Image Visualization and Infrared Spectroscopy Lab
Prof. Michael S. Ramsey (Director)
University of Pittsburgh
Volcanic ash is a hazard to both life and property. The health impacts of ash particle size and chemistry have been previously quantified. In addition, drifting volcanic ash is a major problem for the airline industry causing cockpit window abrasion and possibly even total engine shut down. For example, drifting ash during the 2010 eruption of Eyjafjallajökull volcano in Iceland resulted in a near-shutdown of commercial aviation in Europe at a cost of ~ $1.7 billion. Furthermore, the mixture of ash and volcanic gases such as CO2, SO2 and H2O can affect the Earth’s radiation budget. This interaction is complex, however, because of the unknown range of composition, size, shape and total volume of the material erupted. However, understanding the properties of a volcanic ash plume is a complex problem made more impractical given the danger posed to investigators needing to collect samples very close to erupting volcanoes. Therefore, developing a non-contact approach has always been a goal of remote sensing studies.
Satellite remote sensing has been commonly used to detect drifting ash clouds and track them through the Earth’s atmosphere. This is done by a suite of low-spatial, high-temporal resolution sensors to identify ash by its effect on the thermal infrared (TIR) transmission from the Earth’s surface through the cloud. These techniques are useful for tracking the drifting cloud and potentially mitigating the hazard. However, for more detailed physical and chemical data, higher spatial resolution data and different methods are required.
This ongoing project seeks to understand the particle size and petrologic variations in proximal, opaque volcanic ash plumes, by treating them as a hypothetical solid emitting surface. From this, the emission spectra of the ash-bearing pixels can be analyzed using a spectral end-member library of volcanic ash samples. This approach is being designed using TIR image data from the Advanced Spacebourne and Thermal Emission Radiometer (ASTER) sensor, simultaneously with newly-developed ground-based multispectral TIR camera data.
This research combines laboratory, field, and computational methods to gain better understanding into the properties of volcanic ash plumes. Ash samples have been obtained from several volcanoes worldwide, which cover a wide range of compositions (Figure 1). These samples have been sieved into different particle size fractions, as this parameter has a direct impact on the emission spectrum due to scattering and transmission effects. The ash samples have been separated into larger than 150 µm, 63 - 150 µm, 45 - 63 µm and less than 45 µm fractions. To obtain even finer fractions, a Micro-Orifice Uniform Deposit Impactor (MOUDI) at the Air Quality Laboratory at Carnegie Mellon University has been used on the less than 45 µm sample. This provided four finer fractions (18 - 45 µm, 10 - 18 µm, 1 - 10 µm and less than 1 µm).
Figure 1. ASTER Volcanic Ash Library (AVAL) emission spectra of volcanic ash samples. (A) Four ash samples are shown. These samples contained ash particles that were less than 150 µm. The petrological distinctiveness of each spectrum demonstrates the applicability of this approach to mapping opaque volcanic ash plumes. (B) Spectra of Sakurajima volcanic ash at four size fractions, demonstrating how decreasing particle size causes a change in the spectral contrast. Because this effect is linear with particle size, it is also possible to extract particle size in a volcanic plume using the linear spectral deconvolution approach.
The TIR emission spectra of each size fraction has been acquired at the IVIS Lab’s Nicolet Nexus 670 FTIR spectrometer at the University of Pittsburgh. These measurements are then degraded down to the five-point ASTER TIR spectral resolution to create the ASTER Volcanic Ash Library (AVAL). Work is currently on going to finish this spectral library, at which point it will be made available for download and use.
Figure 2. ASTER data acquired on 19 April 2010 of the plume produced by the Eyjafjallajökull eruption in Iceland. (A) False color VNIR image; (B) Pixel-integrated brightness temperature image, which shows variations from 0˚C (black) to 50˚C (white). (C) Spectral deconvolution result varying from 0% (black) to ~80% (white) for an andesitic end-member and assuming the opaque plume is a solid emitting surface.
