Green Space Data Challenge Winners: Specific Populations Category

Over the month of February, MDI hosted the Green Space Data Challenge, inviting undergraduate and graduate students as well as early career professionals to use green space data to create or improve indicators to better understand and measure community impact in four categories: community health, community safety, physical environment, and specific populations. Over the next few weeks, we’ll be featuring Q&As with the winners of each category’s first place prize on our Medium page. To kick off this series, we’ll hear from the winners of the Specific Populations category.

Specific Populations Category Winner: A Project on Environmental Justice

Yifan Bian and Kandong Han, both graduate students at Georgetown University, have known each other a long time. They lived on the same block in Shanghai and came to the United States together. However, their collaboration for the Green Space Data Challenge was their first time working together. Combining their skills and expertise — Yifan is majoring in data science and analytics, while Kandong is studying integrated communications — they focused their project on environmental justice in Washington, D.C., taking first place in the Specific Populations category.

Q: Why did you take on this data challenge?

A: We wanted to learn something new, and we thought the challenge would help us improve our analytic and technical skills. Also, we are both interested in environmental justice and sociology and their intersection with green space data. This was a new kind of project for us, and we thought it would be good experience for our future careers.

Q: Tell us about your project. What was the problem you wanted to solve and what did you do with the data?

We knew we wanted to focus on Washington, D.C., because we live and go to school here. Initially, we wanted to look at the problem of homelessness in D.C., but we couldn’t get the data we needed to do spatial analysis. So, we took a closer look at the data available to us and found we could analyze access to green space by race.

For this project, we used the EnviroAtlas database, which provides geospatial data on the relationship between people and nature. First, we analyzed the distribution of green space in D.C. Second, we looked at racial distribution. Third, we combined these two measures to examine access to green space at the city block level, specifically whether having a higher proportion of non-white residents was associated with a higher green space rate. And then finally, we analyzed the implications of our findings.

Our focus was on identifying racial disparities within the metropolitan D.C. area, including parts of Virginia and Maryland. We identified a scarcity of green space in central areas of the D.C. region and along interstate highways, all places with higher proportions of non-white people. And, when we examined the data at the city block level, we found a negative correlation between the rate of green space and the rate of non-white people. In other words, if you live on a block with more people who are not white, you are less likely to have green space nearby. So, you have less opportunity to enjoy nature and exercise and socialize with other people outside. In addition, this lack of green space affects how healthy your environment is, as we found that areas with larger non-white populations also have more greenhouse gases and are hotter.

Q: How did you decide on which dataset to use?

A: We wanted a dataset that would allow us to do spatial analysis. EnviroAtlas met all our other needs as well, so it was a good fit for us.

Q: What motivated you to focus on this topic area?

A: We wanted to focus on environmental justice and disparities in green space resources. It is important to know where these disparities are so that they can be addressed. Everyone should have access to green space, not just people who live in wealthier and predominantly white communities.

Q: How do you envision communities using what you created?

A: We hope the D.C. government will use these findings to create more green space in communities that don’t have. That’s something the government can easily do. It’s very important for people to have green space; it will change a lot of people’s lives.

Q: What would you like to see happen with your idea/project next?

Most of all, we want our project to have impact in the real world. We hope that will happen.