Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data

Detalhes bibliográficos
Autor(a) principal: Lemos Maia Santos, Filippe
Data de Publicação: 2019
Outros Autores: Abrantes Rodrigues, Julia, Arantes Pereira, Allan, de Faria Peres, Leonardo, Gouveia, Célia, Libonati, Renata
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Biodiversidade Brasileira
Texto Completo: https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1068
Resumo: Prescribed burning (PB) is a commonly used technique to reduce fuel loads, where fire is introduced under specific and controlled conditions before fire season, thus mitigating the risk and the adverse effects of wildland fire, and the associated high suppressions costs. Fire management agencies require estimations about recovery time over areas under prescribed fire activities in order to determine the extent and spatiotemporal pattern of required actions needed to reduce future fire risk. Post-fire dynamics is a complex phenomenon in which remote sensing techniques play a significant role, providing the opportunity to study fire effects and vegetation recovery over large areas on a long-term basis. In 2014, PB under the scope of the Integrated Fire Management (IFM) were started in some Conservation Units located at Cerrado. However, until now, there is a gap in studies investigating how vegetation behaves after those prescribed fires using satellite data. Therefore, here we aim to estimate and evaluate the vegetation recovery rate over areas managed with prescribed fires based on satellite-derived indexes. Time-series of spectral indices, such as Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Burn Recovery Ratio (BRR), are derived from multi-spectral Landsat surface reflectance imagery through Google Earth Engine platform. Special attention is devoted to the identification of which factors are most important for the recovery process. The duration of the effectiveness of fuel reduction due to PB activities is analysed between 2010 and 2018, in order to verify pre e postIMF conditions. By evaluating the vegetation post-fire recovery time we envisage the construction of indicators about the longevity of the inhibitory effect of PB, allowing the quantification of its impacts on the incidence, severity and extent of unplanned fires. Thus, this work may provide clear directions in the IFM related to PB.
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spelling Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing DataVegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing DataVegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing DataPrescribed burning (PB) is a commonly used technique to reduce fuel loads, where fire is introduced under specific and controlled conditions before fire season, thus mitigating the risk and the adverse effects of wildland fire, and the associated high suppressions costs. Fire management agencies require estimations about recovery time over areas under prescribed fire activities in order to determine the extent and spatiotemporal pattern of required actions needed to reduce future fire risk. Post-fire dynamics is a complex phenomenon in which remote sensing techniques play a significant role, providing the opportunity to study fire effects and vegetation recovery over large areas on a long-term basis. In 2014, PB under the scope of the Integrated Fire Management (IFM) were started in some Conservation Units located at Cerrado. However, until now, there is a gap in studies investigating how vegetation behaves after those prescribed fires using satellite data. Therefore, here we aim to estimate and evaluate the vegetation recovery rate over areas managed with prescribed fires based on satellite-derived indexes. Time-series of spectral indices, such as Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Burn Recovery Ratio (BRR), are derived from multi-spectral Landsat surface reflectance imagery through Google Earth Engine platform. Special attention is devoted to the identification of which factors are most important for the recovery process. The duration of the effectiveness of fuel reduction due to PB activities is analysed between 2010 and 2018, in order to verify pre e postIMF conditions. By evaluating the vegetation post-fire recovery time we envisage the construction of indicators about the longevity of the inhibitory effect of PB, allowing the quantification of its impacts on the incidence, severity and extent of unplanned fires. Thus, this work may provide clear directions in the IFM related to PB.Prescribed burning (PB) is a commonly used technique to reduce fuel loads, where fire is introduced under specific and controlled conditions before fire season, thus mitigating the risk and the adverse effects of wildland fire, and the associated high suppressions costs. Fire management agencies require estimations about recovery time over areas under prescribed fire activities in order to determine the extent and spatiotemporal pattern of required actions needed to reduce future fire risk. Post-fire dynamics is a complex phenomenon in which remote sensing techniques play a significant role, providing the opportunity to study fire effects and vegetation recovery over large areas on a long-term basis. In 2014, PB under the scope of the Integrated Fire Management (IFM) were started in some Conservation Units located at Cerrado. However, until now, there is a gap in studies investigating how vegetation behaves after those prescribed fires using satellite data. Therefore, here we aim to estimate and evaluate the vegetation recovery rate over areas managed with prescribed fires based on satellite-derived indexes. Time-series of spectral indices, such as Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Burn Recovery Ratio (BRR), are derived from multi-spectral Landsat surface reflectance imagery through Google Earth Engine platform. Special attention is devoted to the identification of which factors are most important for the recovery process. The duration of the effectiveness of fuel reduction due to PB activities is analysed between 2010 and 2018, in order to verify pre e postIMF conditions. By evaluating the vegetation post-fire recovery time we envisage the construction of indicators about the longevity of the inhibitory effect of PB, allowing the quantification of its impacts on the incidence, severity and extent of unplanned fires. Thus, this work may provide clear directions in the IFM related to