Traditional data sources for city and regional analysis, including urban planning, real estate, and retail, have historically focused on static representations of urban life. This includes data such as:
Census data: Population and demographic information for residents in a specific area.
Vehicle registration: The number of registered vehicles within a town.
Transit surveys: Commuting methods and trip durations.
Credit card transactions: Inferred visitation patterns based on spending location.
While these conventional data points are valuable for understanding the demographics and lifestyle patterns of a resident population, they fall short of capturing the dynamic movement of people. They cannot accurately depict the real flow of individuals to a destination, their demographics, origins, or intermediate stops. Movement data, however, provides a deeper understanding of visitor intent, actual destinations, and travel behaviors.
Movement Data for Urban Analysis
While a variety of movement data types exist, this report highlights two particularly impactful examples for the analysis of urban life: Floating Population Data and Traffic Flow Data.
Floating Population Data
This data type refers to the transient population within a specific area at any given time. It encompasses visitors, tourists, shoppers, and all non-resident individuals. To isolate this transient group, some data providers intentionally filter out individuals who remain in a location for an extended period, as they are likely residents or regular commuters.
Sources for this data include:
Mobile network signals from cell towers and Wi-Fi access points.
Anonymized GPS location data from mobile applications.
Advanced technologies often combine these different signal sources to generate highly accurate location estimates.
Floating population data enables a wide range of analytics, including:
Customized area analysis: The number of people within user-defined boundaries and their movement patterns.
Public transit metrics: The volume of passengers embarking and disembarking at subway or bus stations, and the flow of pedestrians through specific station exits.
Demographic profiling: Characteristics and demographics of the population in major commercial districts or tourist attractions.
Origin-Destination analysis: Understanding where people came from before visiting a location and their subsequent destinations.
Recent advancements even provide indoor insights for spaces like shopping malls and exhibition centers. This data can track the number of visitors to specific shops on different floors, regardless of whether a credit card transaction occurred, and can even reveal which stores visitors patronize sequentially.
Traffic Flow Data
This data focuses on the movement of vehicles on road networks. It measures vehicle counts, average speeds, congestion levels, and travel patterns. Many global and local navigation services provide real-time traffic information. Notably, some of them also maintain historical records of this data, which can then be used for analytical purposes.
Data collection methods include:
Road sensors and traffic cameras.
GPS devices in cars and on mobile applications.
While local authorities often use sensor and camera data for monitoring and maintenance, most comprehensive movement data products are offered by mobile navigation providers with broad regional or national coverage.
Traffic flow data allows for detailed analytics, such as:
Road performance: Average vehicle speed and volume on selected roads at specific times and dates, segmented by direction.
Intersection analysis: The duration of time vehicles spend passing through a specific intersection.
Origin-destination analysis: Speed and number of vehicles on different routes between a given origin and destination, including the percentage by direction where vehicles travel to and from these points.
Ensuring Data Privacy
Given that this data is primarily collected via mobile devices, privacy concerns are paramount. Regulations in many countries mandate that data providers handle this sensitive information responsibly. By law, individual movement data must be de-identified during collection, processing, and delivery. This ensures that neither the data collectors nor the end-users can trace the information back to a specific person or driver.
Applications Across Key Industries
The insights derived from movement data offer a significant competitive advantage in multiple sectors.
Real Estate
Movement data provides invaluable insights for development, investment, and management.
Site Selection: Developers can identify prime locations for residential, commercial, or mixed-use properties by analyzing foot traffic and vehicle flow, ensuring high visibility and accessibility.
Property Valuation: Areas with consistent and favorable movement patterns often command higher property values. This data allows for more accurate valuations by correlating movement metrics with property prices.
Property Optimization: By understanding the demographics and origin-destination patterns of visitors, developers can tailor a property's design and services—whether for office, retail, or hospitality—to better suit its likely occupants.
Traffic Impact Analysis: Analyzing traffic around a new development allows developers to predict its impact on local road networks and understand travel patterns to and from key points of interest.
City Planning and Management
Effective city management relies on an accurate understanding of urban dynamics.
Urban Planning: Planners can design more efficient public spaces, transportation routes, and infrastructure by using floating population data to understand how people actually use the city.
Public Safety: Analyzing movement patterns helps in deploying emergency services more effectively and identifying areas prone to overcrowding or traffic incidents.
Resource Allocation: City managers can optimize public resources like transit and waste management based on real-time population density and distribution.
Event Analysis: Both historical and real-time data on traffic flow and floating population can be used to understand the impact of specific events. This allows planners to identify origins and destinations and create contingency plans for future similar events.
Retail
For retail businesses, movement data is a critical tool for strategic planning and operational efficiency.
Store Location Optimization: Retailers can select new store locations with high foot traffic and demographics that align with their target customer base, maximizing visibility and sales potential.
Targeted Marketing: Understanding pedestrian routes and traffic flow allows retailers to strategically place advertisements and plan promotions to reach a more relevant audience efficiently.
Inventory Management: Insights from movement data can help predict demand fluctuations, enabling retailers to optimize inventory levels and reduce waste.
Utilizing Movement Data for Analysis
Movement data can be analyzed in several ways to achieve actionable insights. One common approach is creating dashboards with charts and graphs tailored to specific analytical purposes. Alternatively, users can upload movement data to a Geographic Information System (GIS) tool, where it can be combined with other geospatial data for deeper insights. Many user-friendly tools are now available, requiring no specialized GIS or coding skills.
To derive the best insights, it is crucial to select the right data attributes. This includes specifying statistics for a particular time frame (e.g., weekdays vs. weekends), geographical coordinates, and demographic information (e.g., age, gender).
For inquiries or a consultation regarding bespoke geospatial data and solutions, please contact navigate@apieceofmap.com.