ASTER image data of volcanic eruptions obtained from the Urgent Request Protocol (URP) archive are processed using the linear spectral deconvolution model and the AVAL end-member library. An initial proof of concept was performed on data collected of Eyjafjallajökull volcano (Figure 2). The distinct emission spectra of volcanic ash present within ash-bearing pixels has led to further ASTER image plume (e.g., Figure 3).
Figure 3. Images of the Chaitén eruption on 19 January 2009, using a high SiO2 glass end-member from AVAL. (A) False color ASTER visible/near infrared (VNIR) image of the eruption. (B) ASTER TIR image. (C) Result for the less than 45 μm particle size end-member (with the cloud highlighted by the yellow line). (D) Spectral deconvolution result for the 45 - 63 μm fraction. This result was positive for the region of the plume further north in the image. However, false-positive regions are also identified.
The work for this project will continue as described, with the ASTER URP database being continually screened for proximal ash plume image data, and analyzed using the spectral end-member technique. Furthermore, we are continually updating AVAL with new ash samples as they are collected or donated. The samples undergo x-ray diffraction (XRD) and x-ray fluorescence (XRF) analysis to determine both the chemistry of the ash as well as calculating the percentage of crystal to glass fragments present. This work has been funded by the NASA under the Science of Terra and Aqua Program (NNX14AQ96G) and an Earth and Space Sciences Graduate Fellowship Program (NNX15AQ72H), as well as the National Geographic Society’s Research and Exploration Program (9734-15).
Duda, K.A., Ramsey, M., Wessels, R. and Dehn, J., Optical satellite volcano monitoring: A multi-sensor rapid response system. In Geoscience and Remote Sensing; Ho, P.P., Ed.; IN-TECH Press: Vukovar, Croatia, 473-496, 2009.
Ramsey, M.S., Reath, K.A. and Williams, D.B., Threshold considerations for future volcanic hotspot and ash detection using HyspIRI, 2013 HyspIRI Science Workshop, Pasadena, CA, 2013.
Ramsey, M.S. and Harris, A.J.L., Volcanology 2020: How will thermal remote sensing of volcanic surface activity evolve over the next decade?, J. Volc. Geotherm. Res., 249, 217-233, 2014.
Ramsey, M.S., Synergistic use of satellite thermal detection and science: A decadal perspective using ASTER, Detecting, Modelling and Responding to Effusive Eruptions, in: Harris, A.J.L., De Groeve, T., Garel, F. & Carn, S.A. (eds.), Detecting, Modelling and Responding to Effusive Eruptions, Geol. Soc., London, Special Publications, 426, doi:10.1144/SP426.23, 2015.
Williams, D.B. and Ramsey, M.S., Mapping volcanic ash plumes using ground and satellite thermal imaging: A new approach to understanding explosive eruptions and reducing population risks, NGS Research and Exploration Program Award, Period: 2015-2017.
Williams, D.B. and Ramsey, M.S., Analysis of proximal volcanic emissions, NASA, Earth and Space Sciences Graduate Fellowship Program Award, Period: 2015-2018.
Williams, D.B. and Ramsey, M.S., AVAL - The ASTER Volcanic Ash Library, AGU Fall Meeting, San Francisco, CA, 2016.
Williams, D.B. and Ramsey, M.S., Ground-based analysis of volcanic ash plumes using a new multispectral thermal infrared camera approach, AGU Fall Mtg., 2015.
Williams, D.B. and Ramsey, M.S., Analyzing proximal volcanic ash emissions using high spatial resolution thermal infrared imagery, Tephra 2014 Meeting: Maximizing the potential of Tephra for multidisciplinary science, Portland, OR, 2014.
Williams, D.B., Ramsey, M.S. and Karimi, B., Identifying the volcanic source of disconnected ash clouds using the HYSPLIT dispersion model, AGU Fall Mtg., 2013.
Williams, D.B., Ramsey, M.S., Wickens, D.J. and Karimi, B., Identifying eruptive sources of drifting volcanic ash clouds using back-trajectory modelling and satellite data, Bull. Volc., (in preparation).