Evaluating implied urban nature vitality in San Francisco: An interdisciplinary approach combining census data, street view images, and social media analysis

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.