التفاصيل البيبلوغرافية
| العنوان: |
Urban visual intelligence: Uncovering hidden city profiles with street view images. |
| المؤلفون: |
Zhuangyuan Fan, Fan Zhang, Loo, Becky P. Y., Ratti, Carlo |
| المصدر: |
Proceedings of the National Academy of Sciences of the United States of America; 7/4/2023, Vol. 120 Issue 27, p1-7, 29p |
| مصطلحات موضوعية: |
CITIES & towns, URBAN research, COMPUTER vision, OUTDOOR furniture, URBAN studies, CITY dwellers |
| مصطلحات جغرافية: |
UNITED States |
| مستخلص: |
A longstanding line of research in urban studies explores how cities can be understood through their appearance. However, what remains unclear is to what extent urban dwellers' everyday life can be explained by the visual clues of the urban environment. In this paper, we address this question by applying a computer vision model to 27 million street view images across 80 counties in the United States. Then, we use the spatial distribution of notable urban features identified through the street view images, such as street furniture, sidewalks, building façades, and vegetation, to predict the socioeconomic profiles of their immediate neighborhood. Our results show that these urban features alone can account for up to 83% of the variance in people's travel behavior, 62% in poverty status, 64% in crime, and 68% in health behaviors. The results outperform models based on points of interest (POI), population, and other demographic data alone. Moreover, incorporating urban features captured from street view images can improve the explanatory power of these other methods by 5% to 25%. We propose "urban visual intelligence" as a process to uncover hidden city profiles, infer, and synthesize urban information with computer vision and street view images. This study serves as a foundation for future urban research interested in this process and understanding the role of visual aspects of the city. [ABSTRACT FROM AUTHOR] |
|
Copyright of Proceedings of the National Academy of Sciences of the United States of America is the property of National Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
Full Text Finder