Code for Environment 2nd Place
- Vivian Li
- Aug 10
- 2 min read
Ayvian Earth | USA
CanopyRx is built around a simple problem: cities often plant trees where projects are easiest to complete, not where canopy would do the most good. Our program turns that uneven decision-making process into a transparent, adjustable planning tool.
Using neighborhood-level data from the U.S. Census and NYC Open Data, CanopyRx evaluates four conditions: heat vulnerability, community vulnerability, flood exposure, and school access. Users can change the weight of each factor, set a budget, and generate a ranked set of priority neighborhoods. The interactive map then shows each area’s overall score and the statistics behind it, while the recommendation list identifies the two conditions that contributed most strongly. This matters because a recommendation is only useful if planners can understand why it was made.
CanopyRx also goes beyond ranking. For any neighborhood, it estimates what concentrating the selected budget there could accomplish, including the number of trees planted, additional canopy, residents gaining access to shade, stormwater intercepted, and high-heat land improved. It also suggests a tree species suited to the area’s environmental conditions.
The project is designed to scale. Data is loaded directly into the program through public database links, so adapting it to another city would mainly involve replacing those links with equivalent local Census, environmental, and geographic datasets. Since census systems and public spatial databases exist across much of the world, the same framework could support larger regional or international planning efforts.
CanopyRx advances SDG 11 by improving urban livability, SDG 13 by addressing heat and flooding, and SDG 15 by expanding urban canopy with more appropriate species. Its primary goal is help limited funding reach the places where trees can produce the greatest public benefit.
*To run the program, a Census Data API Key is needed. The program will prompt you to enter one.
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