MATLAB tools for improved characterization and quantification of volcanic incandescence in Webcam imagery: Applications at Kilauea Volcano, Hawai'i

Abstract

Webcams are now standard tools for volcano monitoring and are used at observatories in Alaska, the Cascades, Kamchatka, Hawai‘i, Italy, and Japan, among other locations. Webcam images allow invaluable documentation of activity and provide a powerful comparative tool for interpreting other monitoring datastreams, such as seismicity and deformation. Automated image processing can improve the time efficiency and rigor of Webcam image interpretation, and potentially extract more information on eruptive activity. For instance, Lovick and others (2008) provided a suite of processing tools that performed such tasks as noise reduction, eliminating uninteresting images from an image collection, and detecting incandescence, with an application to dome activity at Mount St. Helens during 2007. In this paper, we present two very simple automated approaches for improved characterization and quantification of volcanic incandescence in Webcam images at Kīlauea Volcano, Hawai‘i. The techniques are implemented in MATLAB (version 2009b, ® The Mathworks, Inc.) to take advantage of the ease of matrix operations. Incandescence is a useful indictor of the location and extent of active lava flows and also a potentially powerful proxy for activity levels at open vents. We apply our techniques to a period covering both summit and east rift zone activity at Kīlauea during 2008–2009 and compare the results to complementary datasets (seismicity, tilt) to demonstrate their integrative potential. A great strength of this study is the demonstrated success of these tools in an operational setting at the Hawaiian Volcano Observatory (HVO) over the course of more than a year. Although applied only to Webcam images here, the techniques could be applied to any type of sequential images, such as time-lapse photography. We expect that these tools are applicable to many other volcano monitoring scenarios, and the two MATLAB scripts, as they are implemented at HVO, are included in the appendixes. These scripts would require minor to moderate modifications for use elsewhere, primarily to customize directory navigation. If the user has some familiarity with MATLAB, or programming in general, these modifications should be easy. Although we originally anticipated needing the Image Processing Toolbox, the scripts in the appendixes do not require it. Thus, only the base installation of MATLAB is needed. Because fairly basic MATLAB functions are used, we expect that the script can be run successfully by versions earlier than 2009b.