Land Use Policy, Год журнала: 2025, Номер 155, С. 107581 - 107581
Опубликована: Май 2, 2025
Язык: Английский
Land Use Policy, Год журнала: 2025, Номер 155, С. 107581 - 107581
Опубликована: Май 2, 2025
Язык: Английский
Cities, Год журнала: 2024, Номер 152, С. 105169 - 105169
Опубликована: Июнь 21, 2024
Язык: Английский
Процитировано
34Annals of the American Association of Geographers, Год журнала: 2024, Номер 114(5), С. 876 - 897
Опубликована: Апрель 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.
Язык: Английский
Процитировано
33ISPRS Journal of Photogrammetry and Remote Sensing, Год журнала: 2024, Номер 215, С. 216 - 238
Опубликована: Июль 16, 2024
Язык: Английский
Процитировано
26Urban forestry & urban greening, Год журнала: 2024, Номер 95, С. 128289 - 128289
Опубликована: Март 15, 2024
Язык: Английский
Процитировано
24Sustainable Cities and Society, Год журнала: 2024, Номер 103, С. 105262 - 105262
Опубликована: Фев. 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.
Язык: Английский
Процитировано
22Habitat International, Год журнала: 2025, Номер 157, С. 103310 - 103310
Опубликована: Фев. 10, 2025
Язык: Английский
Процитировано
2International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2023, Номер 122, С. 103385 - 103385
Опубликована: Июнь 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.
Язык: Английский
Процитировано
40Sustainable Cities and Society, Год журнала: 2023, Номер 100, С. 105047 - 105047
Опубликована: Ноя. 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.
Язык: Английский
Процитировано
32Cities, Год журнала: 2023, Номер 145, С. 104704 - 104704
Опубликована: Дек. 7, 2023
Язык: Английский
Процитировано
27International Journal of Geographical Information Science, Год журнала: 2025, Номер unknown, С. 1 - 33
Опубликована: Апрель 10, 2025
Язык: Английский
Процитировано
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