Detecting, Modelling and Responding to Effusive Eruptions
CONTAINS OPEN ACCESS
For effusive volcanoes in resource-poor regions, there is a pressing need for a crisis response-chain bridging the global scientific community to allow provision of standard products for timely humanitarian response. As a first step in attaining this need, this Special Publication provides a complete directory of current operational capabilities for monitoring effusive eruptions. This volume also reviews the state-of-the-art in terms of satellite-based volcano hot-spot tracking and lava-flow simulation. These capabilities are demonstrated using case studies taken from well-known effusive events that have occurred worldwide over the last two decades at volcanoes such as Piton de la Fournaise, Etna, Stromboli and Kilauea. We also provide case-type response models implemented at the same volcanoes, as well as the results of a community-wide drill used to test a fully-integrated response focused on an operational hazard-GIS. Finally, the objectives and recommendations of the ‘Risk Evaluation, Detection and Simulation during Effusive Eruption Disasters’ working group are laid out in a statement of community needs by its members.
Thermal monitoring of volcanic effusive activity: the uncertainties and outlier detection
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Published:January 01, 2016
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CiteCitation
Klemen Zakšek, Leonie Pick, Manoochehr Shirzaei, Matthias Hort, 2016. "Thermal monitoring of volcanic effusive activity: the uncertainties and outlier detection", Detecting, Modelling and Responding to Effusive Eruptions, A. J. L. Harris, T. De Groeve, F. Garel, S. A. Carn
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Abstract
Thermal observations of volcanic activity when the volcano is partially covered by clouds or observed under a wide-scan angle are often removed from further analyses. In the event of a volcanic crisis, such a reduced set of data is not adequate. Even when the observation conditions are favourable, the full observation set is still required to provide decision-makers with quality information about the data. Automatic quality estimation and outlier detection was not estimated in the past. We propose to analytically define the uncertainty for individual observations based on the measurement circumstances. To additionally reduce the temporal noise of the radiant power (RP) time series we apply a Kalman Filter (KF). The KF is able to recursively analyse an unevenly sampled time series. Based on some proposed rules, it can also detect outliers. We apply the proposed methodology to the 2008–09 Etna eruption monitored by MODIS (Moderate Resolution Imaging Spectroradiometer). The analysis of the results shows that the topography has a greater influence on RP than previously considered.
- accuracy
- algorithms
- atmosphere
- data management
- detection
- distribution
- emissivity
- equations
- errors
- eruptions
- Europe
- geologic hazards
- geophysical methods
- information management
- infrared spectra
- instruments
- Italy
- Kalman filters
- Landsat
- lava flows
- measurement
- MODIS
- monitoring
- Mount Etna
- natural hazards
- noise
- outliers
- pixels
- radiometers
- remote sensing
- satellite methods
- Sicily Italy
- simulation
- Southern Europe
- spectra
- standard deviation
- statistical analysis
- temperature
- thermal anomalies
- topography
- uncertainty
- volcanic risk
- volcanism
- MODVOLC
- SEVIRI
- radiant power
- normalized thermal index