Urban visual intelligence: Uncovering hidden city profiles with street view images

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.

Entropy and Cities: A Bibliographic Analysis towards More Circular and Sustainable Urban Environments

Cities are critical to a sustainable future for our planet; still, the construction and operation of cities rely on intensive resource and energy use and transformation, leading to the generation of waste, effluents, and pollution, representing negative externalities outside and inside the city. Within every process, transformation implies the use of energy and the increase of entropy. In an urban system, the transformation of energy and materials will trigger the creation of entropic landscapes, mainly in the informal city and in unguarded natural landscapes, even hundreds of kilometers away, which generates substantial economic, social, and environmental impacts. In this sense, cities are significant contributors to the environmental crisis. Upstream, degradation of landscapes and ecosystems is frequent. Cities' externalities and exogenous consumptions are directly linked with entropy and entropic landscapes, which are recognized as pollution (in the air, water, and land) or waste and in the degradation of natural ecosystems and communities. Through a systematic review of existing literature, this paper first outlines briefly how entropy has been applied in different disciplines and then focuses on presenting recent developments of how entropy has been defined, used, and characterized in urban studies concerning sustainability in cities and architecture, and presents a definition of the concept in relation to urban systems and key aspects to consider.

A Transdisciplinary Framework to Unlock the Potential Benefits of Green Spaces for Urban Communities Under Changing Contexts

New urban models increasingly seek to create more sustainable, livable, and healthier cities by reinvigorating green space. In this article, we highlight and briefly review several main but disconnected areas of study in which the factors that frame human-environment interactions and therefore also influence the potential well-being outcomes of those interactions are studied. We then use the intersection of affordance theory and socio-institutional programming to provide a conceptual framework that ties together these spheres of research, and we discuss some critical keys for enabling different positive green space experiences. Urban communities are not homogeneous, and accounting for the intersection between individual differences and landscape programming opens up more diverse pathways for affording positive human-environment interactions and different well-being outcomes.

(Re) thinking urban mental health from the periphery of São Paulo in times of the COVID-19 pandemic

Urban mental health studies traditionally search for causal relationships between elements of the city and the prevalence of mental disorders. This paper discusses the importance of (re)thinking the 'lived urban experience' from the perspective of city residents about how the immediate environment affects their mental health and how people cope with inequalities. A participatory-action research was implemented in a peripheral area of São Paulo - Brazil, in which volunteers from the territory made phone calls to neighbours to provide emotional support during the COVID-19 pandemic. Weekly supervision meetings were held between volunteers and researchers to discuss the experiences shared by community counterparts. Narratives have shown that the lived experience in the city is mediated by multiple layers of 'urban insecurities'. These difficulties pressured people to organise and resist in face of pervasive inequalities as well as to respond to unfolding experiences of social suffering. We highlight the potential of participatory methodologies to observe the ways in which subjects face their structural issues and the suffering that emerge in these circumstances. The understanding of how these conflicts are lived at a subjective level can support studies that are wondering about the mechanisms of how social conflicts 'get under the skin'.

Social Inequities in Urban Heat and Greenspace: Analyzing Climate Justice in Delhi, India

Climate change and rapid urbanization currently pose major challenges for equitable development in megacities of the Global South, such as Delhi, India. This study considers how urban social inequities are distributed in terms of burdens and benefits by quantifying exposure through an urban heat risk index (UHRI), and proximity to greenspace through the normalized difference vegetation index (NDVI), at the ward level in Delhi. Landsat derived remote sensing imagery for May and September 2011 is used in a sensitivity analysis of varying seasonal exposure. Multivariable models based on generalized estimating equations (GEEs) reveal significant statistical associations (p < 0.05) between UHRI/NDVI and several indicators of social vulnerability. For example, the proportions of children (β = 0.922, p = 0.024) and agricultural workers (β = 0.394, p = 0.016) are positively associated with the May UHRI, while the proportions of households with assets (β = -1.978, p = 0.017) and households with electricity (β = -0.605, p = 0.010) are negatively associated with the May UHRI. In contrast, the proportions of children (β = 0.001, p = 0.633) and agricultural workers (β = 0.002, p = 0.356) are not significantly associated with the May NDVI, while the proportions of households with assets (β = 0.013, p = 0.010) and those with electricity (β = 0.008, p = 0.006) are positively associated with the May NDVI. Our findings emphasize the need for future research and policies to consider how socially vulnerable groups are inequitably exposed to the impact of climate change-related urban heat without the mitigating effects of greenspace.

