|
11.188: Urban Planning and Social Science
Laboratory |
| 11.520: Workshop on GIS (2nd half-semester) |
| Student Name | Title | Abstract | |
| 1 | Katie Pelton | Food Deserts and Coronavirus Cases in New York City (2020) | Prior to the Coronavirus epidemic, 1.4 million New Yorkers suffered food insecurity. Harlem, the South Bronx, and Brooklyn have been designated food deserts. The effects of the epidemic forced New Yorkers to shelter in place limiting their food access to their surrounding blocks. Will those living in food deserts have worse outcomes from coronavirus? This research examines the relationship between access to food retailers and Coronavirus cases through a spacial overlay of these variables on the zip codes of New York City. Rstudio is used to compute, compile, and map the data provided by New York State Open Data. The data has been adjusted by population per zip code. With medical resources depleting, visualizing the spatial overlay of Coronavirus cases and food deserts will help reveal geographical inequity and call for reviewed resource allocation |
| 2 | Amelia Seabold | Exploring the Relationship between Income and Education on Long Island | Taxes on Long Island are fairly high compared to many other areas of the United States, and school districts with better quality schools often charge more in taxes than those without. Does this mean that people who earn more money are more likely to have children who receive a better education? The goal of this project is find out if there is any correlation between education through generations and if so, if income is a link between adult education and children’s education. This analysis was done using American Community Census data for two counties in New York, Nassau County and Suffolk County. For mapping and analyses, unified public school district boundaries are used, and all data is aggregated to this level. Public schools that serve any ages from kindergarten through high school are included, and the measures used to define a school’s quality are attendance level and dropout rate. The dropout rate is for students age 16-19 only, meaning students that did not finish high school. These measures are mapped against median household income for each school district. In order to better understand the trends that appear, scatter plots are included for various school measures and income levels. Finally, adult education is also taken into account. Adults age 25 and over are broken into two categories, those with a Bachelor’s Degree or more of schooling and those with less than a college degree. The adult education is compared to the children’s education in each school district to see if education is correlated through generations, and it is compared to median income to determine a link between education and earnings. |
| 3 | Natasha Stamler | The Demographics of Chicago Air Quality | Air pollution is dangerous because it can lead to
numerous health and environmental harms. The study of air quality
is especially important now, given the Trump Administration’s
recent rollback of regulations controlling particulate matter 2.5
(PM2.5), a major air pollutant, and the correlation of COVID-19
deaths with exposure to PM2.5. This project explores the
relationship between air quality in Chicago and demographic
factors, such as income and race, and health indicators, such as
lung cancer and stroke using PM 2.5 readings from sensors in the
Chicago area and demographic data |
| 4 | Alex Guo | Exploring China’s Air, Rail, and Road Transportation Network Through an Analysis of the Connectivity of Five Unalike Cities | As a rapidly developing country, China has spent trillions of dollars developing its transportation infrastructure in the past few decades, building highways, train stations, and airports. Yet such development is uneven, and in this project we compare the connectivity of two provincial capitals -- Beijing and Lhasa – to the rest of China. Beijing, as China’s capital, is one of China’s four “first-tier” cities, and highly connected to the rest of the country Lhasa, as China’s poorest provincial capital, is located in the remote high-altitude Tibetan Plateau and poorly developed. With web-scraped, crowd-sourced and government-provided data and using a routing API and a modified version of Dijkstra’s shortest-path algorithm we aim to understand how connected China is, which of road, rail, or air transportation modes are the fastest, and how such connectivity differs between cities. |
| 5 | Liza Farr | Comparison of TNC usage in Brooklyn neighborhoods of Fort Greene and Ocean Hill |
