Geopath Streetlytics Source Data
- Kevin Narine
Person Movement Data
Monthly Travel Pattern Data: Citilabs acquires a nationwide travel pattern dataset by U.S. Census Block Group from AirSage. This dataset is used to understand the degree of activity in each census block group. This monthly dataset consists of people movement between census block groups within the Streetlytics analysis area. For individuals included in the AirSage dataset, the home locations and workplace locations were identified. These geographies are used to aggregate travel patterns between block groups into nine categories: home to home (HH), home to work (HW), home to other (HO), work to home (WH), work to work (WW), work to other (WO), other to home (OH), other to work (OW), and other to other (OO). The trips are further stratified to identify the home location block group for these trips. Data is provided as an anonymized total trip rate at an hourly level for an average day of the week during the month.
Annual Travel Pattern Data: Citilabs uses LEHD Origin-Destination Employment Statistics (LODES) as a quality control and validation dataset to adjust the census block group employment demographics and HH/WH monthly travel pattern to remove demographic inconsistencies.
Government Survey Data: The National Household Travel Survey (NHTS) provides the most comprehensive travel data from each household in the United States roughly every 5-10 years. The two most recent surveys were completed in 2017 and 2009 by the Federal Highway Administration (FHWA). The survey collects sample trips made by individuals in each household during a 24-hour period including, but not limited to, trip purpose, trip length, origin, destination, departure time, arrival time, and means of transportation. It also includes characteristics of the household, individuals, and their vehicles. The collected survey data were analyzed and expanded so that it can be used as a benchmark for quantifying and analyzing travel behavior nationwide. All Metropolitan Planning Organizations (MPOs) in the U.S. develop their regional travel demand models based on household travel surveys including the NHTS.
Roadway Traffic Count Data: Traffic counts are collected from a variety of published and unpublished sources which include:
Highway Performance Monitoring System (HPMS)
Traffic Monitoring Analysis System (TMAS)
State Department of Transportations (DOTs)
County Departments
City Departments
Metropolitan Planning Organizations (MPOs)
Transportation Improvement Programs (TIPs)
Council of Governments (COGs)
Public Work Departments
Regional/Local Transportation studies
The counts from different sources are processed into a standard format to be included into our proprietary cloud-based count tagging software called PICO. All the counts are carefully evaluated for accuracy, consistency, and tagged to the appropriate links in the street network. The counts are then converted to the most current year by applying various conversion factors (annual, weekly, monthly, seasonal, and daily). These factors are estimated using historical traffic data for each region. The count network is further analyzed to pass the flow consistency and volume-to-capacity ratio tests to filter any inconsistent counts to ensure accuracy before it is included into Streetlytics model runs.
Pedestrian Count Source Data: Approximately 10,800 pedestrian source counts, covering nearly all major metropolitan areas, were obtained from more than 150 government and private sources. These counts were collected through a combination of web searches and strategic local contacts. The raw pedestrian count data were obtained for different times of day including daily or specific hours. When a daily count was not available, hourly and peak period counts were adjusted based on information from the analysis of cellular and GPS data. Pedestrian counts were obtained in the following major urban areas:
New York City
Chicago
Miami
Los Angeles
Washington D.C.
San Francisco
Seattle
Atlanta
Las Vegas
Boston
Minneapolis
Philadelphia
San Diego
Tampa
Cleveland
Denver
Portland
Dallas
Houston
Phoenix
Orlando
New Orleans
Ann Arbor
Buffalo
Louisville
Kansas City
Nashville
Knoxville
Airport Data: The FAA provides monthly boarding and alighting activity at airports nationwide. Incorporating passenger activity targets at major airports enhances the Streetlytics modeling process in those areas.
National Parks Data: The National Park Service (NPS) manages 379 national parks nationwide and provides the total number of visitors on a monthly basis. The current Streetlytics process uses the 2017 NPS visitor data.
Demographic Data
Demographic & Business Data: Citilabs acquires demographic data from ESRI for each US Census Block Group. This data includes detailed information about population, household size, vehicle availability, age, sex, race, and ethnicity. The ESRI Tapestry dataset which stratifies demographic characteristics for each block group is also incorporated into the Streetlytics modeling process. The current Streetlytics process uses the ESRI 2017 demographic dataset. Citilabs also acquires demographic and business employment data from ESRI for each US Census Block Group.
School Data: School enrollment data is obtained from various published and unpublished sources:
National Center for Education Statistics (NCES)
School/college websites
County Department
State Department of Education
School/College Contacts
Data from the different sources are analyzed for any inconsistencies and all non-school related data (daycares, churches, nurseries, preschools etc.) is filtered. The data is further converted into a standard format required for Streetlytics process.
Point of Interest Data: Citilabs acquired point of interest data from both ESRI and HERE. These two datasets provide the specific location of each business in the U.S. by business type such as hotel, restaurant, gas station, office building, stadium, etc. For many of these business locations, we acquired square footage and annual revenue.
Transportation Infrastructure Data
Roadway and Pedestrian Transportation Network: Citilabs’ partner, HERE, provides a comprehensive, highly accurate pedestrian facility and roadway database. This database contains detailed information about each road and pedestrian trail segment in the U.S. This dataset provides the foundation for the traffic and pedestrian data products. The HERE network database contains information, such as transportation facility spatial information, connectivity, operational characteristics, turning restrictions, travel lanes, facility type, and observed speeds, that are used to construct the Streetlytics transportation model networks. The current Streetlytics process uses the HERE 2019 R1 database.
Toll Costs: Citilabs collects information from public and private toll operators to identify and incorporate passenger vehicle toll costs. Toll costs for an average passenger vehicle are estimated for both fixed-cost and variable-cost toll facilities.
Reversible Lanes: Citilabs collects information from public and private roadway operators to identify high-capacity roadway facilities where some or all lanes are open to traffic for only a portion of each day.