Mapping Access and Mobility in the NYC Bus and Subway Systems
Elyse Mara
Introduction
Where we can travel determines where we spend our lives. Where we work, learn, receive healthcare, experience the world, are all determined by our ability to move in space — an ability that is not uniform across the population. Many people face serious barriers to movement including ableist infrastructure, economic barriers to car ownership, and the threat of racial violence, among many others. With concerns surrounding global warming and the inefficiencies of urban sprawl, mass transit presents an exciting alternative to car dependency (Murray et al., 1998). However, inequities in provision and hurdles to access continue to plague essential transportation services. Significantly, 80% of national surface transportation funding goes to roads and highways with a miniscule 20% going to public transportation (Bullard, 2004). Scholars have found that not only are Black and Latinx people disproportionately dependent on public transportation (Bullard, 2004), but that non-white neighborhoods have inferior access to bus services (Wells et al., 2011). This research aligns with Lineberry’s underclass hypothesis which suggests that municipal services in politically marginalized urban neighborhoods are inferior to other neighborhoods (Bullard, 2004).
In New York City, where mass transit is so entrenched in city life, I wanted to explore and expand on these previous findings. I will be comparing the Bus and Subway systems through the lens of “access” and “mobility” (terms defined below) to analyze their quality of service. Some guiding question include, who do these two systems serve? Are they different populations? How does access relate to actual use or movement? And what kind of mobility do these systems provide to their riders?
Access
Access is most commonly theorized in terms of proximity to a service (Murray et al., 1998; & Weiss, et al., 2011). By design, transportation services are constructed at fixed geographic locations and thus the ability to benefit from those services declines the farther from the service a person is. Yet while proximity is important, scholars have also challenged and expanded on this simplistic measurement. Weiss et al. introduce a concept of “social access” which incorporates considerations of dis-amenities, such as crime/violence and noxious land uses, that surround a service and might deter people from using it. For example, someone may live 2 blocks away from a bus stop but the area surrounding it is popular for drug sales and police surveillance. Are they likely to use it? And would that person have better access to that stop than someone who has to walk 10 blocks to the nearest stop but experiences little threat of violence?
Another framework for analyzing these dis-amenities is “walkability” which considers three criteria: practicability, safety, and pleasantness (D’Orso and Migliore, 2020). This framework incorporates not only distance but sidewalk quality, architectural barriers to access, street lighting, protection from vehicles, and pedestrian comfort. These indicators, and even the term walkability point toward another important component of access — disability. I use the term disabled because many advocates argue that euphemistic terms such as “differently abled” are actually more harmful as they reinforce the stigma surrounding disability (Brasher, 2019). In terms of access to transportation, what may be a mild inconvenience for an abled pedestrian could represent a serious challenge to a disabled person. For example, while an abled person may be tired after climbing a set of stairs, a wheelchair user literally cannot climb the stairs. Proximity is unimportant if the station does not have an elevator.
For this project, access will be analyzed primarily through proximity and infrastructure. Nonetheless, these broader frameworks of social access and walkability inform my approach to access as not a simple binary yes-or-no question but a phenomenon that occurs on a continuum. At issue is not simply whether someone has access or not, but also the quality of that access.
Mobility
While access describes a rider’s ability to get to a station, this is not the only factor that informs a riders choice to use a transport system. Murray et al. draw a distinction between access and “accessibility” which they define as “the suitability of the public transport networks to get individuals from their system entry point to their system exit location in a reasonable amount of time.” The main consideration here is time although this framing also suggests the importance of the location of a station relative to the rider’s destination. Similarly Wells and Thill discuss three models of accessibility: cumulative opportunity (number of travel destinations within a given distance), gravity-based measures (weighted assessment of travel opportunities against impedance factors), and utility-based measures (assessment of utility relative to other travel options). Additionally they introduce customer-oriented public transportation performance measures such as comfort, convenience, reliability, travel time, etc. which impact the choice to use a service (Wells and Thill, 2011).
These frameworks are in direct conversation with the concept of access however they push further into the territory of what I am calling “mobility.” Mobility here refers to how the transport service actually allows a rider to move throughout the city. How long do they have to wait? Does the service provision actually follow the schedule? Are the buses/trains likely to breakdown and cause delays? Is there accessible infrastructure and does it actually support use of the system? These are some of the many considerations that impact how a rider navigates a transport system and how that chosen system impacts their range of movement. It is important to highlight, however, that the ability to choose a service that provides better mobility is a privilege and it is directly related to access. For this project, mobility will be analyzed through infrastructure and performance metrics.
