Date of Award

Summer 8-2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Engineering Management & Systems Engineering

Program/Concentration

Engineering Management and Systems Engineering

Committee Director

Pilar Pazos-Lago

Committee Member

Resit Unal

Committee Member

Kanchan K. Das

Abstract

Wildfires are becoming increasingly frequent and severe, creating growing risks for mid-sized communities with limited emergency response resources. The January 2025 Los Angeles wildfires—which burned more than 57,000 acres and destroyed over 18,000 structures—underscore the urgent need to strengthen wildfire response strategies through the integration of unmanned aerial systems (UAS) (Hardy, 2025).

This study develops a scalable framework for drone-assisted wildfire response in resource-constrained environments. Using the city of Waynesboro, Virginia, as a case study, the research examines how mid-sized jurisdictions can integrate unmanned aerial vehicles (UAVs) to improve preparedness, response, and recovery. A three-round, mixed-methods Delphi study engages emergency managers, UAV operators, fire officials, and policy leaders to evaluate how drones can be effectively incorporated into wildfire management operations.

The analysis focuses on five performance metrics—coordination, efficiency, public safety, situational awareness, and response time—while also considering regulatory, financial, and training factors influencing implementation. The study aims to provide evidence-based recommendations and a scalable framework for integrating UAV technologies into local emergency response systems and broader wildfire management operations (Daud et al., 2022).

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/37x8-7p07

ISBN

9798193217022

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