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Rooted in Data
The Equity Story Inside Tree Canopy Data
The NYC Parks Department tree census data is publicly available, detailed, and largely invisible to the public conversation about environmental equity. The challenge was translating it from a technical dataset into a visual argument that a general audience could engage with — without sacrificing the analytical rigor that makes the argument credible. That tension between accessibility and accuracy is the central design problem in data communication.
Cleaned and merged the NYC tree census with American Community Survey income and demographic data in R, built spatial visualizations using ggplot2, and designed the final poster layout in Figma and Illustrator. Every analytical decision — which variables to map, how to bin income quartiles, which borough comparisons to foreground — was as deliberate as every design decision. The two processes were genuinely inseparable.
- Merged dataset connecting tree density to income quartile and racial composition at the census tract level across all five boroughs
- Statistically significant correlation between median income and canopy coverage visualized and annotated clearly
- Poster designed for public legibility — a general audience can follow the equity argument without a statistics background
- Selected for display in Pratt's 2025 graduate exhibition
Data visualization is an act of translation, not just display
The dataset proved what I suspected. The design work was about making that proof legible to someone who didn't already know the story. Those are genuinely different skills, and both matter. A visualization that's analytically correct but communicatively opaque hasn't done its job.