Award Date

August 2025

Degree Type

Thesis

Degree Name

Master of Science in Engineering (MSE)

Department

Electrical and Computer Engineering

First Committee Member

Venkatesan Muthukumar

Second Committee Member

Emma Regentova

Third Committee Member

Pushkin Kachroo

Fourth Committee Member

Haroon Stephen

Number of Pages

84

Abstract

This thesis presents the design and development of a modular unmanned aerial vehicle (UAV) system based on a quadcopter platform for flexible and efficient wildfire-related multimodal image acquisition. Addressing key limitations in ecological UAV monitoring such as sensor inflexibility, time-consuming reconfiguration, and imprecise image georeferencing, the system introduces a versatile payload integration framework supporting three distinct imaging sensors: MicaSense Altum-PT, FLIR Vue Pro R, and Sony Alpha 6000.All onboard components, including the flight controller, autopilot software, GNSS module, motors and ESCs, were selected to optimize stability and payload performance. A gimbal-free, downward-facing mount simplifies field deployment, while custom integration enables precise geotagging. Field tests were conducted over grassland environment using mission-based corridor scans. The resulting imagery was processed in PIX4Dmapper to generate dense point clouds, orthomosaics, digital surface models (DSMs), and vegetation indices. A comprehensive evaluation of flight performance and data quality was performed to validate the system’s effectiveness. The proposed platform enhances UAV-based ecological monitoring in pre- and post-wildfire scenarios by supporting rapid sensor swapping and robust data collection. It facilitates high-resolution analysis of vegetation, soil, and burn impact, contributing to improved wildfire assessment and post-fire ecosystem recovery monitoring. This research contributes to the National Science Foundation (NSF) EPSCoR project “Harnessing the Data Revolution for Fire Science (HDRFS)” through the Cyberinfrastructure Innovations (CII) component.

Keywords

Aerial Imaging; Multi-Spectral Imaging; Quadcopter; Thermal Imaging; Unmanned Aerial Vehicle (UAV); Wildfire

Disciplines

Electrical and Computer Engineering

File Format

pdf

Degree Grantor

University of Nevada, Las Vegas

Language

English

Rights

IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

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