How did the 'state of emergency' declaration in Japan due to the COVID-19 pandemic affect the acoustic environment in a rather quiet residential area?

The COVID-19 pandemic caused lockdowns in many countries worldwide. Acousticians have made surveys to monitor how cities became quieter under the lockdown, mainly in central areas in cities. However, there have been few studies on the changes in the acoustic environment due to the pandemic in the usually quieter residential areas. It may be expected to be different from the effect in 'originally noisy' areas. Also, the effect could be different in Japan, because the 'state of emergency' declaration there was different to lockdowns elsewhere. Considering these circumstances, this article reports the results of noise monitoring and makes some observations on the acoustic environment in residential areas far from city centres, to provide an example of how the acoustic environment was affected by the state of emergency declaration due to the COVID-19 pandemic in Japan. The results showed that the reduction of noise levels was somewhat less than that reported in large cities. Also, comparing the results after the cancellation of the state of emergency, the noise level increased again. However, observations of noise sources imply that a possible change in human behaviour may have also affected the acoustic environment.

Predicting neighborhoods' socioeconomic attributes using restaurant data

Accessing high-resolution, timely socioeconomic data such as data on population, employment, and enterprise activity at the neighborhood level is critical for social scientists and policy makers to design and implement location-based policies. However, in many developing countries or cities, reliable local-scale socioeconomic data remain scarce. Here, we show an easily accessible and timely updated location attribute-restaurant-can be used to accurately predict a range of socioeconomic attributes of urban neighborhoods. We merge restaurant data from an online platform with 3 microdatasets for 9 Chinese cities. Using features extracted from restaurants, we train machine-learning models to estimate daytime and nighttime population, number of firms, and consumption level at various spatial resolutions. The trained model can explain 90 to 95% of the variation of those attributes across neighborhoods in the test dataset. We analyze the tradeoff between accuracy, spatial resolution, and number of training samples, as well as the heterogeneity of the predicted results across different spatial locations, demographics, and firm industries. Finally, we demonstrate the cross-city generality of this method by training the model in one city and then applying it directly to other cities. The transferability of this restaurant model can help bridge data gaps between cities, allowing all cities to enjoy big data and algorithm dividends.

Computer vision uncovers predictors of physical urban change

Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision method to measure changes in the physical appearances of neighborhoods from time-series street-level imagery. We connect changes in the physical appearance of five US cities with economic and demographic data and find three factors that predict neighborhood improvement. First, neighborhoods that are densely populated by college-educated adults are more likely to experience physical improvements-an observation that is compatible with the economic literature linking human capital and local success. Second, neighborhoods with better initial appearances experience, on average, larger positive improvements-an observation that is consistent with "tipping" theories of urban change. Third, neighborhood improvement correlates positively with physical proximity to the central business district and to other physically attractive neighborhoods-an observation that is consistent with the "invasion" theories of urban sociology. Together, our results provide support for three classical theories of urban change and illustrate the value of using computer vision methods and street-level imagery to understand the physical dynamics of cities.

The Human Figure and Urban Ground: Cyborgs and the City

Recent years have seen developments in cyborgian movements in which people play and experiment with the boundaries of human flesh and aesthetic realities. Some individuals develop novel intimate relationships with devices that, each in their own way, interfere with human subjectivity. Public dissemination of these movements often proposes notions of transcendence, therapy, post-humanism and trans-humanism, but often fails to outline the lived-experience of those who explore cyborgian identity as an alternative mode of being in the world. This paper briefly follows self-described cyborgs who delimit the body through sensory 'enhancement' in an effort to disrupt common relationships between the human figure and the urban ground. Borrowing from Lewis Mumford's concepts of biotechnics, I propose cyborgian engagement as a type of psychodynamic living. Rather than focus on post-human discourses, these cyborgs turn to the natural world for inspiration in shaping the terms of engagement between their bodies and the city.