Geopath Standard Data Anytime Population
- Kevin Narine
Standard Data produces a dataset that captures where the population spends time hour by hour, year over year. This data, similar to profiling individual venues for Geopath Activity Patterns, Standard Data Anytime Population profiles the entire U.S. using a uniform grid of tenth-of-a-mile cells.
The map below shows overall population density (occupancy per cell) in Atlanta, midday (10:00 a.m.–3:00 p.m.) during the average weekday (Mon, Tue, Wed, Thu) the week of October 14, 2019.
Home and Work, Key Attributes of Device Activity
When building Geopath Activity Patterns to profile individual places or a more generic cell geography, a few key attributes for each device need to be understood.
Home Block Group – for each individual device, what neighborhood does the device live in (Census Block Group). On a monthly basis, this is determined by isolating the last six weeks of device activity to identify its primary location. This primary location favors “overnight” locations when multiple locations compete for primary. For the vast majority of devices, as research studies also find for people generally, a person spends most of their time at home.
Resident Status – at a specific place, does an individual device’s activity qualify as being a resident at the location? This is simply determined by the proximity to the Home Block Group.
Does the place touch the home blockgroup? If a device is in its home block group, it is always given a Resident Status as priority over any other status.
Worker Status – at a specific place, does an individual device’s activity qualify as being a worker at the location? This is done through a simple set of rules focused on the place itself.
Did the device visit this place at least three times this week spending at least three hours each time? In addition, did the device spend at least 16hours here overall this week? When both of the above questions are true, the device is given a Worker Status at the location.
Visitor Status – at a specific place, if an individual device’s activity does not qualify it as a resident or worker, then it is given the status of a visitor to the place.
Household Type – Using the Geopath Claritas POPFACTS Demographics and PRIZM Premier Segments associated with the home block group, the probability of being a specific PRIZM household type is assigned to the device.
Anytime Population for Movement Patterns
The map above is showing population activity overall. However, when this population activity is segmented by home location and household type, it becomes a key ingredient in the process to develop Trip Matrices (see: Geopath Movement Patterns). It is able to provide information for residents of a particular neighborhood, revealing things like:
What areas of the city do particular households frequent and what areas do they avoid?
How many people are commuting to work, in what areas, and at what time, on the weekend?
How many people are going out in the evening or at other times of the day?
Do people shop near their home or their work locations?
How often do they travel and how far?
Trip Making Behaviors
As the Anytime Population Product is produced on an ongoing basis, it is available for every hour since early 2018 with a complete coverage of the United States. When examining the impacts of Covid, it is straightforward to measure how many people are in a particular area on any particular roadway. However, that recent history of presence alone gives little strength to producing forecasts of what will movement volume be happening over the next few weeks, months, and years. Instead, if we can document what specific trip making behaviors have changed from a documented pre-Covid norm, we can forecast those behaviors and using their impact on traffic levels drive a forecast of traffic on all roadways moving forward.
The next sections will identify a number of trip making behaviors that can be easily pulled from the existing Anytime Population dataset, originally built to only examine population activity in a location and how those behaviors have been trending over the past two years and how they are different for different groups of people.
Visits and Total Trips
As described in the Geopath Activity Patterns documentation, a “Visit” to a place is marked by its arrival time and a length of time spent at the location. For Activity Patterns, the threshold to document a Visit to a location is defined by place type. At a bar or restaurant, a device has to spend 15min to be classified as a visit to the location. At a convenience store or quick-serve restaurant, the threshold is lowered to requiring only a 5min dwell. When examining overall population behaviors and trip making with Anytime Population, the threshold was left at 15min in any given grid cell (0.1 mi in diameter).
The classification of a visit to a grid cell, implies the end of a trip that was just made to get to the place. By counting number of visits that a device generates on a daily basis, you are counting the number of trips. Conveniently, this number on average validates very closely with the Geopath National Household Travel Survey (NHTS) in cities of different sizes.
Staying Home
While a large percentage of the population takes multiple trips every day, a significant percentage take no trips. This population is identified as conducting no visits (and therefore no trips) on a particular day AND were in constant proximity to their home location. For each individual day, a device that never leaves its home blockgroup, confining all activity to a single cell (~0.1 mi diameter) or a cell and it’s immediately adjacent cells is characterized as having no travel on that particular day. The resulting weighted population is given a status of Stayed Home.
Home Based Local
Similar to the population that purely Stayed Home and had no activity outside of their home location, there is a population that while based at home, had activity outside the immediate vicinity. However any activity away from home did not have a long enough dwell in a single place to create a documented visit, as described in Visits and Total Trips above. This activity is heavily observed around parks and neighborhood streets indicating populations that are out walking the dog, cycling, or conducting other local activities. This activity may also be the result of very short visits (< 15min) to convenience or drug stores, quick serve restaurants, or pick ups from restaurants or retail that don’t meet the threshold of a visit.
Home Based Errands
Daily derived population that had time at their home location and visits to other places, but did not visit a work location on the particular day. This may include populations that are working from home as a person working from home would not create an independent work location.
Commuters
Daily derived population that had time at their home location and visited a work location on the particular day.
Long Travel
Daily derived population that had no time at home but did visit a work location on a particular day. This is not an intuitive pattern, but because home locations are defined monthly and work places are classified over a given week, if a person is spending significant time away from home in a single place, like a hotel, that hotel will be classified as their work location for the week.
Short Travel
Daily derived population that had no time at home or at a work location on a particular day. This group of people, away from home, but not long enough in a single place to generate a secondary work location, as described in Long Travel above.