Remote Sensing (Apr 2022)

PlumeTraP: A New MATLAB-Based Algorithm to Detect and Parametrize Volcanic Plumes from Visible-Wavelength Images

  • Riccardo Simionato,
  • Paul A. Jarvis,
  • Eduardo Rossi,
  • Costanza Bonadonna

DOI
https://doi.org/10.3390/rs14071766
Journal volume & issue
Vol. 14, no. 7
p. 1766

Abstract

Read online

Tephra plumes from explosive volcanic eruptions can be hazardous for the lives and livelihoods of people living in the proximity of volcanoes. Monitoring and forecasting tephra plumes play essential roles in the detection, characterization and hazard assessment of explosive volcanic events. However, advanced monitoring instruments, e.g., thermal cameras, can be expensive and are not always available in monitoring networks. Conversely, visible-wavelength cameras are significantly cheaper and much more widely available. This paper proposes an innovative approach to the detection and parametrization of tephra plumes, utilizing videos recorded in the visible wavelengths. Specifically, we have developed an algorithm with the objectives of: (i) identifying and isolating plume-containing pixels through image processing techniques; (ii) extracting the main geometrical parameters of the eruptive column, such as the height and width, as functions of time; and (iii) determining quantitative information related to the plume motion (e.g., the rise velocity and acceleration) using the physical quantities obtained through the first-order analysis. The resulting MATLAB-based software, named Plume Tracking and Parametrization (PlumeTraP), semi-automatically tracks the plume and is also capable of automatically calculating the associated geometric parameters. Through application of the algorithm to the case study of Vulcanian explosions from Sabancaya volcano (Peru), we verify that the eruptive column boundaries are well recognized, and that the calculated parameters are reliable. The developed software can be of significant use to the wider volcanological community, enabling research into the dynamics of explosive volcanic eruptions, as well as potentially improving the use of visible-wavelength cameras as part of the monitoring networks of active volcanoes. Furthermore, PlumeTraP could potentially find a broader application for the analysis of any other plume-shaped natural or anthropogenic phenomena in visible wavelengths.

Keywords