NYU CUSP’s Capstone Program brings together student research teams with government agencies, industry, or other research partners to address real-world urban challenges through data. The capstone presentations are the culmination of their six-month projects and mark the final presentation of the students’ work during their studies at CUSP.
CUSP spoke to several of this year’s capstone teams to understand more about their research, and how their projects could help improve urban life, both in New York City and other cities around the world.
Mapping Sustainable Mobility in NYC Nightlife Culture
CUSP Students: Nicholas LiCalzi, Kaifu Ren, Yingyuan Zhang, and Yutong Zhu
Capstone Sponsor: VibeLab
CUSP Capstone Mentor: Kim Mahler
Please give a brief overview of your capstone project.
Nightlife is a major economic and cultural driver for NYC, and our initial research goal was to use multi-modal time series transportation data as an advocacy tool to help local stakeholders in the nightlife industry (dance clubs, music venues, bars, and more) demonstrate their contribution to NYC’s citywide and hyper-local night-time economies. With the arrival of the COVID pandemic, we’ve expanded our research goal to examine how the night economy has been uniquely impacted by the crisis in the hopes of enabling policymakers to develop a nuanced understanding of the role of nightlife in the City and develop a uniquely targeted package of policies and aid that ensure its continued vitality.
Why did you choose to work on this capstone project?
As a mix of newcomers and NYC lifers, full-time students and professionals, we understand that diversity is key to a city’s vitality– diversity of spaces, diversity of places, diversity of people, and diversity of experience. Transportation and nightlife have long been the city’s great equalizers– people from all over sharing space and time, moving together.
We have friends who work in restaurants, in bars, in clubs; friends who work as DJs; we miss going out to dance and know that every club or bar we lose due to COVID disruptions represents the loss of a cultural and/or social community space.
How are you collecting and analyzing the data needed for this project?
Much of our data is open source– from NYC and NYS sources dealing with time-series and geo-data about transportation and the built environment, Citibike, U.S. Census data, and more. We have scraped some data from the web, pulling addresses and opening hours for local venues from a number of sources, as well as event listings and more. Our project sponsor, VibeLab, shared with us data they collected on local venues as part of their Creative Footprint industry survey as well.
We’re using a suite of tools, largely in Python but also QGIS, covering time-series analysis, geospatial analysis and spatial interpolation, machine learning for clustering analysis, and more.
Did the COVID-19 pandemic affect your project?
COVID-19 directly affected our project and the groups we were hoping to assist– even before Governor Cuomo ordered the shuttering of all non-essential businesses in NYS, gatherings of more than 50 people were banned, effectively destroying the business model of all nightlife establishments. However, the resulting drop in public transportation usage presents urban scientists with an incredible research opportunity– we’ve built a baseline model of the transportation landscape as it looked in comparable months from 2019 and will explain exactly how each mode (bike, bus, subway, and taxi/for hire vehicle) were affected at each step of the onset of the pandemic.
How does your research relate to CUSP's mission of helping cities around the world become more productive, livable, equitable, and resilient?
Our research deals in large part with transportation accessibility and equity– how are people moving around the City at night? Are there specific patterns of mode choice that are geographically specific and deal with the built environment? Are there parts of NYC where women are more or less likely to take a bike? Does that hold true for the night-time as well, and can we learn anything about perceived safety through that knowledge?
What importance does a city’s nightlife have on its economy and culture? How many people are traveling at night, and what modes are they using? How can cities better support their nightlife spaces, and what impact might that have on them? These are all questions that we hope to answer.
How could your research be used in NYC or other cities after your project has concluded?
We plan on sharing our aggregated dataset publicly at the end of our project so that other people might be able to pull out their own insights and replicate our work in their cities– what would this research look like in LA, or in London? Might those cities be inspired to start collecting/publishing similar types of open data in the hopes that they can enable these kinds of analyses?
What did you wish you knew before starting this project?
We’re thankful for the presence of the Data Visualization course in the CUSP curriculum this summer– very excited to learn some more about producing interactive visuals to help demonstrate some of our findings!