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While aerial photography is associated with vertical objectivity and spatial abstractions, street-level imagery appears less political in its orientation to the particularities of place. I contest this assumption, showing how the aggregation of street-level imagery into “big datasets” allows for the algorithmic sorting of places by their street-level visual qualities. This occurs through an abstraction by “datafication,” inscribing new power geometries onto urban places through algorithmic linkages between visual environmental qualities, geographic information, and valuations of social worth and risk. Though largely missing from media studies of Google Street View, similar issues have been raised in critiques of criminological theories that use place as a proxy for risk. Comparing the Broken Windows theory of criminogenesis with big data applications of street-level imagery informs a critical media studies approach to Google Street View. The final section of this article suggests alternative theoretical orientations for algorithm design that avoid the pitfalls of essentialist equations of place with social character.

This article assesses the sources and consequences of public disorder. Based on the videotaping and systematic rating of more than 23,000 street segments in Chicago, highly reliable scales of social and physical disorder for 196 neighborhoods are constructed. Census data, police records, and an independent survey of more than 3,500 residents are then integrated to test a theory of collective efficacy and structural constraints. Defined as cohesion among residents combined with shared expectations for the social control of public space, collective efficacy explains lower rates of crime and observed disorder after controlling neighborhood structural characteristics. Collective efficacy is also linked to lower rates of violent crime after accounting for disorder and the reciprocal effects of violence. Contrary to the “broken windows” theory, however, the relationship between public disorder and crime is spurious except perhaps for robbery.

The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The authors illustrate these challenges by developing measures of “broken windows” from Boston’s constituent relationship management (CRM) system (aka 311 hotline). A 16-month archive of the CRM database contains more than 300,000 address-based requests for city services, many of which reference physical incivilities (e.g., graffiti removal). The authors carry out three ecometric analyses, each building on the previous one. Analysis 1 examines the content of the measure, identifying 28 items that constitute two independent constructs, private neglect and public denigration. Analysis 2 assesses the validity of the measure by using investigator-initiated neighborhood audits to examine the “civic response rate” across neighborhoods. Indicators of civic response were then extracted from the CRM database so that measurement adjustments could be automated. These adjustments were calibrated against measures of litter from the objective audits. Analysis 3 examines the reliability of the composite measure of physical disorder at different spatiotemporal windows, finding that census tracts can be measured at two-month intervals and census block groups at six-month intervals. The final measures are highly detailed, can be tracked longitudinally, and are virtually costless. This framework thus provides an example of how new forms of large-scale administrative data can yield ecometric measurement for urban science while illustrating the methodological challenges that must be addressed.

This study examined what factors best predict residents’ concerns about neighborhood safety. One-hundred and twenty-two participants were selected from a large, Midwestern metropolitan area. All participants lived in high crime areas. Participants completed a 22-item questionnaire that assessed their perceptions of neighborhood safety and vigilance. These items were clustered as: 1) Community care and vigilance, 2) neighborhood safety concerns, 3) physical incivilities, and 4) social incivilities. Police crime data were also used in the analyses. Our findings suggest that aspects of the broken window theory, collective efficacy, and place attachments/territoriality play a role in affecting residents’ concerns about neighborhood safety.

Research shows that social relations within a space and the group(s) who control that space socially have a greater influence on how safe women feel than does the design of the space. And more action and research is needed to investigate how men dominate space and how this dominance can be broken.

Records on recovery after cholecystectomy of patients in a suburban Pennsylvania hospital between 1972 and 1981 were examined to determine whether assignment to a room with a window view of a natural setting might have restorative influences. Twenty-three surgical patients assigned to rooms with windows looking out on a natural scene had shorter postoperative hospital stays, received fewer negative evaluative comments in nurses' notes, and took fewer potent analgesics than 23 matched patients in similar rooms with windows facing a brick building wall.

This article focuses on the dynamics between migrant street vendors and public security forces and the complex social production of urban public space in Guangzhou. As an answer to daily contestation of public order, security agencies reluctantly open flexible windows of business opportunities to hawkers. Zones and periods of control, ‘soft’ approaches, and categories of ethnic belonging influence everyday governance and accessibility of public space. This results in a transient public space, fluid and continuously changing, which offers a new perspective on openness and functioning of public space in urban China.