Transportation Network Companies (TNCs), like Uber and Lyft, have become an increasingly impactful player in urban mobility. However, they release limited data for public use so little is understood as to how they are being used in urban places. This analysis utilizes New York City’s High Frequency For Hire Vehicle (FHV) trip data by taxi zone to map TNC usage for two neighborhoods in Brooklyn using choropleth maps. I used spatial joins and attribute joins to analyze census data for each of the taxi zones. Fort Greene and Ocean Hill are relatively similar in size and population but Fort Greene has a much higher median income than Ocean Hill. I find that there are over 60% more trips taken from Fort Greene, and nearly double the number of trips per person. Fort Greene trips travel to more neighborhoods and generally spread further than Ocean Hill trips. Analyzing just the top five most popular neighborhoods for pick ups and drop offs for these two neighborhoods reveals that Ocean Hill trips are frequently connecting to other low income neighborhoods. Fort Greene trips are connecting to a mix of low and high income neighborhoods. Subway access is relatively high in all of these neighborhoods, though the top five destinations for Fort Greene have somewhat more subway lines and routes on average. These results indicate that Ocean Hill residents and visitors tend to use TNCs less and over shorter distances than Fort Greene residents and visitors. This disparity may be due to the high cost of TNCs, which is disproportionately felt by people with lower income. Alternatively, social networks and employment networks may be somewhat segregated along income levels, leading the low income residents of Ocean Hill to only need or want to take trips in nearby, low income neighborhoods. Overall, it seems like the cost of TNCs could be limiting the ability of lower income residents of Ocean Hill in using the service to the same extent as the higher income residents of Fort Greene. Further analysis is needed to study whether this disparity based on income is true when all neighborhoods in New York City are analyzed. |
| 6 | Chris Moyer | Building violations in Boston | Building violations are a method by which municipalities enforce standards of safety for their residents. This GIS analysis seeks to investigate if any patterns exist between unsafe conditions of buildings, owner / renter occupancy status and median income. Are more building violations reported in neighborhoods with higher renter occupied units? Are more building violations reported in neighborhoods with higher or lower median incomes? |
| 7 | JingKai Ong | Responding to COVID-19: A Spatial Analysis of County Policies and Mobility Patterns in the U.S. | This project aims to explore the relationship between county-level policy responses and mobility and COVID-19 trends, focusing on the following questions: 1) Do government responses at the county level successfully decrease mobility as intended? 2) How do counties with early restriction policies and decreased mobility compare to counties without in terms of COVID-19 cases and death? 3) Specifically, in New York where the pandemic is the most catastrophic, how do county-level policies and mobility patterns relate to cases and death? The analysis uses data from Google (for mobility), the New York Times (for COVID-19 cases and deaths), and Keystone Strategy (for county-level policies). I map mobility changes by week to show how Americans alter their mobility patterns when they face different levels of movement restrictions and different severity of the current pandemic. I also map policy changes by week showing the different timing of counties’ COVID-19-related policies. Zooming in to the state of New York, I compare case and death trends between counties with different responses and mobility patterns. By overlaying the choropleth maps (of mobility and policies) with graduated symbols (visualizing the change in COVID-19 cases and death), the project presents a time-series analysis of the dynamics in New York at the county level. |
| Student Name | Title | Abstract | |
| 8 | Manil Zenaki | Spatial analysis of the profile of far-right voters in the 2017 French presidential elections | In 2017, Emmanuel Macron came out at the top of the ballot in France and was elected President of the Republic. The vote in the second round of the 2017 presidential election in France gave the following results: 66.10% of the votes for Emmanuel MACRON against 33.90% for Marine LE PEN (“Front National”). The 2017 presidential elections saw Marine Le Pen and her far right political party achieve a historic score. In a Europe where the parties at the extreme end of the political spectrum are growing, where populist and nationalist speeches are increasingly appealing, it is important to understand the profile of the voters. This question is all the more important as the excesses of extreme right-wing political parties are often dangerous. Thus, in this project we will ask ourselves the following questions: Is there any geographical patterns in votes of the 2017 presidential election? What are the geographical and socio-economic characteristics of the vote for the National Front? Is the political support for Marine le Pen more important in geographical areas where economic and social inequalities are the most burdensome? I choose to conduct my analysis at the departmental level (There are 107 departments in France) |
| 9 | Eva Then | A Comparison of Street Scores and Crime Incidents in
Boston |
The broken windows theory proposed by academics James Q. Wilson and George Kelling states that visible signs of crime, anti-social behavior, and civil disorder lead to an urban environment that encourages further crime. My final project aims to investigate this debated theory and further explores the relation between crime and urban perception. Using Streetscore data developed by the MIT Media Lab and crime incident reports provided by the Boston Police Department, my map compares the perceived safety of streets to real safety and captures some of the limitations of Streetscore’s algorithm. |
