Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement

Detalhes bibliográficos
Autor(a) principal: Fisher, Rohan
Data de Publicação: 2019
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Biodiversidade Brasileira
Texto Completo: https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1036
Resumo: The science of fire spread modelling has traditionally focused on providing predictive tools using empirically derived rate of spread calculations. However, fire spread prediction is difficult and whilst it can be a helpful tool for emergency management support the effective use of predictive rate of spread models are generally limited to relatively small spatiotemporal scales in data-rich environments. It is argued that this approach has particular value in the context of in the vast fire prone landscapes of tropical Northern Australia where biodiversity, cultural and carbon abatement considerations are more significant drives than emergency management. This is applied through a novel participatory modelling and gamification approach aimed at building shared understandings of complex fire behaviour. Described is the development of a Stochastic Cellular Automata fire behaviour simulation through a participatory modelling process that makes explicit the key variables affecting fire behaviour at a landscape scale in Northern Australia. This work aims to fill a gap in fire behaviour modelling tools by focusing on learning and participatory planning outcomes though fire behaviour simulation. A range of operational applications of this approach, within indigenous and non-indigenous communities of Northern Australia, are described and the value of predictive vrs explanatory environmental modelling for understanding fire behaviour assessed.
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spelling Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community EngagementFire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community EngagementThe science of fire spread modelling has traditionally focused on providing predictive tools using empirically derived rate of spread calculations. However, fire spread prediction is difficult and whilst it can be a helpful tool for emergency management support the effective use of predictive rate of spread models are generally limited to relatively small spatiotemporal scales in data-rich environments. It is argued that this approach has particular value in the context of in the vast fire prone landscapes of tropical Northern Australia where biodiversity, cultural and carbon abatement considerations are more significant drives than emergency management. This is applied through a novel participatory modelling and gamification approach aimed at building shared understandings of complex fire behaviour. Described is the development of a Stochastic Cellular Automata fire behaviour simulation through a participatory modelling process that makes explicit the key variables affecting fire behaviour at a landscape scale in Northern Australia. This work aims to fill a gap in fire behaviour modelling tools by focusing on learning and participatory planning outcomes though fire behaviour simulation. A range of operational applications of this approach, within indigenous and non-indigenous communities of Northern Australia, are described and the value of predictive vrs explanatory environmental modelling for understanding fire behaviour assessed.The science of fire spread modelling has traditionally focused on providing predictive tools using empirically derived rate of spread calculations. However, fire spread prediction is difficult and whilst it can be a helpful tool for emergency management support the effective use of predictive rate of spread models are generally limited to relatively small spatiotemporal scales in data-rich environments. It is argued that this approach has particular value in the context of in the vast fire prone landscapes of tropical Northern Australia where biodiversity, cultural and carbon abatement considerations are more significant drives than emergency management. This is applied through a novel participatory modelling and gamification approach aimed at building shared understandings of complex fire behaviour. Described is the development of a Stochastic Cellular Automata fire behaviour simulation through a participatory modelling process that makes explicit the key variables affecting fire behaviour at a landscape scale in Northern Australia. This work aims to fill a gap in fire behaviour modelling tools by focusing on learning and participatory planning outcomes though fire behaviour simulation. A range of operational applications of this approach, within indigenous and non-indigenous communities of Northern Australia, are described and the value of predictive vrs explanatory environmental modelling for understanding fire behaviour assessed.Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)2019-11-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistaeletronica.icmbio.gov.br/BioBR/article/view/103610.37002/biodiversidadebrasileira.v9i1.1036Biodiversidade Brasileira ; v. 9 n. 1 (2019): Wildfire Conference: Resumos; 118Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 118Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 1182236-288610.37002/biodiversidadebrasileira.v9i1reponame:Biodiversidade Brasileirainstname:Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)instacron:ICMBIOenghttps://revistaeletronica.icmbio.gov.br/BioBR/article/view/1036/763Copyright (c) 2021 Biodiversidade Brasileira - BioBrasilhttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessFisher, Rohan2023-05-09T12:56:02Zoai:revistaeletronica.icmbio.gov.br:article/1036Revistahttps://revistaeletronica.icmbio.gov.br/BioBRPUBhttps://revistaeletronica.icmbio.gov.br/BioBR/oaifernanda.oliveto@icmbio.gov.br || katia.ribeiro@icmbio.gov.br2236-28862236-2886opendoar:2023-05-09T12:56:02Biodiversidade Brasileira - Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)false
dc.title.none.fl_str_mv Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
title Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
spellingShingle Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
Fisher, Rohan
title_short Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
title_full Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
title_fullStr Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
title_full_unstemmed Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
title_sort Fire Behaviour Simulation; a Gamification Approach Supporting Complex System Learning and, Fire Management Planning and Community Engagement
author Fisher, Rohan
author_facet Fisher, Rohan
author_role author
dc.contributor.author.fl_str_mv Fisher, Rohan
description The science of fire spread modelling has traditionally focused on providing predictive tools using empirically derived rate of spread calculations. However, fire spread prediction is difficult and whilst it can be a helpful tool for emergency management support the effective use of predictive rate of spread models are generally limited to relatively small spatiotemporal scales in data-rich environments. It is argued that this approach has particular value in the context of in the vast fire prone landscapes of tropical Northern Australia where biodiversity, cultural and carbon abatement considerations are more significant drives than emergency management. This is applied through a novel participatory modelling and gamification approach aimed at building shared understandings of complex fire behaviour. Described is the development of a Stochastic Cellular Automata fire behaviour simulation through a participatory modelling process that makes explicit the key variables affecting fire behaviour at a landscape scale in Northern Australia. This work aims to fill a gap in fire behaviour modelling tools by focusing on learning and participatory planning outcomes though fire behaviour simulation. A range of operational applications of this approach, within indigenous and non-indigenous communities of Northern Australia, are described and the value of predictive vrs explanatory environmental modelling for understanding fire behaviour assessed.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-15
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1036
10.37002/biodiversidadebrasileira.v9i1.1036
url https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1036
identifier_str_mv 10.37002/biodiversidadebrasileira.v9i1.1036
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1036/763
dc.rights.driver.fl_str_mv Copyright (c) 2021 Biodiversidade Brasileira - BioBrasil
https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Biodiversidade Brasileira - BioBrasil
https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)
publisher.none.fl_str_mv Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)
dc.source.none.fl_str_mv Biodiversidade Brasileira ; v. 9 n. 1 (2019): Wildfire Conference: Resumos; 118
Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 118
Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 118
2236-2886
10.37002/biodiversidadebrasileira.v9i1
reponame:Biodiversidade Brasileira
instname:Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
instacron:ICMBIO
instname_str Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
instacron_str ICMBIO
institution ICMBIO
reponame_str Biodiversidade Brasileira
collection Biodiversidade Brasileira
repository.name.fl_str_mv Biodiversidade Brasileira - Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
repository.mail.fl_str_mv fernanda.oliveto@icmbio.gov.br || katia.ribeiro@icmbio.gov.br
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