README.md

metadata

title: GIS322FinalProject
sdk: docker
app_port: 7860
pinned: false

Urban Vegetation Dashboard — Maricopa County, AZ

Christian Anderson GIS 322 Spring 2026 Instructor: Debayan Mandal

---

Description

This interactive Solara dashboard explores the relationship between NDVI vegetation index, tree equity scores, and U.S. Census demographics at the block-group level across Maricopa County, Arizona. Users can visualize a bivariate choropleth map comparing greenness to demographic variables (Income, % Minority), toggle a Tree Equity Score overlay, and inspect a summary statistics table and chart of the top 15 block groups most in need of tree canopy investment.

---

Screenshot

---

Data Sources

Dataset	Source	License
NDVI (vegetation index)	Google Earth Engine — Landsat/Sentinel composites	Free for research/education
Block-group demographics	U.S. Census Bureau ACS 5-Year Estimates	Public domain
Tree Equity Scores	American Forests — Tree Equity Score	Free download
Block-group boundaries	U.S. Census TIGER/Line Shapefiles	Public domain

---

Environment Setup

1. Virtual environment

pip install -r requirements.txt

2. Census API key (free)

Sign up at https://api.census.gov/data/key_signup.html, then either paste your key into data_pipeline.py when defining CENSUS_API_KEY

3. Google Earth Engine (free for students)

1. Sign up at https://earthengine.google.com with your Google account.
2. Authenticate in anaconda prompt:

   python -c "import ee; ee.Authenticate()"
   

3. Create a project at https://console.cloud.google.com (free tier).
4. Paste your project ID into data_pipeline.py where it says ee.Initialize(project="gis322final").

4. Tree Equity Scores (free)

1. Go to https://treeequityscore.org/map/
2. Click Download Data → Arizona → Shapefile
3. Save to data/raw/az_tes.shp

5. Build the database

Run this once (~5 min) to fetch and process all data into processed_dashboard.db:

python data_pipeline.py

---

Run Instructions

solara run app.py

---

Project Files

File	Purpose
data_pipeline.py	Run once to fetch data and build processed_dashboard.db
app.py	Solara dashboard — launch with solara run app.py
dashboard_helpers.py	Map and chart builder functions used by app.py
requirements.txt	Python dependencies
data/raw/	Place downloaded raw files here