Long Range UAS Operations for Volcanic Monitoring

  • Ben J Schellenberg

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)


This thesis considers the effective long range operation of fixed-wing Unmanned Aerial Systems (UAS) for volcanic monitoring, focusing on the automation of plume sensing, route planning, and plume re-interception. Ash sampling from within volcanic plumes provides vital data for ash dispersion models, which are used to manage aviation hazards and monitor risks to populations. Volcan de Fuego is a highly active stratovolcano in Guatemala with a summit altitude of 3800 m Above Mean Sea Level (AMSL), just 40 km from an International Airport. This thesis describes a robust method of operating UAS in hazardous environments, presenting Beyond Visual Line of Sight (BVLOS) fixed-wing flights for the collection of airborne ash. Reaching ranges in excess of 10 km, and altitudes of 5000 m AMSL, the automation of these UAS missions remains highly desirable in order to maximise efficiency and reduce operator workload. Key components of the presented missions include the identification and sensing of volcanic plumes, efficient flight path planning, and coordinating plume re-interception for the collection of comparative ash samples. A metric is presented for detecting plumes autonomously onboard using lightweight and low power sensors. The development and implementation of an onboard Real-Time Trajectory Planner (RTTP) is also discussed, in the context of calculating efficient climb paths to the volcano’s summit region. The real-time element of this system means the route calculated mid-flight, and running the system onboard the aircraft effectively increases the UAV's level of autonomy. Finally, a Coordinated Plume Interception (CPI) scheme is presented for efficient repeat sampling of a volcanic plume. A series of routing options are developed and discussed, considering their dependence on wind conditions and the impact of practical flight zone limits. The themes of autonomy, efficiency, and volcanic monitoring run throughout this thesis, developing technical and practical solutions to real-world problems.
Date of Award29 Sept 2020
Original languageEnglish
Awarding Institution
  • University of Bristol
SupervisorTom S Richardson (Supervisor), Arthur G Richards (Supervisor) & I M Watson (Supervisor)

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