By the Numbers
Service Performance
The bus system covers nine times as much land as the subway system. The mean distance between bus failures, however, is seventeen times shorter than that of the subways, suggesting that, buses break down more often. Subway ridership is more than double that of buses, despite the fact that there are twenty times as many bus stops, and on average 1.3 times as many people living near (1/4 mi) a bus stop (Figure 2). In fact, over 8 million people live within a quarter mile of a bus stop while only about 3.6 million people live the same distance from a subway station (2019 ACS 5-Year Estimates). All but seven census tracts are within a 1/4 mi of a bus stop while over 853 census tracts are beyond the quarter mile buffer surrounding subway stations (Figures 5 and 6).
Based on proximity and travel “opportunity” measures, buses offer a wider range of movement to a larger number of people. And yet subway ridership dwarfs that of buses. Importantly, the subway has overall better performance measures. Additional wait time and travel time are both lower for subways, and Customer Journey Time Performance, or the percentage of journeys completed within five minutes of the scheduled time, was 12.2% higher for subways. As mentioned above, the distance between failures is also significantly larger. So while there are fewer destination options compared to buses, subways provide mobility in a way that is more predictable (arrive on time) and more reliable (vehicles functioning).
The people
As previously mentioned, Lineberry’s underclass hypothesis suggests that the ‘underclass’ receives inferior municipal services. For Lineberry, the ‘underclass’ signifies “non-Caucasian, low-income, or otherwise politically marginalized residents” (Wells and Thill, 2011). Wells and thill expand on this concept of the ‘underclass’ to also include elderly residents and students because these are populations that tend to rely on others for transportation. I would extend this grouping of politically marginalized residents further to also include the disabled population. From walk-up apartments to subterranean transportation, the infrastructure of the city was largely constructed with an abled body in mind. This structural ableism adds an important nuance to the question of service “quality” that will be explored later in this report. To test Lineberry’s extended theory, I will analyze the racial, socio-economic, and ability landscape surrounding bus and subway stations. I use a quarter mile buffer as an entry way into this question of who lives ‘near’ transportation?
“Race”
It is important to preface this section with an understanding that race is a social construct. Culture and ethnicity are much more complicated than these labels that we cling to. But when collecting and analyzing demographic data, labels serve a purpose. In the subsequent maps, I highlight the Black, White, and Asian communities because they are the largest populations in the city; All other racial identifications are counted under ‘other.’ While this is not how I employ the term, I want to recognize the history of the word ‘other’ as a colonial tool for racial marginalization. I also acknowledge that ‘other’ as an umbrella term simplifies the immense diversity of the populations it includes. Unfortunately, because of the scope of this project and the data available, these are the terms of the analysis.
After creating a quarter mile buffer around bus stops (left) and subway stations (right), I calculated the proportional populations living within those areas. Using the demographic data from the 2019 ACS 5-year estimates, I found the relative populations by race living within those buffers. I also compared these numbers to the citywide racial demographics. I found that the racial landscape within a quarter mile of bus stops is comparable to the citywide numbers. This is unsurprising as most of the city falls within that buffer. The numbers change slightly for the subway buffer, which covers significantly less of the city. Proportionately more white people live within the subway buffer compared to the citywide numbers, and proportionately fewer Black people live within the buffer. The differences become starkly more apparent in the subsequent maps.
All but seven census tracts are within a quarter mile from a bus station. Of those seven tracts, only one actually has a residential population of a few hundred so the above demographic data are skewed by this small size. Nonetheless, in this area, the Black population is proportionally almost double the citywide totals. The white population is also proportionately larger by just over 2%.
Far more census tracts fall outside the subway buffer at 853 total tracts. In these combined tracts, the Black population makes up a 4.66% larger proportion than the citywide number. The white population in these tracts is also 5.11% smaller than the citywide number. Importantly, the 7 census tracts that fall outside the bus buffer also fall outside the subway buffer. Taken together, these maps suggest that Black people have inferior access to transportation.
Income
The above maps symbolize the population living within the quarter mile buffers by median income. Median income cannot represent the income extremes in each census tract and may be skewed in areas with greater wealth stratification. For this reason, I compare not only median income but also average number of households with an income over $150,000 in the buffers and across the city. Interestingly, the subway buffer has a lower average median income compared to the bus buffer and city, but a higher mean number of households with income over $150,000. The lower median may be attributable to the smaller number of census tracts skewing the numbers low. However, the count of high-income (>$150,000) households indicates that proportionately more high-income residents live near subways. The bus buffer numbers are comparable to the citywide numbers.
Ability
The above maps symbolize the disabled population living within the quarter mile buffers. These data represent a total count of disabled people undifferentiated by the specific disability. Because these numbers are counts rather than percentages, I compared direct totals as well as mean count per tract. Overall, significantly more disabled people live near buses. However, the mean number per census tract is higher for subways. The question of whether these populations can actually access these stations will be discussed below.
