A city map glows red near the railway station and pale blue along quieter streets. It appears to show where everyone went. In practice, a location heatmap is a statistical picture built from a dataset—one that may represent only particular devices, times and collection methods.
A heatmap is not a photograph of the population
Software can group location observations into geographic cells and shade each cell according to a count, a density or a derived score. The resulting visual can help transport planners study movement or analysts compare patterns. But it is only as representative as its source data. A dataset skewed toward particular apps or phones may underrepresent people who do not use them.
A high-value cell can also mean several different things: many distinct visitors, many repeated observations from a small group, or long dwell times, depending on how the data was constructed. Without a legend and a method description, the same striking colour gradient can tell multiple stories.
Did you know? Ten thousand location records do not necessarily represent ten thousand people. One device can produce many repeated observations.
Aggregation reduces detail but not every risk
Combining observations can help protect individual privacy, yet small groups and unusual movement patterns may remain sensitive. Repeated home-to-work journeys, visits to clinics or attendance at intimate events can carry information that people did not intend to publish. The FTC has taken actions involving sensitive geolocation datasets, underscoring the consequences of careless data collection or sale.
Researchers distinguish between what a map seems to show and what the sampling process actually supports. If the underlying observations are old, incomplete or geographically biased, conclusions may be unwarranted even when the graphic looks precise.
Read a movement map with four questions
Ask who contributed the observations, when they were collected, what the colours measure and whether small groups were protected. For public reporting, give enough methodological detail to make the limits intelligible. For organizations, collect only what is needed and define retention periods.
Explore what location history can reveal about habits and the market for your movements.
Follow the evidence, not the fiction.
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