Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries

Detalhes bibliográficos
Autor(a) principal: MENDES JR,CLAUDIO W.
Data de Publicação: 2022
Outros Autores: ARIGONY NETO,JORGE, HILLEBRAND,FERNANDO L., DE FREITAS,MARCOS W.D., COSTI,JULIANA, 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=S0001-37652022000201103
Resumo: Abstract The classification of Synthetic Aperture Radar (SAR) images by knowledge-based algorithms with elevation and backscatter thresholds were used in several studies to detect the Wet Snow Radar Zone (WSZ) in the Antarctic Peninsula. To identify it more accurately based on its seasonal variations, this study proposed the additional use of a threshold in synthetic images, created by rationing summer and winter sigma linear images. In our algorithm we used the following thresholds to detect the WSZ in Envisat ASAR imageries, using the Radarsat Antarctic Map Digital Elevation Model as ancillary data: i) -25 dB < s0 < -14 dB; ii) slinear summer / slinear winter < 0.4; iii) elevation H < 1,200 m for northern tip and H < 800 m for southern tip of the Antarctic Peninsula. The classified images were post-processed by a focal majority 5 x 5 filter and superimposed by an image of rock outcrops derived from the Antarctic Digital Database. The ratio image threshold allowed discriminating the WSZ from the Dry Snow Radar Zone and radar shadows, as well as transitional areas between this glacier zone and the Frozen Percolation Radar Zone, which would be classified incorrectly if we used only elevation and backscatter thresholds.
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spelling Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageriesAntarctic PeninsulaEnvisat ASARSAR imagerysnowmeltWet Snow ZoneAbstract The classification of Synthetic Aperture Radar (SAR) images by knowledge-based algorithms with elevation and backscatter thresholds were used in several studies to detect the Wet Snow Radar Zone (WSZ) in the Antarctic Peninsula. To identify it more accurately based on its seasonal variations, this study proposed the additional use of a threshold in synthetic images, created by rationing summer and winter sigma linear images. In our algorithm we used the following thresholds to detect the WSZ in Envisat ASAR imageries, using the Radarsat Antarctic Map Digital Elevation Model as ancillary data: i) -25 dB < s0 < -14 dB; ii) slinear summer / slinear winter < 0.4; iii) elevation H < 1,200 m for northern tip and H < 800 m for southern tip of the Antarctic Peninsula. The classified images were post-processed by a focal majority 5 x 5 filter and superimposed by an image of rock outcrops derived from the Antarctic Digital Database. The ratio image threshold allowed discriminating the WSZ from the Dry Snow Radar Zone and radar shadows, as well as transitional areas between this glacier zone and the Frozen Percolation Radar Zone, which would be classified incorrectly if we used only elevation and backscatter thresholds.Academia Brasileira de Ciências2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201103Anais da Academia Brasileira de Ciências v.94 suppl.1 2022reponame:Anais da Academia Brasileira de Ciências (Online)instname:Academia Brasileira de Ciências (ABC)instacron:ABC10.1590/0001-3765202220210217info:eu-repo/semantics/openAccessMENDES JR,CLAUDIO W.ARIGONY NETO,JORGEHILLEBRAND,FERNANDO L.DE FREITAS,MARCOS W.D.COSTI,JULIANASIMÕES,JEFFERSON C.eng2022-03-15T00:00:00Zoai:scielo:S0001-37652022000201103Revistahttp://www.scielo.br/aabchttps://old.scielo.br/oai/scielo-oai.php||aabc@abc.org.br1678-26900001-3765opendoar:2022-03-15T00:00Anais da Academia Brasileira de Ciências (Online) - Academia Brasileira de Ciências (ABC)false
dc.title.none.fl_str_mv Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
title Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
spellingShingle Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
MENDES JR,CLAUDIO W.
Antarctic Peninsula
Envisat ASAR
SAR imagery
snowmelt
Wet Snow Zone
title_short Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
title_full Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
title_fullStr Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
title_full_unstemmed Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
title_sort Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
author MENDES JR,CLAUDIO W.
author_facet MENDES JR,CLAUDIO W.
ARIGONY NETO,JORGE
HILLEBRAND,FERNANDO L.
DE FREITAS,MARCOS W.D.
COSTI,JULIANA
SIMÕES,JEFFERSON C.
author_role author
author2 ARIGONY NETO,JORGE
HILLEBRAND,FERNANDO L.
DE FREITAS,MARCOS W.D.
COSTI,JULIANA
SIMÕES,JEFFERSON C.
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv MENDES JR,CLAUDIO W.
ARIGONY NETO,JORGE
HILLEBRAND,FERNANDO L.
DE FREITAS,MARCOS W.D.
COSTI,JULIANA
SIMÕES,JEFFERSON C.
dc.subject.por.fl_str_mv Antarctic Peninsula
Envisat ASAR
SAR imagery
snowmelt
Wet Snow Zone
topic Antarctic Peninsula
Envisat ASAR
SAR imagery
snowmelt
Wet Snow Zone
description Abstract The classification of Synthetic Aperture Radar (SAR) images by knowledge-based algorithms with elevation and backscatter thresholds were used in several studies to detect the Wet Snow Radar Zone (WSZ) in the Antarctic Peninsula. To identify it more accurately based on its seasonal variations, this study proposed the additional use of a threshold in synthetic images, created by rationing summer and winter sigma linear images. In our algorithm we used the following thresholds to detect the WSZ in Envisat ASAR imageries, using the Radarsat Antarctic Map Digital Elevation Model as ancillary data: i) -25 dB < s0 < -14 dB; ii) slinear summer / slinear winter < 0.4; iii) elevation H < 1,200 m for northern tip and H < 800 m for southern tip of the Antarctic Peninsula. The classified images were post-processed by a focal majority 5 x 5 filter and superimposed by an image of rock outcrops derived from the Antarctic Digital Database. The ratio image threshold allowed discriminating the WSZ from the Dry Snow Radar Zone and radar shadows, as well as transitional areas between this glacier zone and the Frozen Percolation Radar Zone, which would be classified incorrectly if we used only elevation and backscatter thresholds.
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
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201103
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652022000201103
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0001-3765202220210217
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)
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