| 10 | Amelia Dogan | Predicting Childhood Lead Levels | I am looking at the relationship of Philadelphia, one of the poorest largest cities in America, with poverty and childhood lead blood levels. Presence of lead in children can lead to long term disabilities and education attainment. I will create a set of thematic maps based on deep poverty, family poverty, and age of buildings from the ACS and city data. I also use green health indicators like access to trees and childhood after-school programs to buffer and predict where childhood blood lead levels are high. I compare this to actual childhood blood levels in the city and compare relationships between the two different relationships. |
| 11 | Caroline Rosenzweig | Life as an MIT Architecture Undergrad: Spatial
Analysis of my Junior Year at MIT |
For this project, I’d like to explore my spatial patterns and analyse my habits during junior year (Sep.2018 – May.2019). I will use my google tracking data and work in R and ArcMap to create graphical representations of my spatial patterns over the two semesters. My goal is to produce a series of clear, easy to read, maps representing my spatial patterns and how they changed during the course of the year. I think these questions will reveal interesting study behaviours and daily habits that I developed during the year. By breaking these questions up month-month and by semesters I hope to see the gradual change in spatial patterns. |
| 12 | Lovemore Mawere | Title: Visualizing the relative flood vulnerabilities of Pakistan firms based on past flooding events. |
Pakistan is relatively exposed to natural disasters, and is particularly vulnerable to flooding. Flooding is the most frequently recurring natural disaster in Pakistan, and the country is one of the South Asian countries with the highest annual average number of people affected by floods. From an economic perspective, these floods often lead to destruction of productive assets thereby directly affecting the livelihoods of both employees and business owners. This project seeks to identify firms that have been most vulnerable to flooding events from 2010 to 2014. Using data from the UNOSAT flood portal as well as geocoded Pakistan firms’ data, major flood events are tracked, and an evaluation of the extent to which Pakistan firms were affected is carried out. The final output is a map showing location of firms and their relative vulnerabilities to floods as indicated by how frequently they were exposed to these past flooding events. |
| 13 | Emily Levenson | Seasonality, Cost, and Prevalence of Short Term Rentals in Venice, Italy | Before a pandemic led to canceled flights and
quarantine, the streets of Venice were overwhelmed with 30 million
tourists a year. The local population trickled to one third of
1950’s levels. Now the alleys and canals are deserted as the
pandemic shuts Venetians inside their homes. This pause provides
an opportunity to reexamine the lagoon city’s strained
relationship with its visitors. Inside Airbnb publishes monthly
datasets cataloguing the prevalence of Airbnbs in cities around
the world. I will use this data to visualize the short term rental
landscape pre-pandemic and answer the following questions. 1. Was tourism in Venice seasonal pre-COVID-19? Some locals claim a steady stream year-round. Understanding the flow of visitors in more granular detail would allow city officials to regulate Airbnbs, and perhaps limit the number of permits available based on seasonal demand. 2. Which areas in Venice are the most expensive for tourists? 3. Which areas have the most Airbnb units compared to the number of local residents? I will use Italian Census data to find these “touristified” neighborhoods. |
| 14 | Jackie Chen | Understanding the Access to Resources in Palestine | By exploring the distribution of hospitals, roads, barriers and other infrastructure of the West Bank with respect to the location of Palestinian and Israeli communities, the topic of interest becomes a matter of mapping or emphasizing the differences in access to resources between Jewish-Israelis and Palestinians. The problem relates to exploring the Israeli-Palestinian crisis and understanding the Palestinian narrative and the high poverty rates of Palestinians. The data used include the location of health sites, barriers, closures, Palestinian communities, and Israeli settlements. These points, polygons, and polylines are then over-laid onto a West Bank Shapefile and polygons of the West Bank Oslo Accord Divisions. It would be interesting to also visualize the population distribution of the West Bank, so a maps may be generated with a thematic map of the population densities in the governorate of the West Bank. This processing of the maps will take some use of joining data tables and converting the excel data into readable formats for ArcMap. If time permits, creating a simple interactive map can give some textual context/articles that raise awareness of lack of resources and funding received by Palestinian communities. Most of the work will go into filtering out the data to create very legible maps. Based on prior knowledge and research, it is expected that the maps will reveal a bias in the distribution of health sites and barriers against Palestinian communities. |