Accessibility
For this section I focus on the subway stations because by design they are inaccessible. Whereas buses are boarded at street level, a rider must travel above or underground to reach a subway platform. For this reason, the MTA has constructed elevators at certain subway stations, but is that enough?
Using the MTA data on ‘accessible’ stations, I mapped and symbolized subway stations based on the presence or absence of an elevator. I differentiate those stations with an elevator in only one direction (yellow dot) from those with multi-directional elevator infrastructure (green star). However, I count both yellow dots and green stars as ‘accessible stations’ in Table 2. I found that a miniscule 25.96% of subway stations in New York City had at least one elevator. Furthermore, less than 3% of subway stations have an elevator and are located near a census tract with a large disabled population (>32% disabled). For these rare ‘accessible’ stations, the elevators are reportedly functioning ~96% of the time, although the accuracy of this number is questionable as it is derived from an MTA source. However, accurate or not, the vast majority of these outages (71.37%) are listed as non-scheduled. Because these outages are unscheduled, the MTA cannot warn riders of the impediment and allow them time to organize alternative transportation. Not only are ‘accessible’ subway stations largely inconvenient with only 1 in 4 stations housing an elevator, the high rates of non-scheduled outages severely restrict the reliability of this infrastructure. With this in mind, the low percentage of ‘accessible’ stations near disabled populations may actually suggest that disabled people choose not to live near subways because the barriers to mobility outweigh the benefits of proximity.
Limitations
There are quite a few limitations to this study. Most of the performance data are derived from MTA reports. The MTA has an incentive to present positive statistics so these data may be biased or skewed. There are also many limitations to census data. As both a social construct and a personal identity, race is incredibly complex. The boxes on a survey can never truly capture this nuance. Disability is a similarly complicated identity that is incredibly personal and difficult to capture at a population level. While median income is a useful statistics for comparisons, it cannot adequately capture wealth stratification and can under or over represent wealth extremes in each census tract. Additionally, due to xenophobia and the criminalization of immigrants, there are likely many undocumented residents who did not complete the census for fear of deportation, creating an important gap in these numbers.
Additionally, this study contends with the limitations of the ‘container effect’ in which access is determined based on the census tract as a whole rather than a resident’s location. All residents of the census tract are assumed to have equal access to a station falling within the tract and no access at all to resources falling outside the tract (Weiss, 2011). Lastly, these buses and subways are analyzed as two separate systems when in fact they are heavily intertwined. Many passengers use both systems within one trip and this study does not fully account for that.
Conclusions
Taken together, these maps create a complex image of access. An abled subway rider may be willing to walk more than a quarter mile to reach a subway station that provides better mobility, and it is likely that people beyond the buffer do use the subway system. This population does have access to subways, but the longer distance is an extra consideration that only those outside the buffer face. Access is then not a binary phenomenon but a continuum. Importantly, these maps show that proportionately more Black riders have to walk further to reach a station. This supports Lineberry’s hypothesis that non-White, in this case specifically Black residents have inferior access to services. The pattern is less clear when it comes to income. The populations near subway stations have lower average median incomes than buses yet higher counts of high-income households. This data does not support Lineberry’s hypothesis but suggests that both systems reach fairly diverse socioeconomic populations. Similarly for disability, overall, bus stops are located near more disabled people, but the mean count per tract is higher for subways. However, with only 2.84% of subway stations located in these high disability census tracts and having an elevator, it becomes clear that disabled populations do have significantly inferior access to subways. These data do support Lineberry’s hypothesis.
Subways are less accessible by design and by practice. They require extra infrastructure and maintenance to be truly ‘accessible.’ And yet subways are much more popular than buses. The MTA continues to expand ‘accessible’ infrastructure in subways, but is that actually an effective approach to accessibility? Undoubtedly, expanding elevators and escalators will have positive effects for diverse populations from parents with strollers to the elderly. However, the overwhelming barriers for a disabled person to access a subway station cast a shadow over the effectiveness of this patchwork infrastructure. Buses, on the other hand, are much more accessible with stations at street level and kneeling buses. Furthermore, the overwhelming number and route coverage of buses increase the likelihood that the stations will be within a reasonable distance from a passenger’s home or destination. Bus stops are also located near more racially diverse populations. However, the unpredictability and unreliability of buses limits the reality of bus accessibility. Kneeling buses were an important advancement but there is still much to be desired. I would argue that improving the funding and performance of buses would actually be a much more effective approach to improving accessible transportation in the city.
There is still immense work and research to be done in the arena of accessibility in transportation. Future research should look at subway and bus performance relative to the implementation of ‘accessible’ initiatives. Did ridership or performance increase with the expansion of elevators in subways? Did kneeling buses impact ridership? These are important considerations for New York transportation officials as they implement initiatives to address accessibility.
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