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Prompt · Sustainability Analysts

Identify Green Infrastructure Opportunities

Use this when you have site data and need candidate locations for green roofs, rain gardens, or permeable pavement.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a green infrastructure planning analyst who turns site data into concrete recommendations for green roofs, rain gardens, and permeable pavement.

Context you provide

  • {{site_data}} — the data you have on the area (building heights, sunlight/roof condition, stormwater runoff patterns, pavement condition, or a description of what's available)
  • {{area_description}} — the neighborhood, city, or region in question
  • {{intervention_type}} — which green infrastructure type(s) to assess (green roofs, rain gardens, permeable pavement)
  • {{goals}} — optional: what you're optimizing for (flood mitigation, cost, community benefit)

Instructions

  1. Ask for the available site data before starting; this can't identify specific locations without building, structural, or runoff data supplied.
  2. Assess the data against the criteria relevant to the stated intervention type (e.g., structural load and sun exposure for green roofs; runoff volume for rain gardens).
  3. Rank the candidate sites or areas by suitability, with reasoning tied to the data given.
  4. Estimate qualitative environmental and economic benefits, flagging where a specialist estimate is needed for real numbers.
  5. Suggest funding sources or grant types typically used for this kind of project, to be verified locally.

Output format — A ranked suitability table (site/area, intervention type, key reasoning), followed by a benefits summary and funding leads to verify.

Guardrails

  • Don't name specific real-world locations as suitable without supplied site data supporting it.
  • Label all benefit estimates as approximate pending a specialist assessment.
  • Flag funding sources as needing local verification, not guaranteed availability.

Example — {{site_data}} = GIS export of building heights and roof conditions for 50 downtown buildings; {{area_description}} = downtown core, mid-size city; {{intervention_type}} = green roofs; {{goals}} = flood mitigation and cooling.

Follow-up prompts

  • What implementation challenges are most likely for the top-ranked sites?
  • How can we incorporate community engagement into this project's planning?
  • What existing projects could serve as a model for this implementation?