The advantages of planning with People Movement Data

October 16, 2023

People Movement Data aggregates location data from mobile devices, and this fact makes it uniquely powerful for finding spatial insights.

A unique and powerful dataset

Thanks to its inimitable properties, People Movement Data can deliver a distinctive perspective into how people move and do so in ways that’s applicable for a wide range of planning projects. A few examples include:

  • A tourism region’s local council can learn where their out-of-state visitors are coming from to geographically target their marketing efforts
  • A network planner can compare two prospective store locations to understand which one has more pedestrian activity
  • A traffic and transport team can see where people are travelling to after they leave their car at a ‘Park and ride’
  • An urban planner can perform a post-implementation analysis of an asset to see how well it’s performing its place function
  • An economic development expert can use movement activity to compare the day and night-time economies of a commercial precinct
  • An open space team can locate exactly which areas of a park are getting used the most
  • A public transport planner can assess the travel impacts of a rail line closure to help minimise impact during future closures

All these examples beg the question: why does People Movement Data stand out as a way of uncovering geospatial insights?

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See how people move, naturally

People Movement Data is an aggregated dataset that is gathered through apps on mobile devices, fitness trackers and vehicles. This means that it shows people moving in uncontrived, organic ways. Perhaps more importantly, it offers movement insights into any places that people travel with mobile devices – many of which (such as parks and open spaces) are usually difficult to analyse using more traditional geospatial datasets.

Base mapActivityDwells
People Movement Data can depict where people are moving and where they're dwelling in granular detail.

An unmatched level of spatial accuracy

Over the past 15 years, mobile device owners have come to rely on their device’s GPS capabilities for a range of everyday tasks, with more and more app developers leveraging the technology to enhance their app’s utility for their users. Mobile devices, subsequently, move almost everywhere that people move.

The reason for this? The value of GPS and other mobile phone sensors, both for developers and device users, lies in their high degree of spatial accuracy. This is a defining benefit of People Movement Data for planners, too. With greater spatial granularity, it’s possible to identify movement patterns in greater detail than would otherwise be possible, giving you more precision in your analysis and deeper levels of insight to guide your decision making.

Because it's derived from mobile phone travel data, People Movement Data is highly accurate, making it useful for planners assessing granular movements.

Connect movements with the times at which they occur

Mobile phone location events capture where a device is moving or dwelling, but they also record the time at which these events happen. By knowing where and when devices (and their owners) move on a large scale, People Movement Data can give planners insight into where people are travelling through, where they’re congregating and how long they’re staying there for.

People Movement Data is able to link movement activity to an exact point in time, giving planners greater depth of analysis and potential for insights.

Furthermore, GPS location events can be used to analyse and compare movement over time with a high level of flexibility. They can be spliced in a variety of ways – running the gamut from specific times of day to days of the week, months, quarters and beyond – to narrow or expand your analysis to extract more meaningful insights.

Easily identify travel patterns

People Movement Data doesn’t identify individuals, but it can be used to discover more aggregate insights into where people are coming from to reach a location, where they’re travelling from after leaving a particular location, whether these journeys are single or multi-legged and where people stop on multi-legged journeys. This kind of trip data analysis can reveal travel behaviours that would have otherwise remained hidden, and present actionable insights.

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