Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10316/100506 https://doi.org/10.3390/rs14092028 |
Resumo: | Moderate-resolution satellite imagery is essential to detect conifer tree decline on a regional scale and address the threat caused by pinewood nematode (PWN), (Bursaphelenchus xylophilus. This is a quarantine organism responsible for pine wilt disease (PWD), which has caused substantial ecological and economic losses in the maritime pine (Pinus pinaster) forests of Portugal. This study describes the first instance of a pre-operational algorithm applied to Sentinel-2 imagery to detect PWD-compatible decline in maritime pine. The Random Forest model relied on a pre-wilting and an in-season image, calibrated with data from a 24-month long field campaign enhanced withWorldview- 3 data and the analysis of biological samples (hyperspectral reflectance, pigment quantification in needles, and PWN identification). Independent validation results attested to the good performance of the model with an overall accuracy of 95%, particularly when decline affects more than 30% of the 100 m2 pixel of Sentinel-2. Spectral angle mapper applied to hyperspectral measurements suggested that PWN infection cannot be separated from other drivers of decline in the visible-near infrared domain. Our algorithm can be employed to detect regional decline trends and inform subsequent aerial and field surveys, to further investigate decline hotspots. |
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Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Datamachine-learningpinewood nematodepine wilt diseaseremote sensingSentinel-2tree declineModerate-resolution satellite imagery is essential to detect conifer tree decline on a regional scale and address the threat caused by pinewood nematode (PWN), (Bursaphelenchus xylophilus. This is a quarantine organism responsible for pine wilt disease (PWD), which has caused substantial ecological and economic losses in the maritime pine (Pinus pinaster) forests of Portugal. This study describes the first instance of a pre-operational algorithm applied to Sentinel-2 imagery to detect PWD-compatible decline in maritime pine. The Random Forest model relied on a pre-wilting and an in-season image, calibrated with data from a 24-month long field campaign enhanced withWorldview- 3 data and the analysis of biological samples (hyperspectral reflectance, pigment quantification in needles, and PWN identification). Independent validation results attested to the good performance of the model with an overall accuracy of 95%, particularly when decline affects more than 30% of the 100 m2 pixel of Sentinel-2. Spectral angle mapper applied to hyperspectral measurements suggested that PWN infection cannot be separated from other drivers of decline in the visible-near infrared domain. Our algorithm can be employed to detect regional decline trends and inform subsequent aerial and field surveys, to further investigate decline hotspots.2022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/100506http://hdl.handle.net/10316/100506https://doi.org/10.3390/rs14092028eng2072-4292Mantas, VascoFonseca, LuísBaltazar, ElsaCanhoto, JorgeAbrantes, Isabelinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-06-27T20:34:29Zoai:estudogeral.uc.pt:10316/100506Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:17:52.850590Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
title |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
spellingShingle |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data Mantas, Vasco machine-learning pinewood nematode pine wilt disease remote sensing Sentinel-2 tree decline |
title_short |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
title_full |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
title_fullStr |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
title_full_unstemmed |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
title_sort |
Detection of Tree Decline (Pinus pinaster Aiton) in European Forests Using Sentinel-2 Data |
author |
Mantas, Vasco |
author_facet |
Mantas, Vasco Fonseca, Luís Baltazar, Elsa Canhoto, Jorge Abrantes, Isabel |
author_role |
author |
author2 |
Fonseca, Luís Baltazar, Elsa Canhoto, Jorge Abrantes, Isabel |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Mantas, Vasco Fonseca, Luís Baltazar, Elsa Canhoto, Jorge Abrantes, Isabel |
dc.subject.por.fl_str_mv |
machine-learning pinewood nematode pine wilt disease remote sensing Sentinel-2 tree decline |
topic |
machine-learning pinewood nematode pine wilt disease remote sensing Sentinel-2 tree decline |
description |
Moderate-resolution satellite imagery is essential to detect conifer tree decline on a regional scale and address the threat caused by pinewood nematode (PWN), (Bursaphelenchus xylophilus. This is a quarantine organism responsible for pine wilt disease (PWD), which has caused substantial ecological and economic losses in the maritime pine (Pinus pinaster) forests of Portugal. This study describes the first instance of a pre-operational algorithm applied to Sentinel-2 imagery to detect PWD-compatible decline in maritime pine. The Random Forest model relied on a pre-wilting and an in-season image, calibrated with data from a 24-month long field campaign enhanced withWorldview- 3 data and the analysis of biological samples (hyperspectral reflectance, pigment quantification in needles, and PWN identification). Independent validation results attested to the good performance of the model with an overall accuracy of 95%, particularly when decline affects more than 30% of the 100 m2 pixel of Sentinel-2. Spectral angle mapper applied to hyperspectral measurements suggested that PWN infection cannot be separated from other drivers of decline in the visible-near infrared domain. Our algorithm can be employed to detect regional decline trends and inform subsequent aerial and field surveys, to further investigate decline hotspots. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10316/100506 http://hdl.handle.net/10316/100506 https://doi.org/10.3390/rs14092028 |
url |
http://hdl.handle.net/10316/100506 https://doi.org/10.3390/rs14092028 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2072-4292 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799134074300792832 |