Street Tree Canopy Equity Analysis Builder

You are a civic data analyst helping a city or nonprofit evaluate street tree canopy equity and planting priorities. Analyze the available data for:

Geography: [city, district, neighborhood, census tract, council district, service area]
Datasets available: [tree inventory, canopy raster, planting records, 311 requests, maintenance logs, sidewalks, heat index, land use]
Tree fields: [species, DBH, condition, planting date, removal date, maintenance status, stump, vacant site]
Equity indicators: [income, renters, age, disability, race/ethnicity if lawful, asthma, heat vulnerability, transit dependence]
Environmental context: [surface temperature, impervious surface, flood risk, air quality, park access, shade corridors]
Operational constraints: [utility conflicts, sidewalk width, underground services, watering capacity, nursery stock, crew capacity]
Time period: [single snapshot, annual trend, planting seasons, maintenance backlog window]
Data quality issues: [missing coordinates, duplicate trees, outdated inventory, inconsistent species names, incomplete requests]
Stakeholders: [urban forestry, public works, sustainability office, neighborhood groups, council, grant funder]
Decision needed: [grant application, planting priority map, maintenance budget, outreach plan, climate action report]
Tools available: [spreadsheet, SQL, GIS, Python, R, BI dashboard, public map]
Privacy and governance: [public data rules, small-area suppression, sensitive demographic use, community review]

Create:
1. Data inventory and join plan by geography and time period.
2. Cleaning checklist for coordinates, species, dates, duplicate assets, and request categories.
3. Equity metrics for canopy coverage, vacant planting sites, maintenance response, removals, heat exposure, and planting investment.
4. Segmentation plan by neighborhood, heat risk, land use, income, renters, age, and other lawful indicators.
5. Statistical or geospatial methods appropriate for the available data, with assumptions and limitations.
6. Dashboard layout with map layers, scorecards, trend charts, and priority lists.
7. Planting priority scoring model with transparent weights and sensitivity checks.
8. Data quality and bias cautions for 311 requests, inventory gaps, and demographic proxies.
9. Recommended actions for outreach, planting, watering, maintenance, and grant reporting.
10. Executive summary template for public-facing communication.

Do not infer protected-class conclusions beyond the supplied lawful data. Flag privacy, community engagement, and local policy questions for qualified review.