A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models

Live Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into...

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Autores: García, Mariano, Riaño, David, Yebra, Marta, Salas, Javier, Cardil, Adrián, Monedero, Santiago, Ramirez, Joaquín, Martín, M. Pilar, Vilar del Hoyo, Lara, Gajardo, John, Ustin, Susan
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/229107
Acceso en línea:http://hdl.handle.net/10261/229107
Access Level:acceso abierto
Palabra clave:Live fuel moisture content
Landsat-5 TM
Fire behavior simulator
Fire danger
Fire propagation
Data normalization
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spelling A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior modelsGarcía, MarianoRiaño, DavidYebra, MartaSalas, JavierCardil, AdriánMonedero, SantiagoRamirez, JoaquínMartín, M. PilarVilar del Hoyo, LaraGajardo, JohnUstin, SusanLive fuel moisture contentLandsat-5 TMFire behavior simulatorFire dangerFire propagationData normalizationLive Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into fire behavior simulation models. Nine chaparral sampling sites across three Landsat-5 Thematic Mapper (TM) scenes were used to validate the product over the Western USA. The relations between field-measured LFMC and Landsat-derived SIs were strong for each individual site but worsened when pooled together. The Enhanced Vegetation Index (EVI) presented the strongest correlations (r) and the least Root Mean Square Error (RMSE), followed by the Normalized Difference Infrared Index (NDII), Normalized Difference Vegetation Index (NDVI) and Visible Atmospherically Resistant Index (VARI). The relations between LFMC and the SIs for all sites improved after using their relative values and relative LFMC, increasing r from 0.44 up to 0.69 for relative EVI (relEVI), the best predictive variable. This relEVI served to estimate the herbaceous and woody LFMC based on minimum and maximum seasonal LFMC values. The understory herbaceous LFMC on the woody pixels was extrapolated from the surrounding pixels where the herbaceous vegetation is the top layer. Running simulations on the Wildfire Analyst (WFA) fire behavior model demonstrated that this LFMC product alone impacts significantly the fire spatial distribution in terms of burned probability, with average burned area differences over 21% after 8 h burning since ignition, compared to commonly carried out simulations based on constant values for each fuel model. The method could be applied to Landsat-7 and -8 and Sentinel-2A and -2B after proper sensor inter-calibration and topographic correctionNASA NNX11AF93G: The European Union SENSORVEG (FP7-PEOPLE-2009-IRSES-246666); and the Spanish Ministry of Economy and Competitiveness SynerTGE (CGL2015-G9095-R-MINECO/FEDER, EU) funded this research. In addition, a CONICYT Doctoral Fellowship from the Chilean Government supported J.G.Peer reviewedMultidisciplinary Digital Publishing InstituteEuropean CommissionMinisterio de Economía y Competitividad (España)García, Mariano [0000-0001-6260-5791]Riaño, David [0000-0002-0198-1424]Yebra, Marta [0000-0002-4049-9315]Salas, Javier [0000-0002-8208-6703]Cardil, Adrián [0000-0002-0185-3959]Martín, M. Pilar [0000-0002-5563-8461]Vilar del Hoyo, Lara [0000-0003-0872-1235]Ustin, Susan [0000-0001-8551-0461]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202120212020info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/10261/229107reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#eu-repo/grantAgreement/EC/FP7/246666info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2015-G9095-Rhttps://doi.org/10.3390/rs12111714https://doi.org/10.3390/rs12111714Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2291072026-05-22T06:33:51Z
dc.title.none.fl_str_mv A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
title A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
spellingShingle A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
García, Mariano
Live fuel moisture content
Landsat-5 TM
Fire behavior simulator
Fire danger
Fire propagation
Data normalization
title_short A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
title_full A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
title_fullStr A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
title_full_unstemmed A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
title_sort A live fuel moisture content product from landsat TM satellite time series for implementation in fire behavior models
dc.creator.none.fl_str_mv García, Mariano
Riaño, David
Yebra, Marta
Salas, Javier
Cardil, Adrián
Monedero, Santiago
Ramirez, Joaquín
Martín, M. Pilar
Vilar del Hoyo, Lara
Gajardo, John
Ustin, Susan
author García, Mariano
author_facet García, Mariano
Riaño, David
Yebra, Marta
Salas, Javier
Cardil, Adrián
Monedero, Santiago
Ramirez, Joaquín
Martín, M. Pilar
Vilar del Hoyo, Lara
Gajardo, John
Ustin, Susan
author_role author
author2 Riaño, David
Yebra, Marta
Salas, Javier
Cardil, Adrián
Monedero, Santiago
Ramirez, Joaquín
Martín, M. Pilar
Vilar del Hoyo, Lara
Gajardo, John
Ustin, Susan
author2_role author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv European Commission
Ministerio de Economía y Competitividad (España)
García, Mariano [0000-0001-6260-5791]
Riaño, David [0000-0002-0198-1424]
Yebra, Marta [0000-0002-4049-9315]
Salas, Javier [0000-0002-8208-6703]
Cardil, Adrián [0000-0002-0185-3959]
Martín, M. Pilar [0000-0002-5563-8461]
Vilar del Hoyo, Lara [0000-0003-0872-1235]
Ustin, Susan [0000-0001-8551-0461]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Live fuel moisture content
Landsat-5 TM
Fire behavior simulator
Fire danger
Fire propagation
Data normalization
topic Live fuel moisture content
Landsat-5 TM
Fire behavior simulator
Fire danger
Fire propagation
Data normalization
description Live Fuel Moisture Content (LFMC) contributes to fire danger and behavior, as it affects fire ignition and propagation. This paper presents a two layered Landsat LFMC product based on topographically corrected relative Spectral Indices (SI) over a 2000–2011 time series, which can be integrated into fire behavior simulation models. Nine chaparral sampling sites across three Landsat-5 Thematic Mapper (TM) scenes were used to validate the product over the Western USA. The relations between field-measured LFMC and Landsat-derived SIs were strong for each individual site but worsened when pooled together. The Enhanced Vegetation Index (EVI) presented the strongest correlations (r) and the least Root Mean Square Error (RMSE), followed by the Normalized Difference Infrared Index (NDII), Normalized Difference Vegetation Index (NDVI) and Visible Atmospherically Resistant Index (VARI). The relations between LFMC and the SIs for all sites improved after using their relative values and relative LFMC, increasing r from 0.44 up to 0.69 for relative EVI (relEVI), the best predictive variable. This relEVI served to estimate the herbaceous and woody LFMC based on minimum and maximum seasonal LFMC values. The understory herbaceous LFMC on the woody pixels was extrapolated from the surrounding pixels where the herbaceous vegetation is the top layer. Running simulations on the Wildfire Analyst (WFA) fire behavior model demonstrated that this LFMC product alone impacts significantly the fire spatial distribution in terms of burned probability, with average burned area differences over 21% after 8 h burning since ignition, compared to commonly carried out simulations based on constant values for each fuel model. The method could be applied to Landsat-7 and -8 and Sentinel-2A and -2B after proper sensor inter-calibration and topographic correction
publishDate 2020
dc.date.none.fl_str_mv 2020
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/229107
url http://hdl.handle.net/10261/229107
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
eu-repo/grantAgreement/EC/FP7/246666
info:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CGL2015-G9095-R
https://doi.org/10.3390/rs12111714
https://doi.org/10.3390/rs12111714
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.81155

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