Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images

Detalhes bibliográficos
Autor(a) principal: FONSECA,ELIANA L.
Data de Publicação: 2022
Outros Autores: SANTOS,EDVAN C. DOS, FIGUEIREDO,ANDERSON R. DE, SIMÕES,JEFFERSON C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Anais da Academia Brasileira de Ciências (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201006
Resumo: Abstract The remote sensing techniques must be used to obtain long-term information in remote areas, like the Antarctic continent, to monitor the environmental productivity and its changes. The aim of this work was to analyze the surface reflectance profile patterns for the Antarctic biological soil crusts (algae, lichens, and mosses) in an area of Nelson Island (South Shetland Islands, maritime Antarctic), calculated from Landsat and Sentinel-2 images to identify its similarities and differences due to targets, sensors and acquired date. The surface reflectance values for Antarctic biological soil crusts are similar for those observed for biological soil crusts in other Earth extreme environments, like deserts. In Landsat images, the differences among biological soil crusts surface reflectance were identified at visible and near-infrared wavelengths and for Sentinel-2 images, the differences occur at visible, red-edge and shortwave infrared wavelengths, showing the feasibility of using surface reflectance products to identify these different crusts, despite its inherent pixel spectral mixture. Long-term biophysical parameters from such crusts as retrieved from orbital data is not possible due to very low cloud-free images over the Antarctic, which prevents building a consistent surface reflectance time-series which covers all biological soil crusts growth season.
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spelling Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 imagesbiophysical parameterscross calibrationclassificationGoogle Earth Enginetime-series analysisvegetationAbstract The remote sensing techniques must be used to obtain long-term information in remote areas, like the Antarctic continent, to monitor the environmental productivity and its changes. The aim of this work was to analyze the surface reflectance profile patterns for the Antarctic biological soil crusts (algae, lichens, and mosses) in an area of Nelson Island (South Shetland Islands, maritime Antarctic), calculated from Landsat and Sentinel-2 images to identify its similarities and differences due to targets, sensors and acquired date. The surface reflectance values for Antarctic biological soil crusts are similar for those observed for biological soil crusts in other Earth extreme environments, like deserts. In Landsat images, the differences among biological soil crusts surface reflectance were identified at visible and near-infrared wavelengths and for Sentinel-2 images, the differences occur at visible, red-edge and shortwave infrared wavelengths, showing the feasibility of using surface reflectance products to identify these different crusts, despite its inherent pixel spectral mixture. Long-term biophysical parameters from such crusts as retrieved from orbital data is not possible due to very low cloud-free images over the Antarctic, which prevents building a consistent surface reflectance time-series which covers all biological soil crusts growth season.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201006Anais da Academia Brasileira de Ciências v.94 suppl.1 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220210596info:eu-repo/semantics/openAccessFONSECA,ELIANA L.SANTOS,EDVAN C. DOSFIGUEIREDO,ANDERSON R. DESIMÕES,JEFFERSON C.eng2022-05-04T00:00:00Zoai:scielo:S0001-37652022000201006Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-05-04T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
title Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
spellingShingle Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
FONSECA,ELIANA L.
biophysical parameters
cross calibration
classification
Google Earth Engine
time-series analysis
vegetation
title_short Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
title_full Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
title_fullStr Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
title_full_unstemmed Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
title_sort Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images
author FONSECA,ELIANA L.
author_facet FONSECA,ELIANA L.
SANTOS,EDVAN C. DOS
FIGUEIREDO,ANDERSON R. DE
SIMÕES,JEFFERSON C.
author_role author
author2 SANTOS,EDVAN C. DOS
FIGUEIREDO,ANDERSON R. DE
SIMÕES,JEFFERSON C.
author2_role author
author
author
dc.contributor.author.fl_str_mv FONSECA,ELIANA L.
SANTOS,EDVAN C. DOS
FIGUEIREDO,ANDERSON R. DE
SIMÕES,JEFFERSON C.
dc.subject.por.fl_str_mv biophysical parameters
cross calibration
classification
Google Earth Engine
time-series analysis
vegetation
topic biophysical parameters
cross calibration
classification
Google Earth Engine
time-series analysis
vegetation
description Abstract The remote sensing techniques must be used to obtain long-term information in remote areas, like the Antarctic continent, to monitor the environmental productivity and its changes. The aim of this work was to analyze the surface reflectance profile patterns for the Antarctic biological soil crusts (algae, lichens, and mosses) in an area of Nelson Island (South Shetland Islands, maritime Antarctic), calculated from Landsat and Sentinel-2 images to identify its similarities and differences due to targets, sensors and acquired date. The surface reflectance values for Antarctic biological soil crusts are similar for those observed for biological soil crusts in other Earth extreme environments, like deserts. In Landsat images, the differences among biological soil crusts surface reflectance were identified at visible and near-infrared wavelengths and for Sentinel-2 images, the differences occur at visible, red-edge and shortwave infrared wavelengths, showing the feasibility of using surface reflectance products to identify these different crusts, despite its inherent pixel spectral mixture. Long-term biophysical parameters from such crusts as retrieved from orbital data is not possible due to very low cloud-free images over the Antarctic, which prevents building a consistent surface reflectance time-series which covers all biological soil crusts growth season.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201006
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201006
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202220210596
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Academia Brasileira de Ciências
publisher.none.fl_str_mv Academia Brasileira de Ciências
dc.source.none.fl_str_mv Anais da Academia Brasileira de Ciências v.94 suppl.1 2022
reponame:Anais da Academia Brasileira de Ciências (Online)
instname:Academia Brasileira de Ciências (ABC)
instacron:ABC
instname_str Academia Brasileira de Ciências (ABC)
instacron_str ABC
institution ABC
reponame_str Anais da Academia Brasileira de Ciências (Online)
collection Anais da Academia Brasileira de Ciências (Online)
repository.name.fl_str_mv Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)
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