How the University of Florida TI Used Location Analytics to Enhance Natural Disaster Emergency Response
Planning and Management

January 6, 2021

Beyond providing actionable insights to businesses, location intelligence can help to solve some of society’s biggest challenges. By analyzing location data, regional and local leaders can help vulnerable communities reduce risk and enhance safety during natural disasters and emergencies. With the insight derived from location data, local emergency managers can better prioritize outreach, deploy life-saving services, and direct the efforts of first responders based on how residents in a certain community react during times of crisis. 

Read on to learn how the University of Florida Transportation Institute (UFTI) used location analytics to examine wildfire evacuation data in hopes of helping vulnerable communities reduce risk and enhance safety during natural disasters.

A firefighter responds to a call over their radio.

The Problem

Researchers from UFTI recognized that wildfires have become a growing threat to communities across the globe. To reduce wildfire risks and strengthen the resilience of vulnerable communities, researchers from UFTI sought to enhance the understanding of wildfire evacuation behaviors by studying the movements of local residents during the 2019 Kincade Fire in Sonoma County, CA. Researchers hoped the study’s findings could help emergency managers develop appropriate response measures and make effective decisions during a wildfire event while enhancing emergency planning strategies to prepare high-risk households for wildfires in the future.

Although there had been previous research studies on wildfire evacuation behaviors, these studies typically relied on data collection methods, such as surveys, interviews, and focus groups, which led to various limitations like small sample sizes, narrow timeframes to analyze, and self-report bias. To gain new insights into human behavior during wildfires, UFTI researchers needed to implement a different data collection method than those used in past studies.

The Solution

UFTI researchers worked with Gravy Analytics to secure trusted human mobility data for their study. Gravy provided UFTI researchers with its Observations Data-as-a-Service (DaaS) product for mobile devices seen in the evacuation zone and surrounding area of the wildfire. Researchers selected Gravy’s data for its quality, precision, and additional Forensic Flags which enabled them to filter and use only the data they needed for this particular analysis. 

With Gravy Observations data, UFTI researchers were able to isolate the human mobility data in which they were most interested and then determine and apply their own modeling parameters. This data fueled their analysis to gain insight into the movement of local residents before, during, and after the fire.

The Results

The resulting data and analysis helped UFTI researchers to:

  • Better understand wildfire evacuation behaviors

By examining the movements of local residents before, during, and after the 2019 Kincade Fire, researchers gained a deeper understanding of how people behave during wildfire evacuations.

  • Support more effective emergency management

Emergency managers can use the results and insights of UFTI’s study to develop and improve their response measures during wildfires as well as other natural hazards (e.g., executing traffic management strategies, issuing evacuation orders, providing support for travelers in need, undertaking rescues, etc.). The study can also help enable decision-makers to customize emergency management processes based on time of year, day of week, or even time of day based on understanding the regular behaviors of local populations at those times. 

  • Help vulnerable communities prepare and mitigate risks

The findings of the study can be used by emergency managers and planners in the development of targeted public outreach campaigns, training protocols, and emergency communication strategies to prepare high-risk households for future wildfires. With enhanced strategies, at-risk communities may be able to reduce the impact of a natural hazard.

Improved Disaster Response Research with Location Intelligence

With location intelligence, leaders of local municipalities can gain deeper insight into human behavior during various disasters and emergencies. This can help emergency managers develop and enhance disaster preparedness and emergency response strategies to meet the needs of specific communities.

For more information on how UFTI researchers used location analytics in their study of wildfire evacuation behaviors, read our full case study. To learn even more, click here to discover how organizations are using Gravy’s location data for social good or contact one of our experts today.

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