Run Comparative Analysis

The real power of scenario planning comes from comparing your intervention against the baseline. Let's quantify the impact of your changes!

Running Analysis in Scenario Mode

When a scenario is active, any analysis you run uses the scenario data instead of baseline.

Step-by-Step: Compare Catchments

Baseline Analysis:

1. Deactivate your scenario (return to baseline)
2. Run catchment area analysis from existing facilities
3. Save/note the results

Scenario Analysis:

1. Activate your scenario
2. Run the same catchment analysis
3. The new facility will be included

Step-by-Step: Compare Heatmaps

For a more comprehensive view:

1. Generate Baseline Heatmap

• Switch to baseline mode
• Run gravity heatmap analysis
• Name the result "Baseline_Accessibility"

2. Generate Scenario Heatmap

• Activate your scenario
• Run same heatmap analysis (same parameters!)
• Name the result "Scenario_Accessibility"

3. Calculate Difference Use GOAT's comparison tools or export data to calculate:

$$ \Delta A = A{scenario} - A{baseline} $$

Where positive values = accessibility improvement.

Visualizing the Comparison

Side-by-Side View

Use GOAT's split-screen or swipe tool to compare:

• Left: Baseline accessibility
• Right: Scenario accessibility

Difference Map

Create a "change map" showing:

Color	Meaning
🟢 Green	Accessibility improved
⚪ White/Gray	No change
🔴 Red	Accessibility decreased

Heatmap showing accessibility distribution

Quantifying Impact

Key Metrics to Calculate

Coverage Metrics:

• Number of people within 15-min walk (before vs. after)
• Percentage of area with "good" accessibility
• Average accessibility score change

Equity Metrics:

• Improvement in underserved areas
• Change in accessibility for vulnerable populations
• Reduction in accessibility inequality (Gini coefficient)

Example Analysis Results

For our community center scenario:

Metric	Baseline	Scenario	Change
Pop. within 15min	12,500	18,200	+5,700 (+46%)
Avg. accessibility	245	312	+67 (+27%)
Low-access areas	34%	22%	-12 points

Comparing Multiple Scenarios

If you created multiple location options:

Decision Matrix

Criterion	Weight	Option A	Option B	Option C
Population served	30%	5,700	6,200	5,100
Low-income pop. served	25%	2,100	1,800	2,400
Construction cost	20%	€2.5M	€3.1M	€2.2M
Transit access	15%	Good	Excellent	Fair
Land availability	10%	Yes	Partial	Yes
Weighted Score	100%	78	82	71

Multi-Criteria Analysis

Don't just optimize for one metric. Consider accessibility, equity, cost, and feasibility together.

Statistical Tests

For robust analysis, consider:

• T-test: Is the average accessibility significantly different?
• Spatial autocorrelation: Are improvements clustered?
• Sensitivity analysis: How do results change with different parameters?

Next Step

You have compelling results! Let's present your findings effectively.

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