ASTER/AVHRR Data Hybridization to determine Pyroclastic Flow cooling curves

Thursday, 18 December 2014
Kevin A Reath, University of Pittsburgh Pittsburgh Campus, Department of Geology and Planetary Science, Pittsburgh, PA, United States, Robert Wright, Univ. Hawaii/HIGP, Honolulu, HI, United States and Michael S Ramsey, University of Pittsburgh, Pittsburgh, PA, United States
Shiveluch Volcano (Kamchatka, Russia) has been in a consistent state of eruption for the past 15 years. During this period different eruption styles have been documented including: sub-plinian events, dome growth and collapse, and subsequent debris flow deposits. For example, on June 25-26, 2009 a pyroclastic debris flow was emplaced and the eruption onset that produced it was recorded by a series of seismic events spanning several hours. However, due to cloud cover, visual confirmation of the exact emplacement time was obscured. Orbital remote sensing was able to image the deposit repeatedly over the subsequent months. ASTER is a high spatial resolution (90m), low temporal resolution (2 – 4 days at the poles, 16 days at the equator) thermal infrared (TIR) sensor on the NASA Terra satellite. AVHRR is a high temporal resolution (minutes to several hours), low spatial resolution (1km) spaceborne TIR sensor on a series of NOAA satellites. Combined, these sensors provide a unique opportunity to fuse high-spatial and high-temporal resolution data to better observe changes on the surface of the deposit over time. For example, ASTER data were used to determine the flow area and to provide several data points for average temperature while AVHRR data were used to increase the amount of data points. Through this method an accurate average cooling rate over a three month period was determined. This cooling curve was then examined to derive several features about the deposit that were previously unknown. The time of emplacement and period of time needed for negligible thermal output were first determined by extrapolating the cooling curve in time. The total amount of heat output and total flow volume of the deposit were also calculated. This volume was then compared to the volume of the dome to calculate the percentage of collapse. This method can be repeated for other flow deposits to determine if there is a consistent correlation between the dome growth rate, the average collapse size, and the size of the deposit. Therefore, by combining the data from these two sensors the creation of an accurate cooling curve for thermally-elevated volcanic flow deposits was made possible. In doing, additional features related to the eruption mechanism were also determined.