Student	Project Title	Project Abstract
Nicole Wilson	Urban Inequalities in Lagos, Nigeria	The continent of Africa is urbanizing at an incredibly rapid rate. Of the 30 fastest-growing cities in the world, 21 are in Africa. Nigeria is at the center of gravity of this growth, projected to become the third-largest country in the world by the year 2050. While much of this growth is happening in secondary cities, megacities such as Lagos remain important. Inequality is also rising with urbanization in this region, and while much of the scholarly focus is on urban-rural inequality, there is also significant intra-urban inequality. To explore spatial inequality in Lagos State (the administrative unit that contains most of the Lagos metropolitan area), I look at the relationship between distance to social infrastructure and population density to identify the areas with the best and worst access to services. I also consider the difference between access to both public and private alternatives of the same service, such as schools or health clinics. Finally, I consider whether access to social infrastructure is correlated with more formal or informal patterns of development as measured by the scale and orientation of road networks. On the one hand, we may expect that more well-laid out or “formal” areas can better advocate for government services. On the other hand, however, given the relatively low quality of many public schools and clinics, these populations may instead be served by private alternatives.
Alena Culbertson	Next Door to Whom?: Spatial Distribution of Land Uses of Former Vacant Properties in New Orleans	After Hurricane Katrina, thousands of New Orleans residents sold their property to the federal government as part of the Road Home program’s payments for hurricane-displaced residents to rebuild their homes or move somewhere else. Many of these properties were turned over to the non-profit New Orleans Redevelopment Authority, which was tasked with finding uses for these now-vacant properties. This project tracks the spatial patterns in the category of use each current NORA property or NORA property sold between 2006 and 2021 falls under, which includes sale (at a reduced price) for affordable housing development, sale (also at a reduced price) to a next-door neighbor, sale at auction to the highest bidder, sale to be turned into green space, and present vacancy due to lack of sale. This is primarily accomplished by linking each NORA property to the 2010 Census block group it falls in and visualizing the percentage of NORA properties in each block group that fall into each category, then considering these spatial patterns alongside Census data on the spatial distribution of racial and socioeconomic characteristics. This analysis finds that a property’s use for affordable housing is strongly correlated with its location in a primarily-Black block group, while sale to next-door neighbors or at auction is correlated with location in a whiter block group.
Naylah Canty	Accessing Atlanta: Mapping & Characterizing Communities Under-served by the Metro Atlanta Rapid Transit Authority (MARTA) System	Atlanta’s Transit System, MARTA, offers an uncomplicated mode of transportation for urban Georgians with only four transit lines traversing along the cardinal directions (east to west, west to east, north to south, and south to north). However, this simplicity ignores the drastic geographic disparities in educational attainment, employment, and income level across each quadrant of Atlanta. As gentrification progresses in this city, areas with high proximity & accessibility to transit stations are being settled by those who won’t use or don’t rely on public transportation. This study seeks to map the concentration of economically vulnerable populations (defined as areas containing primarily below-college educational attainment, low income, and high unemployment) in relation to their proximity to any of the four MARTA transit lines, in order to reveal the existence and/or magnitude of a gap in transit accessibility across these indicators. These indicators will be joined to U.S. 2020 census block group shape files. The area under analysis will be within a 15-mile radius of Five Points Station (the only layover station between all four lines, considered the center of MARTA) being that this radius includes all MARTA stations, despite not all regions within the radius having an Atlanta zip code. My social indicator data will come from Rand State Statistics, while the shapefile data for the routes will come from MARTA’s public app development resources.
Tanner Bonner	Disparities in Accessibility to Mental Healthcare and Related Services in Wayne County, MI	This project investigates how spatial analyses reveal disparities among communities regarding select measures of accessibility to mental healthcare and related services in Michigan. The project explores the spatial distributions of services sourced from the 2021 Substance Abuse and Mental Health Services Administration’s Treatment Service Locator and 2019 National Mental Health Services Survey. I compare these distributions to multiple factors sourced from the 2019 American Community Survey (5-year estimates) on a block-group scale specifically in Wayne County. These factors for which research consistently associates with disproportionately negative mental health outcomes include the percentage below poverty status, median household income, unemployment rates, and health insurance coverage type and rates. I explore the measures of each of these variables, leveraging choropleth mapping and filtering to identify particularly at-risk block-groups. Furthermore, I investigate the frequency of mental healthcare sites near these at-risk block groups in comparison to others in Wayne County with buffers and aggregation. Lastly, I draw comparisons between Wayne County and other counties in Michigan with regards to the aforementioned factors, as well as data from Michigan’s 2018 Green Book Report of Key Program Statistics regarding crime and violence rates and rates of receiving government aid (e.g. food stamps). Overall, the analysis identifies communities that may be particularly vulnerable to negative mental health outcomes and face barriers in accessibility pointing to where future investments into mental healthcare should be prioritized.
