Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash

Atmospheric natural hazards pose a risk to people, aircraft and infrastructure. Automated algorithms can detect these hazards from satellite imagery so that the relevant advice can be issued. The transparency and adaptability of these automated algorithms is important to cater to the needs of the en...

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Published in:Quarterly Journal of the Royal Meteorological Society
Main Authors: Western, Luke, Rougier, Jonathan, Watson, Matthew
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/1983/30699bdb-bcd3-4e06-a7ad-9693a7a4618a
https://research-information.bris.ac.uk/en/publications/30699bdb-bcd3-4e06-a7ad-9693a7a4618a
https://doi.org/10.1002/qj.3230
https://research-information.bris.ac.uk/ws/files/148603558/qj3230.pdf
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spelling ftubristolcris:oai:research-information.bris.ac.uk:publications/30699bdb-bcd3-4e06-a7ad-9693a7a4618a 2024-01-28T10:06:46+01:00 Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash Western, Luke Rougier, Jonathan Watson, Matthew 2018 application/pdf https://hdl.handle.net/1983/30699bdb-bcd3-4e06-a7ad-9693a7a4618a https://research-information.bris.ac.uk/en/publications/30699bdb-bcd3-4e06-a7ad-9693a7a4618a https://doi.org/10.1002/qj.3230 https://research-information.bris.ac.uk/ws/files/148603558/qj3230.pdf eng eng info:eu-repo/semantics/openAccess Western , L , Rougier , J & Watson , M 2018 , ' Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash ' , Quarterly Journal of the Royal Meteorological Society , vol. 144 , no. 711 , pp. 581-587 . https://doi.org/10.1002/qj.3230 detection of atmospheric natural hazards weather risk uncertainty in Earth observation decision support article 2018 ftubristolcris https://doi.org/10.1002/qj.3230 2024-01-04T23:54:33Z Atmospheric natural hazards pose a risk to people, aircraft and infrastructure. Automated algorithms can detect these hazards from satellite imagery so that the relevant advice can be issued. The transparency and adaptability of these automated algorithms is important to cater to the needs of the end user, who should be able to readily interpret the hazard warning. This means avoiding heuristic techniques. Decision theory is a statistical tool that transparently considers the risk of false positives and negatives when detecting the hazard. By assigning losses to incorrect actions, ownership of the hazard warning is shared between the scientists and risk managers. These losses are readily adaptable depending on the perceived threat of the hazard. This study demonstrates how decision theory can be applied to the detection of atmospheric natural hazards using the example of volcanic ash during an ongoing eruption. The only observations are the difference in brightness temperature between two channels on the SEVIRI sensor. We apply the method to two volcanic eruptions: the 2010 eruption of Eyjafjallajo ̈kull, Iceland, and the 2011 eruption of Puyehue-Cordo ́n Caulle, Chile. The simple probabilistic method appears to work well and is able to distinguish volcanic ash from desert dust, which is a common false positive for volcanic ash. As is made clear, decision theory is a tool for decision support, providing transparency and adaptability, but it still requires careful input from scientists and risk managers. Effectively it provides a space where these groups of experts can meet and convert their shared understanding of a hazard into a choice of action. Article in Journal/Newspaper Iceland University of Bristol: Bristol Research Quarterly Journal of the Royal Meteorological Society 144 711 581 587
institution Open Polar
collection University of Bristol: Bristol Research
op_collection_id ftubristolcris
language English
topic detection of atmospheric natural hazards
weather risk
uncertainty in Earth observation
decision support
spellingShingle detection of atmospheric natural hazards
weather risk
uncertainty in Earth observation
decision support
Western, Luke
Rougier, Jonathan
Watson, Matthew
Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
topic_facet detection of atmospheric natural hazards
weather risk
uncertainty in Earth observation
decision support
description Atmospheric natural hazards pose a risk to people, aircraft and infrastructure. Automated algorithms can detect these hazards from satellite imagery so that the relevant advice can be issued. The transparency and adaptability of these automated algorithms is important to cater to the needs of the end user, who should be able to readily interpret the hazard warning. This means avoiding heuristic techniques. Decision theory is a statistical tool that transparently considers the risk of false positives and negatives when detecting the hazard. By assigning losses to incorrect actions, ownership of the hazard warning is shared between the scientists and risk managers. These losses are readily adaptable depending on the perceived threat of the hazard. This study demonstrates how decision theory can be applied to the detection of atmospheric natural hazards using the example of volcanic ash during an ongoing eruption. The only observations are the difference in brightness temperature between two channels on the SEVIRI sensor. We apply the method to two volcanic eruptions: the 2010 eruption of Eyjafjallajo ̈kull, Iceland, and the 2011 eruption of Puyehue-Cordo ́n Caulle, Chile. The simple probabilistic method appears to work well and is able to distinguish volcanic ash from desert dust, which is a common false positive for volcanic ash. As is made clear, decision theory is a tool for decision support, providing transparency and adaptability, but it still requires careful input from scientists and risk managers. Effectively it provides a space where these groups of experts can meet and convert their shared understanding of a hazard into a choice of action.
format Article in Journal/Newspaper
author Western, Luke
Rougier, Jonathan
Watson, Matthew
author_facet Western, Luke
Rougier, Jonathan
Watson, Matthew
author_sort Western, Luke
title Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
title_short Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
title_full Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
title_fullStr Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
title_full_unstemmed Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
title_sort decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash
publishDate 2018
url https://hdl.handle.net/1983/30699bdb-bcd3-4e06-a7ad-9693a7a4618a
https://research-information.bris.ac.uk/en/publications/30699bdb-bcd3-4e06-a7ad-9693a7a4618a
https://doi.org/10.1002/qj.3230
https://research-information.bris.ac.uk/ws/files/148603558/qj3230.pdf
genre Iceland
genre_facet Iceland
op_source Western , L , Rougier , J & Watson , M 2018 , ' Decision theory based detection of atmospheric natural hazards from satellite imagery using the example of volcanic ash ' , Quarterly Journal of the Royal Meteorological Society , vol. 144 , no. 711 , pp. 581-587 . https://doi.org/10.1002/qj.3230
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1002/qj.3230
container_title Quarterly Journal of the Royal Meteorological Society
container_volume 144
container_issue 711
container_start_page 581
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