability usability between located developed developing countries. identified that NDVI could be effectively values direct street-level imagery limited. Additionally, analysis reveals notable differences across cities, particularly high-density, lower-income Africa South Asia, compared low-density, high-income USA Europe.

Language: Английский

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Evaluating implied urban nature vitality in San Francisco: An interdisciplinary approach combining census data, street view images, and social media analysis

Urban forestry & urban greening, Journal Year: 2024, Volume and Issue: 95, P. 128289 - 128289

Published: March 15, 2024

Language: Английский

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Greenspace equity across variation in residential densities: Insights for urban sustainability

Habitat International, Journal Year: 2025, Volume and Issue: 157, P. 103310 - 103310

Published: Feb. 10, 2025

Language: Английский

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Sensitivity of measuring the urban form and greenery using street-level imagery: A comparative study of approaches and visual perspectives

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2023, Volume and Issue: 122, P. 103385 - 103385

Published: June 17, 2023

Street View Imagery (SVI) is crucial in estimating indicators such as Sky Factor (SVF) and Green Index (GVI), but (1) approaches terminology differ across fields planning, transportation climate, potentially causing inconsistencies; (2) it unknown whether the regularly used panoramic imagery actually essential for tasks, or we can use only a portion of imagery, simplifying process; (3) do not know if non-panoramic (single-frame) photos typical crowdsourced platforms serve same purposes ones from services Google Baidu Maps their limited perspectives. This study first to examine comprehensively built form metrics, influence different practices on computing them multiple fields, usability normal (from consumer cameras). We overview run experiments 70 million images 5 cities analyse impact multitude variants SVI characterising physical environment mapping street canyons: few (e.g. fisheye) 96 scenarios perspective with variable directions, view, aspect ratios mirroring diverse smartphones dashcams. demonstrate that disparate give mostly comparable results metric R=0.82 R=0.98 metrics); often when using front-facing ultrawide camera), single-frame derive commercial counterparts. finding may simplify processes data also unlock value billions images, which are overlooked, benefit scores locations worldwide yet covered by services. Further, aggregated city-scale analyses, correspond closely.

Language: Английский

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Computer vision applications for urban planning: A systematic review of opportunities and constraints

Sustainable Cities and Society, Journal Year: 2023, Volume and Issue: 100, P. 105047 - 105047

Published: Nov. 8, 2023

Computer vision (CV) technology, a key subset of artificial intelligence, provides powerful tools for extracting valuable insights from visual data, which is crucial component the urban planning process. Despite promising potential CV in planning, its applications this context have not been thoroughly examined. This lack scholarship represents critical knowledge gap our understanding role planning. paper aims to provide consolidated process and challenges planners face during adoption CV. The conducts systematic literature review tackle questions how applied process, what are adopting techniques process? findings revealed: (a) could support broad range tasks including data collection analysis, issue identification prioritisation, public participation, plan design adoption, implementation evaluation; (b) improve decision-making through various information, but limitations need be considered, and; (c) Utilisation efforts sustainable development. study informs policy- plan-making circles by providing into existing prospective contributions transforms augments practices, elaborates adoption.

Language: Английский

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Assessing the equity and evolution of urban visual perceptual quality with time series street view imagery

Cities, Journal Year: 2023, Volume and Issue: 145, P. 104704 - 104704

Published: Dec. 7, 2023

Language: Английский

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Beyond the frame: evaluating panoramic vs. perspective images for assessing place perception

International Journal of Geographical Information Science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 33

Published: April 10, 2025

Language: Английский

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