New paper: Stiles, J., Li, Y. and Miller, H.J. (2022) “How does street space influence crash frequency? An analysis using segmented street view imagery,” Environment and Planning B: Urban Analytics and City Science, https://doi.org/10.1177/23998083221090962
Abstract. Road crashes in metropolitan areas are challenging to prevent because they stem from the interactions of drivers and other system users in intricate built environments. Recent theories indicate that features of the built environment may induce unsafe driving by shaping users’ expectations and behaviors. The availability of street view imagery and methods of scene parsing create new possibilities for understanding how features of the built environment influence crash incidence. Most previous crash research using street imagery has applied manual processing methods. In this paper, we develop and apply automated machine parsed imagery in conjunction with self-explaining roads theory to consider how the street space visible to drivers influences crash frequency, using data from Columbus, Ohio, USA. While controlling for road network and area characteristics, we model the association of individual street elements with crash frequency. We then conduct a cluster analysis to define four types of street spaces, which are used in a subsequent model. We find that an Open Road type of metropolitan street space, characterized by more visible sky, roadway, and signage are associated with the greatest increase in crashes, and that the majority of these spaces exist on arterial or collector class road segments. We theorize that the visual similarity of this type of street space to highways promotes faster, less careful driving, which combines with their mixed land uses to make them the least safe. This points to the importance of traffic calming for such roads in high-activity areas, and the need to differentiate environments of non-highways from highways to promote careful driving.
New paper: Li, Y., Miller, H.J., Root, E.D., Hyder, A. and Liu, D. “Understanding the role of urban social and physical environment in opioid overdose events using found geospatial data,” Health and Place, 75, 102792.
Abstract: Opioid use disorder is a serious public health crisis in the United States. Manifestations such as opioid overdose events (OOEs) vary within and across communities and there is growing evidence that this variation is partially rooted in community-level social and economic conditions. The lack of high spatial resolution, timely data has hampered research into the associations between OOEs and social and physical environments. We explore the use of non-traditional, “found” geospatial data collected for other purposes as indicators of urban social-environmental conditions and their relationships with OOEs at the neighborhood level. We evaluate the use of Google Street View images and non-emergency “311” service requests, along with US Census data as indicators of social and physical conditions in community neighborhoods. We estimate negative binomial regression models with OOE data from first responders in Columbus, Ohio, USA between January 1, 2016, and December 31, 2017. Higher numbers of OOEs were positively associated with service request indicators of neighborhood physical and social disorder and street view imagery rated as boring or depressing based on a pre-trained random forest regression model. Perceived safety, wealth, and liveliness measures from the street view imagery were negatively associated with risk of an OOE. Age group 50–64 was positively associated with risk of an OOE but age 35–49 was negative. White population, percentage of individuals living in poverty, and percentage of vacant housing units were also found significantly positive however, median income and percentage of people with a bachelor’s degree or higher were found negative. Our result shows neighborhood social and physical environment characteristics are associated with likelihood of OOEs. Our study adds to the scientific evidence that the opioid epidemic crisis is partially rooted in social inequality, distress and underinvestment. It also shows the previously underutilized data sources hold promise for providing insights into this complex problem to help inform the development of population-level interventions and harm reduction policies.
New paper: Acton, B., Le, H.T.K. and Miller, H.J. (2022) “The impacts of bus rapid transit (BRT) on residential property values: A comparative analysis of 11 US BRT systems,” Journal of Transport Geography, 100, 103324.
Abstract: Bus rapid transit (BRT) is growing in popularity as a lower-cost alternative to light rail transit. Although the impacts of rail transportation on residential property values is well-explored, the impact of BRT on property values remains less well-understood, particularly in the United States where BRT infrastructure is more heterogeneous than the rest of the world. This paper addresses this gap by evaluating and comparing the before-and-after effect of 11 BRT systems on nearby property values in ten metropolitan areas across the United States. We used a quasi-experimental approach and hedonic spatial error models with propensity score matching to measure change in residential property transaction prices within walking distance of a BRT station. Overall model results show a mix of appreciation, depreciation, and no change in residential properties value across different BRT systems. Multi-family properties nearby BRTs with on-street dedicated lanes generally experienced the most appreciation while single-family properties around off-street busway systems experienced depreciation. BRT-lite systems without dedicated lanes associate with property appreciation in relatively dense and congested metropolitan areas with developed transit networks and high ridership. Our model results emphasize the ability of BRT to improve transit accessibility in these regions and to provide an attractive alternative to driving. Furthermore, the lack of property appreciation around busways indicates these systems may not provide nearby residents with an amenity bonus greater than its nuisance effects. Our study informs stakeholders and public officials about the broad effects of BRT on land values and invites researchers to continue investigating the role of walkability, nuisance effects, and individual BRT amenities on residential property values.