Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard

Detalhes bibliográficos
Autor(a) principal: Mora, Carla
Data de Publicação: 2015
Outros Autores: Vieira, Goncalo, Pina, Pedro, Lousada, Maura, Christiansen, Hanne H.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/35937
Resumo: A methodology was tested for high‐resolution mapping of vegetation and detailed geoecological patterns in the Arctic Tundra, based on aerial imagery from an unmanned aerial vehicle (visible wavelength – RGB, 6 cm pixel resolution) and from an aircraft (visible and near infrared, 20 cm pixel resolution). The scenes were fused at 10 and 20 cm to evaluate their applicability for vegetation mapping in an alluvial fan in dventdalen, Svalbard. Ground‐truthing was used to create training and accuracy evaluation sets. Supervised classification tests were conducted with different band sets, including the original and derived ones, such as and principal component analysis bands. The fusion of all original bands at 10 cm resolution provided the best accuracies. The best classifier was systematically the maximum neighbourhood algorithm, with overall accuracies up to 84%. Mapped vegetation patterns reflect geoecological conditioning factors. The main limitation in the classification was differentiating between the classes graminea, moss and Salix, and moss, graminea and Salix, which showed spectral signature mixing. Silty‐clay surfaces are probably overestimated in the south part of the study area due to microscale shadowing effects. The results distinguished vegetation zones according to a general gradient of ecological limiting factors and show that + high‐resolution imagery are excellent tools for identifying the main vegetation groups within the lowland fan study site of dventdalen, but do not allow for detailed discrimination between species.
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spelling Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbardhigh‐resolution remote sensingnear infraredUAVvegetationSvalbardA methodology was tested for high‐resolution mapping of vegetation and detailed geoecological patterns in the Arctic Tundra, based on aerial imagery from an unmanned aerial vehicle (visible wavelength – RGB, 6 cm pixel resolution) and from an aircraft (visible and near infrared, 20 cm pixel resolution). The scenes were fused at 10 and 20 cm to evaluate their applicability for vegetation mapping in an alluvial fan in dventdalen, Svalbard. Ground‐truthing was used to create training and accuracy evaluation sets. Supervised classification tests were conducted with different band sets, including the original and derived ones, such as and principal component analysis bands. The fusion of all original bands at 10 cm resolution provided the best accuracies. The best classifier was systematically the maximum neighbourhood algorithm, with overall accuracies up to 84%. Mapped vegetation patterns reflect geoecological conditioning factors. The main limitation in the classification was differentiating between the classes graminea, moss and Salix, and moss, graminea and Salix, which showed spectral signature mixing. Silty‐clay surfaces are probably overestimated in the south part of the study area due to microscale shadowing effects. The results distinguished vegetation zones according to a general gradient of ecological limiting factors and show that + high‐resolution imagery are excellent tools for identifying the main vegetation groups within the lowland fan study site of dventdalen, but do not allow for detailed discrimination between species.Taylor & FrancisRepositório da Universidade de LisboaMora, CarlaVieira, GoncaloPina, PedroLousada, MauraChristiansen, Hanne H.2018-12-17T15:43:21Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/35937engMora, Carla, Vieira, Gonçalo, Pina, Pedro, Lousada, Maura, Christiansen, Hanne H. (2015). Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard. Geografiska Annaler: Series A, Physical Geography, 97:3, 473-488, DOI: 10.1111/geoa.120880435-367610.1111/geoa.12088info: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:RCAAP2023-11-08T16:32:17Zoai:repositorio.ul.pt:10451/35937Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:50:19.237756Repositório 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 Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
title Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
spellingShingle Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
Mora, Carla
high‐resolution remote sensing
near infrared
UAV
vegetation
Svalbard
title_short Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
title_full Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
title_fullStr Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
title_full_unstemmed Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
title_sort Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
author Mora, Carla
author_facet Mora, Carla
Vieira, Goncalo
Pina, Pedro
Lousada, Maura
Christiansen, Hanne H.
author_role author
author2 Vieira, Goncalo
Pina, Pedro
Lousada, Maura
Christiansen, Hanne H.
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Mora, Carla
Vieira, Goncalo
Pina, Pedro
Lousada, Maura
Christiansen, Hanne H.
dc.subject.por.fl_str_mv high‐resolution remote sensing
near infrared
UAV
vegetation
Svalbard
topic high‐resolution remote sensing
near infrared
UAV
vegetation
Svalbard
description A methodology was tested for high‐resolution mapping of vegetation and detailed geoecological patterns in the Arctic Tundra, based on aerial imagery from an unmanned aerial vehicle (visible wavelength – RGB, 6 cm pixel resolution) and from an aircraft (visible and near infrared, 20 cm pixel resolution). The scenes were fused at 10 and 20 cm to evaluate their applicability for vegetation mapping in an alluvial fan in dventdalen, Svalbard. Ground‐truthing was used to create training and accuracy evaluation sets. Supervised classification tests were conducted with different band sets, including the original and derived ones, such as and principal component analysis bands. The fusion of all original bands at 10 cm resolution provided the best accuracies. The best classifier was systematically the maximum neighbourhood algorithm, with overall accuracies up to 84%. Mapped vegetation patterns reflect geoecological conditioning factors. The main limitation in the classification was differentiating between the classes graminea, moss and Salix, and moss, graminea and Salix, which showed spectral signature mixing. Silty‐clay surfaces are probably overestimated in the south part of the study area due to microscale shadowing effects. The results distinguished vegetation zones according to a general gradient of ecological limiting factors and show that + high‐resolution imagery are excellent tools for identifying the main vegetation groups within the lowland fan study site of dventdalen, but do not allow for detailed discrimination between species.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2018-12-17T15:43:21Z
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/10451/35937
url http://hdl.handle.net/10451/35937
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Mora, Carla, Vieira, Gonçalo, Pina, Pedro, Lousada, Maura, Christiansen, Hanne H. (2015). Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard. Geografiska Annaler: Series A, Physical Geography, 97:3, 473-488, DOI: 10.1111/geoa.12088
0435-3676
10.1111/geoa.12088
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 Taylor & Francis
publisher.none.fl_str_mv Taylor & Francis
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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