Can we detect, monitor, and characterize volcanic activity using 'off the shelf' webcams and low-light cameras?

The ability to detect and monitor precursory events, thermal signatures, and ongoing volcanic activity in near-realtime is an invaluable tool. Volcanic hazards often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash to aircraft cruise altitudes. Using ground based remote sensing to detect and monitor this activity is essential, but the required equipment is often expensive and difficult to maintain, which increases the risk to public safety and the likelihood of financial impact. Our investigation explores the use of 'off the shelf' cameras, ranging from computer webcams to low-light security cameras, to monitor volcanic incandescent activity in near-realtime. These cameras are ideal as they operate in the visible and near-infrared (NIR) portions of the electromagnetic spectrum, are relatively cheap to purchase, consume little power, are easily replaced, and can provide telemetered, near-realtime data. We focus on the early detection of volcanic activity, using automated scripts that capture streaming online webcam imagery and evaluate each image according to pixel brightness, in order to automatically detect and identify increases in potentially hazardous activity. The cameras used here range in price from 0 to 1,000 and the script is written in Python, an open source programming language, to reduce the overall cost to potential users and increase the accessibility of these tools, particularly in developing nations. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures to be correlated to pixel brightness. Data collected from several volcanoes; (1) Stromboli, Italy (2) Shiveluch, Russia (3) Fuego, Guatemala (4) Popcatépetl, México, along with campaign data from Stromboli (June, 2013), and laboratory tests are presented here.