CASE STUDY
University of Florida Transportation Institute (UFTI) & Gravy Analytics: Analyzing Evacuation Behavior to Enhance Natural Disaster Emergency Response Planning and Management
COMPANY
INDUSTRY
Public Sector
The Problem: Increased Wildfire Risk to Wildland-Urban Interface (WUI) Communities
To reduce wildfire risks and strengthen the resilience of WUI 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.
The Problem-Solver: Observations Data-as-a-Service (DaaS)
UFTI used Gravy’s Observations DaaS product to analyze human mobility data seen in the evacuation zone and surrounding area of the Kincade Fire to gain insight into the movement of local residents before, during, and after the fire.
“To better understand human behavior during wildfire events, we wanted to implement a different data collection method than those used in past studies. We hypothesized that mobility data would provide us with new insights into human movement during a catastrophic event, which could help facilitate emergency planning and management.”
The Findings: Insights into Evacuation Behavior During the Kincade Fire
After modeling human mobility data, UFTI researchers categorized residents as either non-evacuees or evacuees of the wildfire. For those who were identified as evacuees, the researchers further classified them into additional categories. They then analyzed movements of these groups before, during, and after the Kincade Fire.
The resulting data and analysis helped UFTI researchers to better understand wildfire evacuation behaviors, support more effective emergency management, and ultimately help vulnerable communities prepare and mitigate risks.
Want to learn more?
Download the full case study to learn how UFTI used location analytics to gain insight into evacuation behaviors and to enhance disaster emergency response planning and management.