GIS Brownfield to Greenspace Optimization

ISEF Category: Environmental Engineering

Subcategory: Land Reclamation  ·  Difficulty: Advanced  ·  Setup: Home Setup  ·  Time: 1 to 2 Months

The Hook

One empty lot can change the health of an entire block. A former industrial site near homes, schools, or bus stops may block green space where people need it most. You can use GIS to find which brownfields should turn into parks first. That means your project can connect maps, equity, and real community impact.

What Is It?

Brownfields are sites that may have contamination or a history of industrial use. They often sit unused in cities. Greenspace conversions turn those sites into parks, gardens, trails, or other community land uses after cleanup or reuse planning.

Your job in this project is not to clean up a site in real life. Your job is to rank sites. Think of it like building a scoring system for city land. You combine brownfield location data with demographic and environmental justice data, then ask which sites would help the most people if a city converted them into greenspace.

GIS stands for geographic information system. It is software that helps you layer maps, measure distances, and compare neighborhoods. EJScreen is an EPA tool that shows demographic and environmental burden data, such as income, race, pollution burden, and vulnerability. When you combine those layers, you can find patterns that a simple map would miss.

Why This Is a Good Topic

This topic works well because you can test a real planning question with public data. You do not need a wet lab. You need a clear scoring method, clean maps, and good logic about what makes a site high impact. The project connects land reuse, environmental justice, and urban planning, so your result has real-world meaning. You can also learn how to handle spatial data, compare neighborhoods, and explain decisions with evidence.

Research Questions

• How does adding EJScreen demographic data change the ranking of brownfield sites for greenspace conversion?
• What is the effect of weighting proximity to schools, parks, and transit on the final site score?
• Does a distance-based buffer around vulnerable neighborhoods identify different priority sites than a countywide average?
• To what extent do high-burden census tracts overlap with mapped brownfield clusters?
• Which scoring model best separates high-impact conversion sites from low-impact sites?
• How does the inclusion of population density change the top-ranked sites in each neighborhood?

Basic Materials

• Computer with internet access.
• GIS software such as QGIS.
• EPA brownfield site data.
• EPA EJScreen data.
• U.S. Census tract boundary files.
• Spreadsheet software such as Google Sheets or Excel.
• Local zoning or land use map layers if available.
• Notebook for scoring rules and map notes.

Advanced Materials

• Computer with internet access.
• QGIS or ArcGIS Pro.
• EPA brownfield site data.
• EPA EJScreen data.
• Census tract, block group, and road network layers.
• Parcel boundary data.
• City park, school, transit stop, and land cover layers.
• ImageJ or another image analysis tool for map figure cleanup if needed.
• Python with pandas, geopandas, and matplotlib for repeatable analysis.

Software & Tools

• QGIS: Lets you map brownfield sites, layer demographic data, and build a spatial scoring model.
• Google Earth Pro: Helps you inspect sites visually and compare map layers at a neighborhood scale.
• Google Sheets: Organizes site attributes, scoring weights, and final rankings.
• Python: Helps you automate scoring, clean tables, and test how rankings change under different weights.
• PubMed: Finds review articles on greenspace, environmental justice, and urban health.

Experiment Steps

1. Define your decision rule for what counts as a high-impact conversion site.
2. Choose the map layers that match your question, such as brownfields, EJScreen variables, and nearby community assets.
3. Build a scoring system that combines contamination history, neighborhood need, and access to existing greenspace.
4. Test whether your ranking changes when you adjust the weights on each factor.
5. Compare your top sites against a simple baseline, such as distance from population centers or existing park access.
6. Check whether your results still make sense when you use a different geographic unit, such as tract versus block group.

Common Pitfalls

• Mixing map layers with different geographic units, which makes your scores unfair across neighborhoods.
• Using raw EJScreen values without normalizing them, which lets one variable dominate the ranking.
• Treating every brownfield as equally reusable, which ignores site size, location, and surrounding land use.
• Forgetting to check whether your chosen sites already have nearby parks, which can make your model overcount green access.
• Changing your scoring weights after seeing the answer, which turns the project into a result search instead of a test.

What Makes This Competitive

A strong version of this project does more than make a map. It explains why one scoring model beats another, and it tests that claim with sensitivity analysis or validation against real planning goals. You can make it stronger by comparing several weighting schemes, using neighborhood-level equity metrics, or checking whether your top sites match places where greenness would help the most. Clear methods and careful controls matter more than flashy graphics.

Project Variations

• Use a single city and compare brownfield priorities across neighborhoods with different income and pollution burdens.
• Swap greenspace access for stormwater mitigation potential and rank sites by flood reduction value.
• Compare tract-level and block-group-level EJScreen data to see how geographic scale changes the site ranking.

Learn More

• EPA Brownfields Program: Search the EPA site for brownfield definitions, cleanup basics, and planning resources.
• EPA EJScreen: Use the EPA environmental justice screening tool page to explore demographic and pollution burden layers.
• USGS National Map: Find boundary, land cover, and base map data for GIS projects.
• U.S. Census Bureau TIGER/Line files: Download tract and block group boundaries for spatial analysis.
• NOAA Climate Data Online: Search for local climate and flood context if you want to add resilience layers.
• MIT OpenCourseWare, Introduction to GIS: Look for free course materials on spatial analysis and map design.