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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]

Background: The paper examines the role of community-based participatory research (CBPR) within the context of social justice literature and practice. Methods: Two CBPR case studies addressing health inequities related to Type 2 Diabetes and Cardiovascular disease were selected from a national cross-site study assessing effective academic-community research partnerships. One CBPR partnership works with African Americans in rural Pemiscot County, Missouri and the other CBPR partnership works with African American and Latinos in urban South Bronx, New York City. Data collection included semi-structured key informant interviews and focus groups. Analysis focused on partnerships' context/ history and their use of multiple justice-oriented strategies to achieve systemic and policy changes in order to address social determinants of health in their communities. Results: Community context and history shaped each partnership's strategies to address social determinants. Four social justice approaches (identity/recognition, procedural, distributive, and structural justice) used by both partnerships were identified. These social justice approaches were employed to address underlying causes of inequitable distribution of resources and power structures, while remaining within a scientific research framework. Conclusion: CBPR can bridge the role of science with civic engagement and political participation, empowering community members to become political agents who integrate evidence into their social justice organizing strategies. [ABSTRACT FROM AUTHOR]

The spatial distribution of income shapes the structure and organisation of cities and its understanding has broad societal implications. Despite an abundant literature, many issues remain unclear. In particular, all definitions of segregation are implicitely tied to a single indicator, usually rely on an ambiguous definition of income classes, without any consensus on how to define neighbourhoods and to deal with the polycentric organization of large cities. In this paper, we address all these questions within a unique conceptual framework. We avoid the challenge of providing a direct definition of segregation and instead start from a definition of what segregation is not. This naturally leads to the measure of representation that is able to identify locations where categories are over- or underrepresented. From there, we provide a new measure of exposure that discriminates between situations where categories co-locate or repel one another. We then use this feature to provide an unambiguous, parameter-free method to find meaningful breaks in the income distribution, thus defining classes. Applied to the 2014 American Community Survey, we find 3 emerging classes—low, middle and higher income—out of the original 16 income categories. The higher-income households are proportionally more present in larger cities, while lower-income households are not, invalidating the idea of an increased social polarisation. Finally, using the density—and not the distance to a center which is meaningless in polycentric cities—we find that the richer class is overrepresented in high density zones, especially for larger cities. This suggests that density is a relevant factor for understanding the income structure of cities and might explain some of the differences observed between US and European cities. [ABSTRACT FROM AUTHOR]

The objective of this paper is to provide, for the first time, comparative estimates of racial residential segregation of blacks, Hispanics, and Native Americans in nonmetropolitan and metropolitan places in 1990 and 2000. Analyses are based on block data from the 1990 and 2000 U.S. decennial censuses. The results reveal a singularly important and perhaps surprising central conclusion: levels and trends in recent patterns of racial segregation in America's small towns are remarkably similar to patterns observed in larger metropolitan cities. Like their big-city counterparts, nonmetropolitan blacks are America's most highly segregated racial minority--roughly 30% to 40% higher than the indices observed for Hispanics and Native Americans. Finally, baseline ecological models of spatial patterns of rural segregation reveal estimates that largely support the conclusions reached in previous metropolitan studies. Racial residential segregation in rural places increases with growing minority percentage shares and is typically lower in "new" places (as measured by growth in the housing stock), while racially selective annexation and the implied "racial threat" at the periphery exacerbate racial segregation in rural places. Our study reinforces the need to broaden the spatial scale of segregation beyond its traditional focus on metropolitan cities or suburban places, especially as America's population shifts down the urban hierarchy into exurban places and small towns. [ABSTRACT FROM AUTHOR]

This paper first reviews the descriptions and structural explanations for variations, in urban population densities in the United States over several decades. The research reviewed focuses on shifts in the technology and economics of travel as being the major influences on urban density distributions. These variables appear to be somewhat less adequate as explanations of the process in recent decades. After reviewing these findings and suggesting several research questions, we attempt to assess the evidence relating variations in population density to several other aspects of human behavior. A review of the research relating high population densities to various "social pathologies" indicates that little of the variance in rates of these pathologies can be attributed to density independently of other social structural variables. Some important consequences of population density have been reported, however, and possible research directions are outlined. [ABSTRACT FROM AUTHOR]