Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach

Detalhes bibliográficos
Autor(a) principal: Arigony Neto, Jorge
Data de Publicação: 2006
Outros Autores: Saurer, Helmut, Jaña, Ricardo, Rau, Frank, Simões, Jefferson Cardia, Goßmann, Hermann
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FURG (RI FURG)
Texto Completo: http://repositorio.furg.br/handle/1/5586
Resumo: Ongoing climatic change on the Antarctic Peninsula is well documented in numerous scientific publications. Nevertheless, spatial and temporal distribution of glacier changes on the Antarctic Peninsula remain largely unknown. To analyse regional patterns and trends of changes in snow cover parameters on the Antarctic Peninsula north of 70° S, we propose a geostatistical approach based on the analysis of data derived by remote sensing methods. A time series of radar (ERS-1/2 SAR, Envisat ASAR and Radarsat SAR) and optical data (Landsat TM, Landsat ETM+ and Terra ASTER) enables the compilation of a multi-temporal database of glacier parameters for the last two decades. In this paper, we propose a method to facilitate the pre-processing and classification of remotely sensed data from several sources, and describe a sampling method used for selecting a representative set of glaciers for evaluation of classification algorithms. The so-called centreline approach facilitates pre-processing and classification of remote sensing data for monitoring glacier zones. In addition, the approach enables the integration of data from different sources, and mini-mizes the need of high resolution digital elevation models (DEM) for terrain correction.
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spelling Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approachGlacier monitoringAntarctic PeninsulaGlacier zonesMulti-temporalOngoing climatic change on the Antarctic Peninsula is well documented in numerous scientific publications. Nevertheless, spatial and temporal distribution of glacier changes on the Antarctic Peninsula remain largely unknown. To analyse regional patterns and trends of changes in snow cover parameters on the Antarctic Peninsula north of 70° S, we propose a geostatistical approach based on the analysis of data derived by remote sensing methods. A time series of radar (ERS-1/2 SAR, Envisat ASAR and Radarsat SAR) and optical data (Landsat TM, Landsat ETM+ and Terra ASTER) enables the compilation of a multi-temporal database of glacier parameters for the last two decades. In this paper, we propose a method to facilitate the pre-processing and classification of remotely sensed data from several sources, and describe a sampling method used for selecting a representative set of glaciers for evaluation of classification algorithms. The so-called centreline approach facilitates pre-processing and classification of remote sensing data for monitoring glacier zones. In addition, the approach enables the integration of data from different sources, and mini-mizes the need of high resolution digital elevation models (DEM) for terrain correction.2015-12-06T09:43:26Z2015-12-06T09:43:26Z2006info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfARIGONY NETO, Jorge et al. Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach. EARSeL eProceedings, Paris, v. 5, n. 1, p. 100-110, 2006. Disponível em: <http://las.physik.uni-oldenburg.de/eProceedings/vol05_1/05_1_arigony-neto1.pdf>. Acesso em: 04 dez. 2015.1729-3782http://repositorio.furg.br/handle/1/5586engArigony Neto, JorgeSaurer, HelmutJaña, RicardoRau, FrankSimões, Jefferson CardiaGoßmann, Hermanninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FURG (RI FURG)instname:Universidade Federal do Rio Grande (FURG)instacron:FURG2015-12-06T09:43:26Zoai:repositorio.furg.br:1/5586Repositório InstitucionalPUBhttps://repositorio.furg.br/oai/request || http://200.19.254.174/oai/requestopendoar:2015-12-06T09:43:26Repositório Institucional da FURG (RI FURG) - Universidade Federal do Rio Grande (FURG)false
dc.title.none.fl_str_mv Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
title Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
spellingShingle Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
Arigony Neto, Jorge
Glacier monitoring
Antarctic Peninsula
Glacier zones
Multi-temporal
title_short Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
title_full Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
title_fullStr Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
title_full_unstemmed Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
title_sort Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach
author Arigony Neto, Jorge
author_facet Arigony Neto, Jorge
Saurer, Helmut
Jaña, Ricardo
Rau, Frank
Simões, Jefferson Cardia
Goßmann, Hermann
author_role author
author2 Saurer, Helmut
Jaña, Ricardo
Rau, Frank
Simões, Jefferson Cardia
Goßmann, Hermann
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Arigony Neto, Jorge
Saurer, Helmut
Jaña, Ricardo
Rau, Frank
Simões, Jefferson Cardia
Goßmann, Hermann
dc.subject.por.fl_str_mv Glacier monitoring
Antarctic Peninsula
Glacier zones
Multi-temporal
topic Glacier monitoring
Antarctic Peninsula
Glacier zones
Multi-temporal
description Ongoing climatic change on the Antarctic Peninsula is well documented in numerous scientific publications. Nevertheless, spatial and temporal distribution of glacier changes on the Antarctic Peninsula remain largely unknown. To analyse regional patterns and trends of changes in snow cover parameters on the Antarctic Peninsula north of 70° S, we propose a geostatistical approach based on the analysis of data derived by remote sensing methods. A time series of radar (ERS-1/2 SAR, Envisat ASAR and Radarsat SAR) and optical data (Landsat TM, Landsat ETM+ and Terra ASTER) enables the compilation of a multi-temporal database of glacier parameters for the last two decades. In this paper, we propose a method to facilitate the pre-processing and classification of remotely sensed data from several sources, and describe a sampling method used for selecting a representative set of glaciers for evaluation of classification algorithms. The so-called centreline approach facilitates pre-processing and classification of remote sensing data for monitoring glacier zones. In addition, the approach enables the integration of data from different sources, and mini-mizes the need of high resolution digital elevation models (DEM) for terrain correction.
publishDate 2006
dc.date.none.fl_str_mv 2006
2015-12-06T09:43:26Z
2015-12-06T09:43:26Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv ARIGONY NETO, Jorge et al. Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach. EARSeL eProceedings, Paris, v. 5, n. 1, p. 100-110, 2006. Disponível em: <http://las.physik.uni-oldenburg.de/eProceedings/vol05_1/05_1_arigony-neto1.pdf>. Acesso em: 04 dez. 2015.
1729-3782
http://repositorio.furg.br/handle/1/5586
identifier_str_mv ARIGONY NETO, Jorge et al. Monitoring snow parameters on the Antarctic Peninsula using satellite data: a new methodological approach. EARSeL eProceedings, Paris, v. 5, n. 1, p. 100-110, 2006. Disponível em: <http://las.physik.uni-oldenburg.de/eProceedings/vol05_1/05_1_arigony-neto1.pdf>. Acesso em: 04 dez. 2015.
1729-3782
url http://repositorio.furg.br/handle/1/5586
dc.language.iso.fl_str_mv eng
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instname:Universidade Federal do Rio Grande (FURG)
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reponame_str Repositório Institucional da FURG (RI FURG)
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