| 15 | Miriam Wahid | Environmental Justice in Rural North Carolina: Mapping Environmental Hazards and Income Demographics for Counties in the Piedmont | The social and economic histories of rural North Carolina have created particular conditions of environmental hazard. Agriculture, industrial facilities, mining, waste management, and abandoned mills dot the landscape of rural counties and pose risks to the local water quality. In this project, I will investigate the environmental hazards in my home county of Rowan County, as well as in five neighboring counties, in order to understand the extent to which residents there are exposed to hazards which can pose risks to their health and wellbeing. Furthermore, I will investigate the disparities between which households are most exposed to these hazards. Using median household income as a demographic factor, I will explore how environmental injustice plays out in rural North Carolina. My central question is: What is the relationship between the location of environmental hazards in Rowan County and the median household income of the people living in closest proximity to these hazards? |
| 16 | Darla Earl | MBTA Electric Fleet Charging Site Analysis | The Massachusetts Bay Transportation Authority (MBTA) operates 170 bus routes in the Metro Boston area and has begun switching the bus fleet to hybrid and battery-electric buses. While the current infrastructure and established electric utility are sufficient, as the fleet size increases the MBTA will require upgraded maintenance facilities as well as on-route charging stations to keep the electric bus service operating smoothly. My project focuses on locating suitable sites that the MBTA could possibly purchase to build a new maintenance facility or purchase/lease to install on-route charging. Using ArcMap, data layers (town boundary, road network, bus lines, bus stops, electric substations, and public electric vehicle charging stations) provided by MassGIS open data portal and parcel data provided by MAPC (Metropolitan Area Planning Council) are combined for analysis. An 800-meter radius Buffer layer is created of four bus lines (1, 28, 111, and 351). A new shapefile is created of parcels which intersect this layer to be searched for parcels within further size and land use constraints. In particular, parcels and plots that are coded as commercial parking lots are considered along with open and vacant plots because these lots are a great resource for short-term charging of large vehicles like buses. Finally, to verify accessibility, the road network and chosen parcels are used as inputs to the route builder in Network Analyst to model actual driven paths from the station to the parcel. The final output so far is a summary of the opportunities overall as well as several individual plots by each bus route that the MBTA could consider. |
| 17 | Ana Fiallo | Understanding the Solar Energy Transition in the US | As the planet faces the growing threats posed by climate change, transitioning countries’ sources of energy to renewable energy sources provides numerous solutions to reducing societal carbon emissions and impedes the warming of global temperatures. Authority and choice over one’s sources of energy, however, varies by state in the United States and is influenced by various factors, including government energy policies, the socioeconomic state of the population, the costs of installation, the suitability of available land for installations, and the potential generation capacity of the energy source. The goal of this project is to investigate the distribution of photovoltaic (PV) installations across the US and explore the influence of some of the underlying factors for the prevalence of PV solar energy use. Understanding these and what actions are correlated to positive prevalence of solar energy generation will help governments and communities follow the most efficient steps towards increasing access to solar energy in their area. |
| 18 | Jenny Choi | Bike Share-ability: An Accessibility Analysis of Boston’s Bikeshare Program | Over the past few decades, the transportation world has been disrupted with the rise of new transportation forms, from autonomous vehicles to ride-sharing services. Recently, bikeshare programs are on the rise and have been successfully integrated into transportation systems across the globe. Closest to home is Bluebikes, a public bikeshare system with over 3000 bikes and 300 stations operating in Boston, Brookline, Cambridge, Everett and Somerville. Bikeshare programs are generally expected to have positive effects on the community, aiming to increase mobility, encourage physical activity, and reduce road congestion. While Bluebikes has certainly been successful as one of the largest bikeshare programs in the United States, I am interested in analyzing how equitably such opportunities for increased mobility and activity are distributed over the Boston area. I will do this by using ACS, Bluebikes System data to map access to the service for different populations, including by income, race, activity level, and car ownership. This preliminary research has the potential to develop into a broader study of Bluebike’s impact on transportation and quality of life in Boston. It could also be used to formulate ways to evaluate other bikeshare systems, since no concrete standards are yet in place. |
Last modified: May 12, 2020 by jf
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