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Data visualization on urban transportation | Access to Vibrancy app




11: Urban Studies and Planning

Faculty Supervisor:

Siqi Zheng

Faculty email:


Apply by:

September 20th, 2020.


Adriano Borges Costal: abcosta@mit.edu; https://www.sul.mit.edu

Project Description

OPPORTUNITY. The Sustainable Urbanization Lab (MIT-SUL) is looking for three undergrad students interested in transportation studies. Specifically, we look for two profiles: Two students to work with transportation analysis, who is interested in learning how to work with GTFS data and Open Trip Planner, generate isochrones, and perform accessibility analysis. One student interested in data visualization, with intermediary knowledge on working with R, and who is willing to learn and explore Shiny package. All students eligible, but first-year students will receive special consideration. Position term: September 16th to December 22nd. Compensation: $13/hour, 10 hours/week for 14 weeks. CONTEXT. New transportation infrastructure can trigger built environment changes and leverage the urban vibrancy of neighborhoods. To analyze how transit development - more specifically subway - impacts the opening of new amenities, firm formation, and the real estate market, Sustainable Urbanization Lab (MIT-SUL) is developing the Subway Network and Urban Vibrancy research project. Accessibility analysis is a fundamental tool in transportation studies as it measures the amount of activities and opportunities a person can access given a time constraint, from a specific location. Measuring changes in accessibility allows us to further understand and predict the effect of public transportation on the development of amenities, firms, and therefore, on the way land value changes over time. The research project developed accessibility indexes and analyses for different cities. Students selected for this Experimental Learning Opportunity will work on developing an interactive web application to visualize accessibility for different scenarios and cities.


This is a remote research assistant position. All students are eligible. Familiarity with R is required, experience with transportation analysis is deferential. No prior experience or coursework is required. We are particularly interested in students with a demonstrated interest in transportation, urban planning, and data visualization. Students will be expected to work 10 hours per week. Remote opportunity, but students living abroad will not be able to participate