The visual dimension of cities has been a fundamental subject in urban studies, since the pioneering work of scholars such as Sitte, Lynch, Arnheim, and Jacobs. Several decades later, big data and artificial intelligence (AI) are revolutionizing how people move, sense, and interact with cities. This paper reviews the literature on the appearance and function of cities to illustrate how visual information has been used to understand them. A conceptual framework, Urban Visual Intelligence, is introduced to systematically elaborate on how new image data sources and AI techniques are reshaping the way researchers perceive and measure cities, enabling the study of the physical environment and its interactions with socioeconomic environments at various scales. The paper argues that these new approaches enable researchers to revisit the classic urban theories and themes, and potentially help cities create environments that are more in line with human behaviors and aspirations in the digital age.

翻译：城市的视觉维度一直是城市研究的核心课题，这一传统可追溯至西特、林奇、阿恩海姆、雅各布斯等学者的开创性工作。数十年后的今天，大数据与人工智能正在彻底改变人们的城市移动、感知与交互方式。本文通过梳理关于城市外观与功能的文献，阐明视觉信息如何被用于理解城市。我们提出"城市视觉智能"这一概念框架，系统阐述新型图像数据源与人工智能技术如何重塑研究者感知与测量城市的方式，从而能够在多尺度上研究物质环境及其与社会经济环境的互动关系。本文认为，这些新方法使研究者得以重新审视经典城市理论与议题，并有望在数字时代助力城市营造更符合人类行为与愿景的环境。