UCLA Luskin School of Public Affairs

This essay provides a counterpoint to Robert Bruegmann's perspective on accessibility and sprawl in this journal volume. Bruegmann's recent work on the history of urban form situates contemporary discussions of sprawl in a well-researched historical context; however, this essay takes a different perspective on several key points in Bruegmann's analysis, particularly in relation to cost-benefit analysis for transportation-disadvantaged populations.

Abstract Planners often regard streets as targets for mitigating urban heat across cities by virtue of being abundant, publicly-owned, low-albedo, low-vegetation surfaces. Few studies, however, have assessed the role streets play in contributing to urban heat, and the scale of their effect relative to the built environment around them. We examine the relationship between road area and land surface temperature across a variety of biophysical regions through the urban areas of Los Angeles and San Bernardino Counties in Southern California. Our results show that wide streets have no consistent, detectable effect on urban heat. Rather, vegetation is the primary cooling mechanism for urban areas. In the absence of trees, concrete highways are the coolest surfaces, though particular hot or cool pockets (e.g., airports, industrial centers, parks) can dominate neighborhood temperature signatures. In considering LST mitigation strategies, these hotspots might outweigh the cumulative effects of road surface changes.

This article focuses on national and local anti-homeless ordinances and investigates emerging spatial banishment strategies and their impacts on unhoused folks’ basic freedoms. First, we review debates on co-existing geographies of punishment and care through theoretical and legal lenses. Focusing on sixteen cities in the United States, we examine categories of anti-homeless ordinances and their evolution in the past two decades. Next, we focus on Los Angeles and use archival research and interviews with activists to examine the expansion of newly emerging anti-homeless spaces. Our research details ad hoc strategies of spatial banishment targeting homelessness. We find that the city represents a fragmented landscape of “no-go-zones” for the unhoused. We posit that the COVID-19 pandemic enabled various spatial banishment strategies and that Los Angeles is neo-revanchist. We advocate for city policies that abolish spatial banishment strategies and respond to the needs of the unhoused.

A better understanding of urban form metrics and their environmental outcomes can help urban policymakers determine which policies will lead to more sustainable growth. In this study, we have examined five urban form metrics-weighted density, density gradient slope, density gradient intercept, compactness, and street connectivity-for 462 metropolitan areas worldwide. We compared urban form metrics and examined their correlations with each other across geographic regions and socioeconomic characteristics such as income. Using the K-Means clustering algorithm, we then developed a typology of urban forms worldwide. Furthermore, we assessed the associations between urban form metrics and two important environmental outcomes: green space access and air pollution. Our results demonstrate that while higher density is often emphasized as the way to reduce driving and thus PM2.5 emissions, it comes with a downside-less green space access and more exposure to PM2.5. Moreover, street connectivity has a stronger association with reduced PM2.5 emissions from the transportation sector. We further show that it is not appropriate to generalize urban form characteristics and impacts from one income group or geographical region to another, since the correlations between urban form metrics are context specific. Our conclusions indicate that density is not the only proxy for different aspects of urban form and multiple indicators such as street connectivity are needed. Our findings provide the foundation for future work to understand urban processes and identify effective policy responses.

Credibly identifying how the built environment shapes behaviour is empirically challenging, because people select residential locations based on differing constraints and preferences for site amenities. Our study overcomes these research barriers by leveraging San Francisco’s affordable housing lotteries, which randomly allow specific households to move to specific residences. Using administrative data, we demonstrate that lottery-winning households’ baseline preferences are uncorrelated with their allotted residential features such as public transportation accessibility, parking availability and bicycle infrastructure – meaning that neighbourhood attributes and a building’s parking supply are effectively assigned at random. Surveying the households, we find that these attributes significantly affect transportation mode choices. Most notably, we show that essentially random variation in on-site parking availability greatly changes households’ car ownership decisions and driving frequency, with substitution away from public transport. In contrast, we find that parking availability does not affect employment or job mobility. Overall, the evidence from our study robustly supports that local features of the built environment are important determinants of transportation behaviour.

Urban soil systems research has largely relied on the narrative that soils provide ecosystem services to human populations and should be studied and managed to maximize their potential value in regards to such services. However, soil scientists have not adequately engaged with diverse stakeholders to understand the needs, opportunities, and challenges related to urban soil systems. This disconnect has resulted in urban soil system research agendas that are potentially misaligned with the needs of the communities in which they are situated. Community engagement in the priorities-setting stage of research development can create research agendas that more closely align with community needs. Here we report on findings from the Healthy Soils for Healthy Communities Initiative in which community perceptions, needs, and concerns regarding soils in Los Angeles (LA) County, California, United States were measured through four county-wide online surveys with residents, educators, policy-makers, and professionals and a series of virtual focus groups with key community representatives. The online surveys revealed that the majority of LA County residents (76%) are very or extremely concerned about soil contaminants and pollution. Likewise, 70% of policy-makers and 77% of LA County professionals are highly concerned about soil contamination. In contrast, fewer LA County educators (48%) are concerned about soil contaminants and pollution. Even though 85% of LA County residents surveyed maintain some kind of green space, 70% self-report that their knowledge regarding factors impacting soil health is low. The focus groups revealed several themes present across stakeholder groups including a need for: (1) accessible and transparent soil data and testing; (2) effective community engagement and streamlined communication that centers underserved communities; and (3) building alliances among community, policy, businesses, and science professionals and leveraging connections among organizations, individuals, and agencies that are focused on soil. The findings from this study have informed the future direction of urban soil research and community science in the region. The process of engaging communities in defining research agendas can serve as a model for other cities providing an opportunity to not only improve the relevance and impact of urban soil research, but also improve the sustainability of urban soil systems.

Researchers have improved travel demand forecasting methods in recent decades but invested relatively little to understand their accuracy. A major barrier has been the lack of necessary data. We compiled the largest known database of traffic forecast accuracy, composed of forecast traffic, post-opening counts and project attributes for 1291 road projects in the United States and Europe. We compared measured versus forecast traffic and identified the factors associated with accuracy. We found measured traffic is on average 6% lower than forecast volumes, with a mean absolute deviation of 17% from the forecast. Higher volume roads, higher functional classes, shorter time spans, and the use of travel models all improved accuracy. Unemployment rates also affected accuracy-traffic would be 1% greater than forecast on average, rather than 6% lower, if we adjust for higher unemployment during the post-recession years (2008 to 2014). Forecast accuracy was not consistent over time: more recent forecasts were more accurate, and the mean deviation changed direction. Traffic on projects that opened from the 1980s through early 2000s was higher on average than forecast, while traffic on more recent projects was lower on average than forecast. This research provides insight into the degree of confidence that planners and policy makers can expect from traffic forecasts and suggests that we should view forecasts as a range of possible outcomes rather than a single expected outcome.

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