Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales

Updated and harmonized land cover (LC) data is essential for wildfire estimation in fire-prone areas as is the case in southern Europe. CORINE Land cover (CLC) and ESA Climate Change Initiative Land Cover (CCI-LC) maps have been analyzed and compared their performance in the estimation of wildfire o...

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Autores: Vilar del Hoyo, Lara, Garrido, Jesús, Echavarría Daspet, Pilar, Martínez Vega, Javier, Martín, M. Pilar
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2019
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/211281
Acesso em linha:http://hdl.handle.net/10261/211281
Access Level:acceso abierto
Palavra-chave:CORINE
Climate change initiative land cover
Generalized linear models
InterfacesSpatial analysis
Wildfire occurrence
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spelling Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scalesVilar del Hoyo, LaraGarrido, JesúsEchavarría Daspet, PilarMartínez Vega, JavierMartín, M. PilarCORINEClimate change initiative land coverGeneralized linear modelsInterfacesSpatial analysisWildfire occurrenceUpdated and harmonized land cover (LC) data is essential for wildfire estimation in fire-prone areas as is the case in southern Europe. CORINE Land cover (CLC) and ESA Climate Change Initiative Land Cover (CCI-LC) maps have been analyzed and compared their performance in the estimation of wildfire occurrence in Europe at regional and local scales for the period 2010–2014. LC maps legends were harmonized and similarities and discrepancies were compared. Overall agreement between the two maps for the whole Europe was ˜75%. Forest and agriculture showed the largest agreement, while shrubland and grassland the lowest. Quantity and allocation disagreements were calculated including exchange and shift components (Pontius and Santacruz, 2014) which provided detailed information about the contribution of each class to the overall disagreement. Spatial discrepancies were found in areas where grassland and shrubland were the dominant classes as in United Kingdom or East Turkey. Land Use and Coverage Area frame Survey (LUCAS) was used as ground truth for validation purposes. The agreement with LUCAS was slightly higher for CCI-LC (59%) than for CLC (56%). Generalized Linear Models (GLM), based on presence-absence of wildfires, were used to estimate wildfire occurrence at 3 × 3 km grid cell resolution from both LC maps at the European scale. LC interfaces and climatic variables (temperature and precipitation) where used as explicative variables while fires from European Forest Fire Information System EFFIS (2010–2014 period) were used as response variable. Wildfire occurrence was also estimated with the two maps at local scale in a test region (Zamora, Spain) using a more precise location of the response variable (x, y fire ignition points). At the European scale models obtained within the two maps showed similar results. CCI-LC model sensitivity was 77.26%, specificity 25.89% and omission error 22.74% while CLC model sensitivity was 75.68%, specificity 29.99% and omission error 24.32%. However, CLC performed slightly better in terms of the percent correct classification (62%). In the test region the models achieved better results in terms of specificity (66.07% and 68.93% for CCI-LC and CLC models respectively) and percent correct classification (˜68% for CLC model). At local scale CLC model performed better than CCI-LC model. Wildfire occurrence estimation was more accurate at local scale because of the differences in the spatial accuracy of the response variable used.Peer reviewedElsevierMartínez Vega, Javier [0000-0002-8519-120X]Vilar del Hoyo, Lara [0000-0003-0872-1235]Martín, M. Pilar [0000-0002-5563-8461]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2020202020192020info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/211281reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.1016/j.jag.2019.01.019Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2112812026-05-22T06:33:51Z
dc.title.none.fl_str_mv Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
title Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
spellingShingle Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
Vilar del Hoyo, Lara
CORINE
Climate change initiative land cover
Generalized linear models
InterfacesSpatial analysis
Wildfire occurrence
title_short Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
title_full Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
title_fullStr Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
title_full_unstemmed Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
title_sort Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales
dc.creator.none.fl_str_mv Vilar del Hoyo, Lara
Garrido, Jesús
Echavarría Daspet, Pilar
Martínez Vega, Javier
Martín, M. Pilar
author Vilar del Hoyo, Lara
author_facet Vilar del Hoyo, Lara
Garrido, Jesús
Echavarría Daspet, Pilar
Martínez Vega, Javier
Martín, M. Pilar
author_role author
author2 Garrido, Jesús
Echavarría Daspet, Pilar
Martínez Vega, Javier
Martín, M. Pilar
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Martínez Vega, Javier [0000-0002-8519-120X]
Vilar del Hoyo, Lara [0000-0003-0872-1235]
Martín, M. Pilar [0000-0002-5563-8461]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv CORINE
Climate change initiative land cover
Generalized linear models
InterfacesSpatial analysis
Wildfire occurrence
topic CORINE
Climate change initiative land cover
Generalized linear models
InterfacesSpatial analysis
Wildfire occurrence
description Updated and harmonized land cover (LC) data is essential for wildfire estimation in fire-prone areas as is the case in southern Europe. CORINE Land cover (CLC) and ESA Climate Change Initiative Land Cover (CCI-LC) maps have been analyzed and compared their performance in the estimation of wildfire occurrence in Europe at regional and local scales for the period 2010–2014. LC maps legends were harmonized and similarities and discrepancies were compared. Overall agreement between the two maps for the whole Europe was ˜75%. Forest and agriculture showed the largest agreement, while shrubland and grassland the lowest. Quantity and allocation disagreements were calculated including exchange and shift components (Pontius and Santacruz, 2014) which provided detailed information about the contribution of each class to the overall disagreement. Spatial discrepancies were found in areas where grassland and shrubland were the dominant classes as in United Kingdom or East Turkey. Land Use and Coverage Area frame Survey (LUCAS) was used as ground truth for validation purposes. The agreement with LUCAS was slightly higher for CCI-LC (59%) than for CLC (56%). Generalized Linear Models (GLM), based on presence-absence of wildfires, were used to estimate wildfire occurrence at 3 × 3 km grid cell resolution from both LC maps at the European scale. LC interfaces and climatic variables (temperature and precipitation) where used as explicative variables while fires from European Forest Fire Information System EFFIS (2010–2014 period) were used as response variable. Wildfire occurrence was also estimated with the two maps at local scale in a test region (Zamora, Spain) using a more precise location of the response variable (x, y fire ignition points). At the European scale models obtained within the two maps showed similar results. CCI-LC model sensitivity was 77.26%, specificity 25.89% and omission error 22.74% while CLC model sensitivity was 75.68%, specificity 29.99% and omission error 24.32%. However, CLC performed slightly better in terms of the percent correct classification (62%). In the test region the models achieved better results in terms of specificity (66.07% and 68.93% for CCI-LC and CLC models respectively) and percent correct classification (˜68% for CLC model). At local scale CLC model performed better than CCI-LC model. Wildfire occurrence estimation was more accurate at local scale because of the differences in the spatial accuracy of the response variable used.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/211281
url http://hdl.handle.net/10261/211281
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.1016/j.jag.2019.01.019
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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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