Research & Academia
Use-cases and Applications
Mobile location data gives researchers a way to observe real world movement patterns at scale. By analyzing mobility, visitation, origin and destination patterns, and interactions with places, researchers can investigate how people move through cities and communities and how infrastructure and public services are used.
From transportation and urban planning to migration, tourism, disaster resilience, and socioeconomic research, location data can be combined with other datasets to develop more comprehensive models and answer complex research questions.
Study Human Mobility
Analyze movement patterns to understand how people travel, where they go, and how mobility varies across populations and geographies.
Analyze Transport Accessibility
Study origin and destination patterns, transit usage, and mobility flows to evaluate transportation networks and identify underserved areas.
Research Urban Spaces
Understand how people use public spaces, neighborhoods, and urban environments to support research in urban planning, architecture, and city design.
Study Socioeconomic Patterns
Combine mobility data with demographic, census, and other datasets to investigate socioeconomic disparities, accessibility, and quality of life.
Analyze Tourism & Visitation
Study visitor movements, destination flows, and interactions with places to understand tourism patterns and their impact on communities.
Support Disaster Research
Analyze population movement and displacement to understand mobility during and after disasters and inform resilience and emergency planning.
Research Projects Supported By Quadrant Data
Purdue University
This study by researchers at the World Bank and Purdue University uses Quadrant location data to map public transit demand, identify busy routes and underserved areas, and understand how mobility changes during disruptions to support more accessible, resilient transport planning and investment.
University of Auckland
This research offers an understanding of retail catchment areas by analyzing an extensive dataset with over 117 million data points from approximately 1.6 million users in Auckland. Utilizing the DBSCAN clustering algorithm and the concave hull method, we analyze and visualize the geographic extent of catchment areas.
Asian Development Bank
How can cities understand where people travel, how traffic moves, and where transport related emissions come from? Quadrant’s anonymized mobile location data helps answer these questions, enabling cities to identify travel patterns, build origin destination matrices, and assess the potential impact of low emission zones and vehicle restrictions.
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Frequently Asked Questions
How can mobile location data be used in academic research?
Mobile location data can support research into human mobility, transportation, urban planning, tourism, migration, socioeconomic conditions, and other areas where understanding movement and visitation patterns is important.
What types of research can be conducted using location data?
Researchers can study transportation accessibility, urban mobility, public space usage, infrastructure demand, population movement, tourism, disaster resilience, and socioeconomic issues.
Can location data be combined with other research datasets?
Yes. Mobile location data can be combined with census, demographic, environmental, POI, and other geospatial datasets to provide additional context and support more comprehensive analysis.