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Improving our understanding of individual wildfires by combining satellite data with fire spread modelling

Detalhes bibliográficos
Autor(a) principal: Benali, Akli Ait
Data de Publicação: 2018
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.5/17519
Resumo: Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia
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spelling Improving our understanding of individual wildfires by combining satellite data with fire spread modellingfire spreadmodellingsatellite thermal datafire managementuncertaintyDoutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de AgronomiaWildfires pose real threats to life and property. In Portugal, the recent year of 2017 had the largest burnt area extent and number of casualties. A knowledge gap still exists in wildfire research related with better understanding individual wildfires, which has important implications for fire suppression, management, and policies. Wildfire spread models have been used to study individual wildfires, however, associated uncertainties and the lack of systematic evaluation methods hamper their capability for accurately predicting their spread. Understanding how fire spread predictions can be improved is a critical research task, as they will only be deemed useful if they can provide accurate and reliable information to fire managers. The present Thesis proposes to contribute to improve fire spread predictions by: i) Developing a methodology to systematically evaluate fire spread predictions ii) Thoroughly characterizing input data uncertainty and its impact on predictions; iii) Improving predictions using data-driven model calibration. The spread of large historical wildfires were studied by combining satellite data and models. The major findings of the present Thesis were: i) Satellite data accurately contributed to provide accurate fire dates and ignition information for large wildfires. ii) The evaluation metrics were very useful in identifying areas and periods of low/high spatio-temporal agreement, highlighting the strong underprediction bias and poor accuracy of the predictions. iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions iii) Uncertainties in wind speed and direction, fuel model assignment and typology, location and timing of ignitions, had a major impact on prediction accuracy. iv) Predictions were improved by ‘learning’ from past wildfires, significantly reducing the impact of data uncertainty on the accuracy of fire spread predictions Overall, the work contributed to advance the body of knowledge regarding individual wildfires and identified future research steps towards a reliable operational fire system capable of supporting more effective and safer fire management decisions with the aim of reducing the dramatic impacts of wildfiresISA/ULPereira, José Miguel CardosoRepositório da Universidade de LisboaBenali, Akli Ait2019-03-06T16:13:09Z20182018-01-01T00:00:00Zdoctoral thesisinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.5/17519TID:101594305engBenali, A.A. - Improving our understanding of individual wildfires by combining satellite data with fire spread modelling. Lisboa: ISA, 2018, 104 p.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T16:09:49Zoai:repositorio.ulisboa.pt:10400.5/17519Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T04:04:39.074551Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
title Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
spellingShingle Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
Benali, Akli Ait
fire spread
modelling
satellite thermal data
fire management
uncertainty
title_short Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
title_full Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
title_fullStr Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
title_full_unstemmed Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
title_sort Improving our understanding of individual wildfires by combining satellite data with fire spread modelling
author Benali, Akli Ait
author_facet Benali, Akli Ait
author_role author
dc.contributor.none.fl_str_mv Pereira, José Miguel Cardoso
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Benali, Akli Ait
dc.subject.por.fl_str_mv fire spread
modelling
satellite thermal data
fire management
uncertainty
topic fire spread
modelling
satellite thermal data
fire management
uncertainty
description Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2019-03-06T16:13:09Z
dc.type.driver.fl_str_mv doctoral thesis
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/17519
TID:101594305
url http://hdl.handle.net/10400.5/17519
identifier_str_mv TID:101594305
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Benali, A.A. - Improving our understanding of individual wildfires by combining satellite data with fire spread modelling. Lisboa: ISA, 2018, 104 p.
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv ISA/UL
publisher.none.fl_str_mv ISA/UL
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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