Kiris, Onur;
(2025)
Automated Detection of Pyroclastic Density Currents and High-Resolution Radar Imaging for Quantifying Flow Dynamics.
Doctoral thesis (Ph.D), UCL (University College London).
![[thumbnail of Kiris_10211770_thesis.pdf]](https://discovery.ucl.ac.uk/style/images/fileicons/text.png) |
Text
Kiris_10211770_thesis.pdf Access restricted to UCL open access staff until 1 August 2026. Download (68MB) |
Abstract
Pyroclastic Density Currents (PDCs) pose one of the most severe hazards in volcanic environments, necessitating robust, high-resolution monitoring techniques to improve hazard assessment and early warning capabilities. This study presents a novel Frequency Modulated Continuous Wave (FMCW) radar-based monitoring system designed for continuous, automated observation of PDC dynamics at Volc´an Santiaguito, Guatemala. The integrated monitoring platform has been operational since February 2023, with two subsequent field campaigns in May 2023 and May 2024 focused on system refinement, multi-site expansion, and extended data collection. The radar operates in the 11.5 GHz to 12.5 GHz band, transmitting 1 GHz bandwidth triangular chirps with a 20 ms sweep duration, enabling centimetre-scale range resolution. During the primary deployment period (10 February–26 March 2023), the system recorded 705 detector-triggered events, from which over 200 valid radar captures were retrieved. Of these, 155 sequences exhibited visually detectable flow signatures, and 135 individual flow fronts were identified for detailed analysis. Linear velocity approximation on 132 clearly resolved fronts yielded a mean ground-relative flow velocity of 12.25m/s, with observed values ranging from 5ms−1 to 30m/s, consistent with established field-scale PDC behaviour. The effective radar dataset exceeds 1,200 minutes of continuous capture, constituting the most extensive in-situ radar observation archive of pyroclastic flows reported to date. This study demonstrates the viability of integrating seismic-triggered radar monitoring for reliable, energy-efficient observation of fast-moving volcanic flows. It also outlines system limitations related to Doppler aliasing, angular coverage, and environmental durability, providing a roadmap for future development. The presented architecture enables real-time data collection, supports high-resolution motion characterisation, and offers a scalable solution for autonomous hazard monitoring in complex volcanic terrain.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Automated Detection of Pyroclastic Density Currents and High-Resolution Radar Imaging for Quantifying Flow Dynamics |
| Language: | English |
| Additional information: | Copyright © The Author 2025. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Engineering Science Faculty Office |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10211770 |
Archive Staff Only
 |
View Item |
