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Kain's spatial mismatch hypothesis (SMH) (1968) highlights the segregation of Black population in the inner city as well as the decentralization of jobs, both of which played a role in the poor labor market outcomes for Black residents in the inner city. Demographic and economic changes in U.S. metropolitan areas since the late 20th century have transformed the urban spatial structure. This paper aims to revisit the SMH and investigate whether the spatial pattern of mismatch has changed as a result of geographic shifts in the Black population. This paper specifically examines how the suburbanization of the Black population has affected the geographic patterns of mismatch and whether the mismatch is disappearing in the major U.S. metropolitan areas. Using spatial measures of mismatch, this paper presents intra‐metropolitan spatial mismatch patterns that capture the clustering of jobs and the Black population based on their relative distributions, showing that the overall level of spatial mismatch declined in major U.S. metropolitan areas between 2000 and 2015. However, geographical evidence reveals that the spatial mismatch has shifted to the outer suburbs, replicating city‐suburb spatial inequality, implying that although mismatch may have declined in the inner city due to Black suburbanization, spatial mismatch continue to persist in U.S. metropolitan areas in Black suburbs. The findings also demonstrate that although spatial mismatch generally declined in the inner city, it increased in cities with high inner city polarization, particularly New York, Chicago, San Francisco, and Seattle. [ABSTRACT FROM AUTHOR]

Route planning represents a major challenge with a substantial impact on safety, economy, and even climate. An ever-growing urban population caused a significant increase in commuting times, therefore, stressing the prominence of efficient real-time route planning. In essence, the goal is to compute the fastest route to reach the target location in a realistic environment where traffic conditions are time-evolving. Consequently, a large volume of traffic data is potentially required and the route continuously updated. We thereby address the re-routing problem to answer questions such as when, how often, and where is re-routing worthwhile. We base our study on a real dataset, comprising the travel times of the road segments of New York, London, and Chicago, collected over three months. By exploiting this dataset, we implement an optimal algorithm, able to mimic ideal predictions of road segment speeds in the network. Thereby, allowing us to compute the lower bound of travel-time to serve as a reference against other routing techniques. Mainly, we quantify the achieved travel-time gain of a static, no re-routing, and continuous re-routing strategies. Surprisingly, we find that traffic conditions are sufficiently stable for short time windows, and re-routing a vehicle is very seldom useful when exploiting accurate statistics at departure time. Typically, real-time re-routing should only be triggered during rush hours, for long routes, passing through well-identified road segments. [ABSTRACT FROM AUTHOR]

Parks play a critical role in the health and well-being of people in urban environments. Recent events such as the COVID-19 pandemic have underscored the importance of public parks, particularly in cities. To maximize the benefits of these spaces, it is important to understand the social dimension of site user experiences within successful urban parks. Social media data provide a means to assess public places through the lens of large quantities of site users over time. Recent landscape research studies provide assessments of urban and nature-based locations using social media data and are predominantly quantitative in their methodologies (Havinga et al., 2021; Donahue et al., 2018; Wood et al., 2013). However, incorporating mixed methods into existing approaches can create a better understanding of site user experiences. This study uses 11,419 Tripadvisor reviews from the years 2010 to 2018 in a multi-step process, where qualitative content analysis builds upon Latent Dirichlet allocation (LDA) modeling topics to assess the semantic content of Bryant Park, NY. The new framework emerging from this process separates site user perceptions and sentiment positivity into categories. Site design elements are revealed as a major positive focus of site users, along with the position of the park within the urban fabric, site activity consisting of passive pastimes, and the essence of the space related to emotions. The study's findings can provide guidance for designers and park managers for the creation of successful urban parks and provide another baseline for research on New York City's parks. [ABSTRACT FROM AUTHOR]

This article examines an important element of New Yorkers' legal rhetoric in support of abolition: their use of ideas grounded in the laws of war. It analyzes how New York abolitionists used the rules governing warfare between 1830 and 1860 both to attack the legality of slavery and to justify slaves' enduring right to rebel and escape.