Land cover classification using high‐resolution aerial photography in Adventdalen, Svalbard
Autor(a) principal: | |
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Data de Publicação: | 2015 |
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/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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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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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:RCAAP2024-11-20T17:46:08Zoai:repositorio.ul.pt:10451/35937Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-11-20T17:46:08Repositório 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 |
mluisa.alvim@gmail.com |
_version_ |
1817549022030725120 |