Yu Jing Chen	Anti-Asian Hate in New York City	2020 was a year of unprecedented trials and tribulations, not only bringing upon COVID-19, a global health pandemic that has disparately affected under-resourced communities in particular, but also bringing upon a surge in anti-Asian racism. This past year, anti-Asian hate crimes have come to a head, with over 3,795 reported hate incidents since COVID-19 first hit America. This is especially startling given the fact that the Asian community is one of the marginalized groups least likely to report due to barriers such as language or distrust that doing so would actually amount to change or accountability. New York City in particular is reported to have experienced a 200% increase in hate crimes from the first quarter of 2020 to the first quarter of 2021. This project will explore the relationships or patterns between anti-Asian hate crimes in NYC along with where and how they occur, from the physical location and built environment that these crimes take place in to how that may relate to the demographics of the victims. Additionally, especially as conversation about defunding the police is taking over the nation, many Asian communities find themselves on different sides of the conversation as their communities are being attacked. With overlays and buffers, I will also map out police presence and observe any correlation that may have on the presence of hate crimes if any. Especially as policy is being formulated around anti-Asian hate crimes today, it is especially pertinent that there be good data to inform policy action.
Moctar Fall	Air Quality, Health and Transportation in East Harlem	New York City has been known to be one of the most tourist attracted cities in the world for years and years. But not a lot of people outside of the city know it as a major artery for cars and tractor trailers to go through. Having been raised in Harlem, I’ve firsthand experienced the effects of the fumes that tractor trailers and diesel trains leave behind, with many of my neighbors and friends suffering from asthma in my childhood and to this day. For this project, I draw the correlation between air quality and transportation in East Harlem -- with the guidance of US Census Data, US ACS Community Survey Data, and NYC Open Data (surveys as well as location data) -- to posit the question of replacing the FDR Drive and repurposing avenues to provide efficient and sustainable transportation that doesn’t put East Harlemites in danger of respiratory illnesses.
Gabriel Barrett	No Place Like Home: An Analysis on Pre and Post Pandemic Evictions in Boston	With millions of people finding themselves without a job in March and April of 2020, there was a large push urging local, state, and even the federal government to halt all evictions. Starting on April 20th, an eviction moratorium was put in place in Massachusetts. However, this stopgap solution had an expiration date and just 6 months later on October 17th, the evictions were allowed to continue. This project is an analysis of on evictions in the core cities of the Boston Area both before the Pandemic and in the months after the first eviction moratorium was lifted. The research will look at Massachusetts census tracts see if community characteristics such as home renter rate, median rent price, rent burden, and racial/ethnic make-up correlate with eviction rates. The eviction information is gathered from the Princeton University Eviction Lab and MassLandlords. The demographic and household data is pulled from the Census American Community Survey. Through the use of thematic maps and scatter plots, the project aims two answer two central questions: What characteristics do the neighborhoods with the highest rates of eviction in pre pandemic Boston share, and do these trends hold in evictions rates post moratorium?
Jola Idowu	What is Affordability in Boston?	Boston has a history of income restricted housing and home ownership across various Boston neighborhoods. Like most cities, Boston utilizes HUD data to determine income levels that qualify for income restricted housing according to the Area Median Income. However, the use of AMI is a general measurement that does not take into consideration particular factors such as family size and neighborhood income disparities. For this project, I attempt to disaggregate public housing and income data to see how affordable Boston is and for whom is it affordable?
Tracy Sorto	Changes in Socio-Economic Trends with Increase in Lab Use and Tech Industry in Cambridge	Many cities across the country have experienced some form of gentrification, and Cambridge is no exception. Current zoning and land use trends, coupled with the increase in demand for lab space, may play a role in gentrification patterns in Cambridge. In this project, I aim to analyze socio-economic trends in comparison to land use and employment patterns in Cambridge over time. I hypothesize that the median income and housing prices around the new lab spaces will increase as lab employees start to move in closer to their job. To test this hypothesis, I would like to track the increase of land used for lab space, as well as the subsequent changes in the labor force makeup in Cambridge. To analyze these patterns, I will use land use and labor force data from 2011 and compare it to the most recent data. From there, I will use demographic data to see how these changes correlate with trends in population density, median income, and housing prices. I plan to compare the demographics in a buffer around the new lab spaces to the demographic data in those areas in the past. From this, I hope to begin a conversation around the role of land use patterns and the impact of increased lab development on existing communities.