Urban green spaces (UGS) are vital in modern cities, offering extensive health, social, and environmental benefits. However, traditional research methods primarily focus on UGS distribution and aggregation through 2D mapping, often neglecting the quality and vitality of urban natural environments. This limited approach hampers our full understanding of the complex issues and opportunities surrounding UGS. This study proposes a novel concept of Implied Urban Nature Vitality (IUNV) and evaluation framework that offers a comprehensive lens to understand better and evaluate the manifold human-urban-nature interactions in modern cityscapes. Based on our IUNV framework, an interdisciplinary investigation is conducted to show the distribution and population-level perceived IUNV in San Francisco by leveraging a triad of data sources: census, street-built environment, and social media data. Utilizing census data, we analyze socio-economic influences on UGS distribution and IUNV, including factors such as education, age demographics, income, and ethnicity. Street view imagery (SVI), analyzed with advanced image recognition algorithms, serves as a proxy for visual and physical aspects of IUNV, highlighting features like trees, sky, buildings, and roads. This analysis paints a granular picture of UGS's spatial distribution and physical attributes, facilitating an objective measure of IUNV. Subsequently, we analyze Flickr photos related to urban natural areas, examining their distribution and identifying thematic clusters that illuminate various aspects of UGS vitality. Lastly, we combine computer vision and manual review to define 12 IUNV themes from architecture and nature, eco-friendly gatherings, to cultural performance, exploring the relationship between the vitality clusters and the independent variables. The main findings are: (1) Macro-level factors (e.g., accessibility level, land use mix level, road density, population density, etc.) are the dominant variables influencing IUNV.; (2) Street view factors play key roles in IUNV. Through this holistic IUNV analysis, the study shed light on the complexities of urban green space planning and management, informing future urban development strategies towards greater vitality and, by extension, environmental and social sustainability.

中文翻译：

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评估旧金山隐含的城市自然活力：结合人口普查数据、街景图像和社交媒体分析的跨学科方法

城市绿地 (UGS) 在现代城市中至关重要，可提供广泛的健康、社会和环境效益。然而，传统的研究方法主要侧重于通过二维制图进行地下储气分布和聚集，往往忽视了城市自然环境的质量和活力。这种有限的方法阻碍了我们对 UGS 周围复杂问题和机遇的充分理解。本研究提出了隐含城市自然活力（IUNV）的新概念和评估框架，为更好地理解和评估现代城市景观中人类-城市-自然的多种相互作用提供了一个全面的视角。基于我们的 IUNV 框架，我们利用人口普查、街道建筑环境和社交媒体数据等三大数据源进行了一项跨学科调查，以显示旧金山的 IUNV 分布和人群感知程度。利用人口普查数据，我们分析了社会经济对 UGS 分布和 IUNV 的影响，包括教育、年龄人口统计、收入和种族等因素。使用先进图像识别算法进行分析的街景图像 (SVI) 可作为 IUNV 视觉和物理方面的代理，突出显示树木、天空、建筑物和道路等特征。该分析描绘了 UGS 的空间分布和物理属性的详细图景，有助于对 IUNV 进行客观测量。随后，我们分析了与城市自然区域相关的 Flickr 照片，检查它们的分布并确定阐明 UGS 活力各个方面的主题集群。最后，我们结合计算机视觉和人工审核，定义了从建筑与自然、环保聚会到文化表演的12个IUNV主题，探索活力簇与自变量之间的关系。主要发现是：（1）宏观因素（如可达性水平、土地利用组合水平、道路密度、人口密度等）是影响IUNV的主导变量； (2)街景因素在IUNV中发挥着关键作用。通过这种整体的 IUNV 分析，该研究揭示了城市绿地规划和管理的复杂性，为未来的城市发展战略提供信息，以实现更大的活力，进而实现环境和社会的可持续性。