Wind Site Suitability Intelligence
GIS-based decision support for wind farm site selection that combines spatial, technical, environmental, and stakeholder criteria into a transparent ranked shortlist.
The Problem
“Wind farm site selection is slow, subjective, and hard to defend across technical, environmental, and stakeholder constraints”
Organizations face these key challenges:
Too many conflicting criteria across wind resource, grid access, land use, environment, and community impact
Manual GIS and spreadsheet workflows are slow and difficult to scale
Site rankings are often subjective and hard to explain to stakeholders
Data sources are fragmented across shapefiles, raster layers, reports, and public registries
Impact When Solved
The Shift
Human Does
- •Gather GIS layers, wind data, land-use constraints, and consultant inputs from fragmented sources
- •Apply exclusion rules and manually score candidate areas in GIS and spreadsheets
- •Debate criteria weights and compare site options in workshops and review meetings
- •Prepare maps, score summaries, and ranked shortlists for planning and investment decisions
Automation
- •No significant AI support in the legacy screening workflow
Human Does
- •Set screening objectives, approve criteria weights, and choose scenario priorities
- •Review ranked site shortlists and validate whether recommendations fit development strategy
- •Investigate exceptions, local context, and stakeholder concerns not fully captured in data
AI Handles
- •Ingest and harmonize spatial, environmental, regulatory, and stakeholder inputs into candidate site evaluations
- •Apply exclusion logic, score sites across criteria, and generate transparent ranked shortlists
- •Run scenario comparisons and sensitivity analysis for different development strategies
- •Estimate permitting, environmental, and stakeholder risk from historical and contextual patterns
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not approve a final wind farm site for land pursuit, studies, permitting, or investment review without a human decision maker.
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Wind Site Suitability Intelligence implementations:
Key Players
Companies actively working on Wind Site Suitability Intelligence solutions: