{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T14:02:19Z","timestamp":1791900139168,"version":"4.3.4"},"reference-count":91,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T00:00:00Z","timestamp":1715040000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Hong Kong\u2019s URC Seed Fund"},{"name":"Start-up Fund"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>A smarter city should be a safer city. Nighttime safety in metropolitan areas has long been a global concern, particularly for large cities with diverse demographics and intricate urban forms, whose citizens are often threatened by higher street-level crime rates. However, due to the lack of night-time urban appearance data, prior studies based on street view imagery (SVI) rarely addressed the perceived night-time safety issue, which can generate important implications for crime prevention. This study hypothesizes that night-time SVI can be effectively generated from widely existing daytime SVIs using generative AI (GenAI). To test the hypothesis, this study first collects pairwise day-and-night SVIs across four cities diverged in urban landscapes to construct a comprehensive day-and-night SVI dataset. It then trains and validates a day-to-night (D2N) model with fine-tuned brightness adjustment, effectively transforming daytime SVIs to nighttime ones for distinct urban forms tailored for urban scene perception studies. Our findings indicate that: (1) the performance of D2N transformation varies significantly by urban-scape variations related to urban density; (2) the proportion of building and sky views are important determinants of transformation accuracy; (3) within prevailed models, CycleGAN maintains the consistency of D2N scene conversion, but requires abundant data. Pix2Pix achieves considerable accuracy when pairwise day\u2013and\u2013night-night SVIs are available and are sensitive to data quality. StableDiffusion yields high-quality images with expensive training costs. Therefore, CycleGAN is most effective in balancing the accuracy, data requirement, and cost. This study contributes to urban scene studies by constructing a first-of-its-kind D2N dataset consisting of pairwise day-and-night SVIs across various urban forms. The D2N generator will provide a cornerstone for future urban studies that heavily utilize SVIs to audit urban environments.<\/jats:p>","DOI":"10.3390\/jimaging10050112","type":"journal-article","created":{"date-parts":[[2024,5,7]],"date-time":"2024-05-07T09:03:38Z","timestamp":1715072618000},"page":"112","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Day-to-Night Street View Image Generation for 24-Hour Urban Scene Auditing Using Generative AI"],"prefix":"10.3390","volume":"10","author":[{"given":"Zhiyi","family":"Liu","sequence":"first","affiliation":[{"name":"School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing 100044, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"School of Architecture, South Minzu University, Chengdu 610225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyi","family":"Ren","sequence":"additional","affiliation":[{"name":"Department of Product Research and Development, Smart Gwei Tech, Shanghai 200940, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Da","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Bath, Bath BA2 7AY, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2590-5837","authenticated-orcid":false,"given":"Wenjing","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Spatial Information Science, The University of Tokyo, Kashiwa-shi 277-0882, Chiba-ken, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6461-7243","authenticated-orcid":false,"given":"Waishan","family":"Qiu","sequence":"additional","affiliation":[{"name":"Department of Urban Planning and Design, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1093\/biosci\/biw002","article-title":"Advancing Urban Ecology toward a Science of Cities","volume":"66","author":"McPhearson","year":"2016","journal-title":"Bioscience"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1016\/j.healthplace.2010.03.003","article-title":"Characteristics of Urban Parks Associated with Park Use and Physical Activity: A Review of Qualitative Research","volume":"16","author":"McCormack","year":"2010","journal-title":"Health Place"},{"key":"ref_3","unstructured":"Whyte, W.H. 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