Why Every Academic Researcher Should Have Geolocation Data on Their Map

Location data is more than just dots on a map, it’s a window into how people live, move, and interact with the world around them. Whether you’re studying economic behavior, urban systems, or consumer decisions, geolocation data offers a powerful lens to explore real-world dynamics that traditional datasets often overlook.

Researchers often get overwhelmed by the many different datasets that relate to location. We took a stab at breaking these down into four key categories so it is easier to identify the exact type of data you need. 

• Point of Interest: Information about specific locations like stores, schools, businesses, or landmarks.
• Polygons and Boundaries: Aggregated views of neighborhoods, districts, or regions useful for identifying trends across geographies.
• Environmental Data: Details about the built and natural environment of a region with no hard set boundaries, like weather data.
• Behavioral Data: Anonymized insights into how people move between places, revealing patterns in commuting, shopping, or social activity.
  
  

Each type is valuable on its own. Combined, they create a multidimensional picture of how location and movement shape everything from markets to public health.

While GIS specialists have long leveraged this type of data, researchers in business, economics, marketing, and policy are only now beginning to explore its potential. This post highlights how different academic disciplines are putting geolocation data to work—and how you can, too.

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The Types of Geolocation Data

Information about a physical space comes in many different forms. Studies often cite data about an exact address, a broader city or regional space, or mobility data that focuses on the traffic between these locations. The sources of these datasets also vary, with some relying on personal devices and others on machine learning analyzing satellite imagery. 

Although these datasets may appear interchangeable at first, they unveil distinct facets about locations and how individuals engage with their surroundings. For academic researchers, discerning when to utilize each type of data, or combining them effectively, is essential for addressing complex research inquiries.

For the purposes of establishing a common language and showing how these datasets work together, we have categorized geolocation data into four main layers:

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1. Point of Interest: Refers to a particular place on a map that can be studied, such as a street address. You can, for example, study the transaction history of a specific property or when businesses open and close. This data is typically collected from databases, publicly available records, and is sometimes human-validated. ‍
2. Polygons and Boundaries: Think of information on broader areas like neighborhoods, shopping centers, or plots of land. Data on school zoning, building zones and codes, and other town layout information is heavily utilized by urban planning researchers. It aids in understanding the spatial distribution of activities, resources, and populations. Satellite imaging analyzed with machine learning helps inform these boundaries and track things like the development that has happened on a specific lot.‍
3. Environmental Data: As one can guess, environmental data looks at the weather and other macro trends for a region. Environmental Scientists may, for example, be especially interested in pollen count or pollution trends that traverse city and property lines. This data is sourced from Doppler radars, satellites, and in the case of climate risk analysis, probabilistic models trained with historic hazard data. ‍
4. Behavioral Data: This most commonly looks like mobility or movement data between locations, offering insights into how individuals navigate, be it their work commute or foot traffic patterns to a local store. An individual’s consumption habits can also offer direct economic insight about a geographical region to see not just where they are going, but where they are spending. This data enables researchers to track human flow, revealing a spectrum of insights, from commuting behaviors to disease spread. Mobile devices offer a treasure trove of insight at the individual level and when aggregated.

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How Different Academic Fields are Using Geolocation Data

Whether you're analyzing the design of cities, the impact of economic policies, or shifts in consumer behavior, location-based data can offer insights that traditional methods often miss.

Across academia, scholars in disciplines from urban planning to marketing are integrating geolocation datasets to better capture real-world activity. Here’s how it’s being used—and how it could apply to your research.

Geographic Information Science (GIS) and Spatial Analysis

GIS researchers are natural adopters of geolocation data. They use it to model movement patterns, understand spatial accessibility, and develop predictive tools for everything from disaster response to infrastructure planning.

• Behavioral Movement Modeling: Studies like Mobile phone location data for disasters: A review from natural hazards and epidemics explore how mobility data can improve emergency response and evacuation strategies.
  
  
• Infrastructure Optimization: Research on Urban sensing using existing fiber-optic networks demonstrates how passive data sources can reveal movement patterns in cities.
  
  
• Transportation Innovation: Scholars are exploring route optimization for electric vehicles, like in Optimizing Energy and Time for Electric Vehicle Charging Routes.

Urban Planning and Public Policy

Planners and policy researchers use mobility data to assess the equity and effectiveness of public services—especially in fast-growing or underserved areas.

• Access to Services: Geolocation data reveals gaps in access to hospitals, schools, and transit, helping cities prioritize infrastructure investment. This research looks specifically at water availability: Living with and without water: modeling human-infrastructure interactions in disaster preparedness
  
  
• Zoning and Land Use: Foot traffic analysis has been used to evaluate mixed-use development and land use efficiency: Exploring the impact of park features and visitors’ socioeconomic status on park visitation: A case study of Austin, Texas
  
  
• Pandemic-Era Mobility: During COVID-19, many studies used mobility data to track how urban activity responded to lockdowns and reopening: Modeling the impacts of governmental and human responses on Covid-19 spread using statistical machine learning

Business and Economics

In economics and business research, location data is gaining traction for its ability to capture real-world behavior at scale. Whether you’re studying local economic resilience or firm activity, mobility data offers a powerful complement to traditional economic indicators.

• Industry Changes: Macro trends can come from sources other than strictly financial data and models. See this paper on The Decline of Branch Banking published in S&P Global Market Intelligence in early 2025.
  
  
• Economic Vulnerability: Geolocation data confirms the impact disasters have on local and global economies. In this case, businesses further inland took longer to bounce back after disaster than those near the coast: Assessing Catchment Vulnerability of Community-Based Small Businesses to Coastal Hazards: Spatial and Sectoral Disparities

Marketing 

In marketing, geolocation data brings behavioral depth to research on brand engagement, retail strategy, and promotional effectiveness. 

• Retailer Trends and Insights: See what is working across brick and mortar businesses at scale with research like this from University of Wisconsin and Michigan State: Revitalizing the In-Store Experience: An Empirical Study on the Spillover Efffects of Experiential Services
  
  
• Brand Affinity and Competitive Analysis: Follow the evolution of a brand’s network to develop data-driven marketing strategies without relying on surveys or social media databases. Mapping large-scale brand networks: A consumers’ foot traffic based approach uses visits to brand points of interest to see what other brands consumers are connected to.
  
  

Ecology

One more, potentially less expected field of study, is in the field of Ecology where researchers study the relationships between living organisms. Movement patterns become especially fascinating when layered with other species.

• Species interaction: Human foot traffic was combined with GPS tracking data of white-tailed deer in this recent paper on how urbanization affects wildlife: Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments

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Geolocation Data on Dewey

Data that unlocks details about a physical location or the behavior around it is at the core of the Dewey Data platform. Nearly half of the datasets currently available could be used in one way or another by a GIS, Geography, or Urban Planning Department. 

Some of the most prominent location and mobility providers:  

Unlock Geolocation Data for Your Research

Through a single Dewey Data license, all of the above datasets and more are unlocked for use in academic research. 

Looking to bring geolocation data into your research for the first time? Try connecting with your University’s GIS librarian or even consider partnering with an experienced geo-spatial co-author. There are hundreds listed in our database of published papers! 

We are always happy to jump on a call for a brainstorming session as well. Contact Dewey.

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