Snowmelt retrieval algorithm for the Antarctic Peninsula using SAR imageries
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
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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Anais da Academia Brasileira de Ciências (Online) |
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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 |
format |
article |
status_str |
publishedVersion |
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) 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) |
repository.mail.fl_str_mv |
||aabc@abc.org.br |
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1754302871669571584 |