PB.Prescribed burning (PB) is a commonly used technique to reduce fuel loads, where fire is introduced under specific and controlled conditions before fire season, thus mitigating the risk and the adverse effects of wildland fire, and the associated high suppressions costs. Fire management agencies require estimations about recovery time over areas under prescribed fire activities in order to determine the extent and spatiotemporal pattern of required actions needed to reduce future fire risk. Post-fire dynamics is a complex phenomenon in which remote sensing techniques play a significant role, providing the opportunity to study fire effects and vegetation recovery over large areas on a long-term basis. In 2014, PB under the scope of the Integrated Fire Management (IFM) were started in some Conservation Units located at Cerrado. However, until now, there is a gap in studies investigating how vegetation behaves after those prescribed fires using satellite data. Therefore, here we aim to estimate and evaluate the vegetation recovery rate over areas managed with prescribed fires based on satellite-derived indexes. Time-series of spectral indices, such as Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Burn Recovery Ratio (BRR), are derived from multi-spectral Landsat surface reflectance imagery through Google Earth Engine platform. Special attention is devoted to the identification of which factors are most important for the recovery process. The duration of the effectiveness of fuel reduction due to PB activities is analysed between 2010 and 2018, in order to verify pre e postIMF conditions. By evaluating the vegetation post-fire recovery time we envisage the construction of indicators about the longevity of the inhibitory effect of PB, allowing the quantification of its impacts on the incidence, severity and extent of unplanned fires. Thus, this work may provide clear directions in the IFM related to PB.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/106810.37002/biodiversidadebrasileira.v9i1.1068Biodiversidade Brasileira ; v. 9 n. 1 (2019): Wildfire Conference: Resumos; 166Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 166Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 1662236-288610.37002/biodiversidadebrasileira.v9i1reponame:Biodiversidade Brasileirainstname:Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)instacron:ICMBIOenghttps://revistaeletronica.icmbio.gov.br/BioBR/article/view/1068/813Copyright (c) 2021 Biodiversidade Brasileira - BioBrasilhttps://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessLemos Maia Santos, FilippeAbrantes Rodrigues, JuliaArantes Pereira, Allande Faria Peres, LeonardoGouveia, CéliaLibonati, Renata2023-05-09T12:56:02Zoai:revistaeletronica.icmbio.gov.br:article/1068Revistahttps://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 Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
title Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
spellingShingle Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
Lemos Maia Santos, Filippe
title_short Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
title_full Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
title_fullStr Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
title_full_unstemmed Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
title_sort Vegetation Recovery Analysis Over Areas Managed with Prescribed Fires: an Approach Using Remote Sensing Data
author Lemos Maia Santos, Filippe
author_facet Lemos Maia Santos, Filippe
Abrantes Rodrigues, Julia
Arantes Pereira, Allan
de Faria Peres, Leonardo
Gouveia, Célia
Libonati, Renata
author_role author
author2 Abrantes Rodrigues, Julia
Arantes Pereira, Allan
de Faria Peres, Leonardo
Gouveia, Célia
Libonati, Renata
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Lemos Maia Santos, Filippe
Abrantes Rodrigues, Julia
Arantes Pereira, Allan
de Faria Peres, Leonardo
Gouveia, Célia
Libonati, Renata
description Prescribed burning (PB) is a commonly used technique to reduce fuel loads, where fire is introduced under specific and controlled conditions before fire season, thus mitigating the risk and the adverse effects of wildland fire, and the associated high suppressions costs. Fire management agencies require estimations about recovery time over areas under prescribed fire activities in order to determine the extent and spatiotemporal pattern of required actions needed to reduce future fire risk. Post-fire dynamics is a complex phenomenon in which remote sensing techniques play a significant role, providing the opportunity to study fire effects and vegetation recovery over large areas on a long-term basis. In 2014, PB under the scope of the Integrated Fire Management (IFM) were started in some Conservation Units located at Cerrado. However, until now, there is a gap in studies investigating how vegetation behaves after those prescribed fires using satellite data. Therefore, here we aim to estimate and evaluate the vegetation recovery rate over areas managed with prescribed fires based on satellite-derived indexes. Time-series of spectral indices, such as Normalized Burn Ratio (NBR), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI) and Burn Recovery Ratio (BRR), are derived from multi-spectral Landsat surface reflectance imagery through Google Earth Engine platform. Special attention is devoted to the identification of which factors are most important for the recovery process. The duration of the effectiveness of fuel reduction due to PB activities is analysed between 2010 and 2018, in order to verify pre e postIMF conditions. By evaluating the vegetation post-fire recovery time we envisage the construction of indicators about the longevity of the inhibitory effect of PB, allowing the quantification of its impacts on the incidence, severity and extent of unplanned fires. Thus, this work may provide clear directions in the IFM related to PB.
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/1068
10.37002/biodiversidadebrasileira.v9i1.1068
url https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1068
identifier_str_mv 10.37002/biodiversidadebrasileira.v9i1.1068
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1068/813
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; 166
Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 166
Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 166
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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