The objective was to investigate associations between features of the physical environment and neighborliness. Measures of the physical environment, including sidewalks, front porches, traffic-calming devices, bars on windows, and the presence of litter or graffiti, were collected using a systematic audit instrument in 10 neighborhoods in Portland, Oregon. Generalized linear regression models were created to model the odds of increasing neighborliness given access to the physical-environment factors of interest. The authors observed a greater probability of higher levels of neighborliness as the total number of positive physical-environment characteristics increased (cumulative odds ratio [95% confidence interval] = 1.69 [1.16, 2.45]) and the results were unchanged after controlling for race, self-reported health, perception of safety, years of neighborhood residence, age of house, market value of house, and proportion of homeowners in neighborhood. Modifiable features of the physical environment may be one mechanism through which people can enhance neighborliness.

By measuring twenty streetscape features and numerous other variables for 588 blocks in New York City, we were able to identify variables that explain pedestrian traffic volumes. We found significant positive correlations between three out of twenty streetscape features with pedestrian counts after controlling for density and other built environmental variables. The significant streetscape features are the proportion of windows on the street, the proportion of active street frontage, and the number of pieces of street furniture. This study provides guidance for streetscape projects that aim to create walkable streets and pedestrian-friendly environments.

This study examines a behavioral model using latent variables of leisure involvement, place attachment, and destination loyalty among recreationists walking their dog in urban parks. A total of 928 usable questionnaires were collected. The confirmatory factor analysis and structural equation modeling were analyzed using LISREL 8.70 for Windows. Empirical results indicate that leisure involvement (i.e., attraction and self expression) and place attachment (i.e., place identity and place dependence) accurately predict the destination loyalty of recreationists walking their dogs in urban parks. Findings of this study demonstrate that the proposed behavioral model is a highly effective means of examining the causal relationships among leisure involvement, place attachment, and destination loyalty. A series of managerial implications and recommendations for further studies are drawn.

Despite the fact that virtual environments are increasingly deployed to study the relation between urban planning, physical and social disorder, and fear of crime, their ecological validity for this type of research has not been established. This study compares the effects of similar signs of public disorder (litter, warning signs, cameras, signs of vandalism and car burglary) in an urban neighborhood and in its virtual counterpart on the subjective perception of safety and livability of the neighborhood. Participants made a walking tour through either the real or the virtual neighborhood, which was either in an orderly (baseline) state or adorned with numerous signs of public disorder. During their tour they reported the signs of disorder they noticed and the degree to which each of these affected their emotional state and feelings of personal safety. After finishing their tour they appraised the perceived safety and livability of the environment. Both in the real and in the simulated urban neighborhood, signs of disorder evoked associations with social disorder. In all conditions, neglected greenery was spontaneously reported as a sign of disorder. Disorder did not inspire concern for personal safety in reality and in the virtual environment with a realistic soundscape. However, in the absence of sound disorder compromised perceived personal safety in the virtual environment. Signs of disorder were associated with negative emotions more frequently in the virtual environment than in its real-world counterpart, particularly in the absence of sound. Also, signs of disorder degraded the perceived livability of the virtual, but not of the real neighborhood. Hence, it appears that people focus more on details in a virtual environment than in reality. We conclude that both a correction for this focusing effect and realistic soundscapes are required to make virtual environments an appropriate medium for both etiological (e.g. the effects of signs of disorder on fear of crime) and intervention (e.g. CPTED) research.

Ordinary kriging, a spatial interpolation technique, is commonly used in social sciences to estimate neighborhood attributes such as physical disorder. Universal kriging, developed and used in physical sciences, extends ordinary kriging by supplementing the spatial model with additional covariates. We measured physical disorder on 1,826 sampled block faces across four U.S. cities (New York, Philadelphia, Detroit, and San Jose) using Google Street View imagery. We then compared leave-one-out cross-validation accuracy between universal and ordinary kriging and used random subsamples of our observed data to explore whether universal kriging could provide equal measurement accuracy with less spatially dense samples. Universal kriging did not always improve accuracy. However, a measure of housing vacancy did improve estimation accuracy in Philadelphia and Detroit (7.9 percent and 6.8 percent lower root mean square error, respectively) and allowed for equivalent estimation accuracy with half the sampled points in Philadelphia. Universal kriging may improve neighborhood measurement.