Mapping of Moist Snow and Percolation Zones Through Sentinel-2
The purpose of this work consists of an application of remote sensing indices such as NDSI and NDSW and geoprocessing analyzes to map an occurrence of water, percolation and moist snow zones, as well as an identification of the characteristic altitudes of each snow zone mapped in the Dundee Island l...
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Universidade Federal do Rio de Janeiro
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Online Access: | http://www.anuario.igeo.ufrj.br/2018_03/2018_3_96_103.pdf https://doi.org/10.11137/2018_3_96_103 |
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fttriple:oai:gotriple.eu:oai:doaj.org/article:5e3735780c334681bc63501b9e14394b 2023-05-15T13:45:15+02:00 Mapping of Moist Snow and Percolation Zones Through Sentinel-2 Fernando Luis Hillebrand Cristiano Niederauer da Rosa Ulisses Franz Bremer 2019-03-01 http://www.anuario.igeo.ufrj.br/2018_03/2018_3_96_103.pdf https://doi.org/10.11137/2018_3_96_103 en eng Universidade Federal do Rio de Janeiro 0101-9759 1982-3908 http://www.anuario.igeo.ufrj.br/2018_03/2018_3_96_103.pdf http://dx.doi.org/10.11137/2018_3_96_103 undefined Anuário do Instituto de Geociências, Vol 41, Iss 3, Pp 96-103 (2019) NDSI NDWS Moist snow Percolation snow Sentinel-2 geo manag Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2019 fttriple https://doi.org/10.11137/2018_3_96_103 2023-01-22T18:10:07Z The purpose of this work consists of an application of remote sensing indices such as NDSI and NDSW and geoprocessing analyzes to map an occurrence of water, percolation and moist snow zones, as well as an identification of the characteristic altitudes of each snow zone mapped in the Dundee Island located on the Antarctic Peninsula. For this, a Sentinel-2 image representative of an ablation period corresponding to the end of summer of 2016 was used. As a result an interaction between the NDSI and NDSW indexes allowed a distinction and delimitation of the different zones of snow. As geoprocessing analyzes that involved an overlapping of the land cover classification from the indices, with the altimetric data from the Digital Elevation Model ASTER GDEM, allowed an identification of some bands altimetry characteristic of each zoning. Data base analysis was identified with 17.87% of the total area of the island for the class of moist snow and 81.15% as zone of snow in percolation. However, these results prove the effectiveness of the methodology used based on images of the MSI sensor of the Sentinel-2 satellite in the mapping of the several snow areas in the study area, bringing together geoprocessing tools. Article in Journal/Newspaper Antarc* Antarctic Antarctic Peninsula Dundee Island Unknown Antarctic Antarctic Peninsula Dundee ENVELOPE(-55.966,-55.966,-63.483,-63.483) Dundee Island ENVELOPE(-55.967,-55.967,-63.483,-63.483) The Antarctic The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) Anuário do Instituto de Geociências - UFRJ 41 3 96 103 |
institution |
Open Polar |
collection |
Unknown |
op_collection_id |
fttriple |
language |
English |
topic |
NDSI NDWS Moist snow Percolation snow Sentinel-2 geo manag |
spellingShingle |
NDSI NDWS Moist snow Percolation snow Sentinel-2 geo manag Fernando Luis Hillebrand Cristiano Niederauer da Rosa Ulisses Franz Bremer Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
topic_facet |
NDSI NDWS Moist snow Percolation snow Sentinel-2 geo manag |
description |
The purpose of this work consists of an application of remote sensing indices such as NDSI and NDSW and geoprocessing analyzes to map an occurrence of water, percolation and moist snow zones, as well as an identification of the characteristic altitudes of each snow zone mapped in the Dundee Island located on the Antarctic Peninsula. For this, a Sentinel-2 image representative of an ablation period corresponding to the end of summer of 2016 was used. As a result an interaction between the NDSI and NDSW indexes allowed a distinction and delimitation of the different zones of snow. As geoprocessing analyzes that involved an overlapping of the land cover classification from the indices, with the altimetric data from the Digital Elevation Model ASTER GDEM, allowed an identification of some bands altimetry characteristic of each zoning. Data base analysis was identified with 17.87% of the total area of the island for the class of moist snow and 81.15% as zone of snow in percolation. However, these results prove the effectiveness of the methodology used based on images of the MSI sensor of the Sentinel-2 satellite in the mapping of the several snow areas in the study area, bringing together geoprocessing tools. |
format |
Article in Journal/Newspaper |
author |
Fernando Luis Hillebrand Cristiano Niederauer da Rosa Ulisses Franz Bremer |
author_facet |
Fernando Luis Hillebrand Cristiano Niederauer da Rosa Ulisses Franz Bremer |
author_sort |
Fernando Luis Hillebrand |
title |
Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
title_short |
Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
title_full |
Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
title_fullStr |
Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
title_full_unstemmed |
Mapping of Moist Snow and Percolation Zones Through Sentinel-2 |
title_sort |
mapping of moist snow and percolation zones through sentinel-2 |
publisher |
Universidade Federal do Rio de Janeiro |
publishDate |
2019 |
url |
http://www.anuario.igeo.ufrj.br/2018_03/2018_3_96_103.pdf https://doi.org/10.11137/2018_3_96_103 |
long_lat |
ENVELOPE(-55.966,-55.966,-63.483,-63.483) ENVELOPE(-55.967,-55.967,-63.483,-63.483) ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
Antarctic Antarctic Peninsula Dundee Dundee Island The Antarctic The Sentinel |
geographic_facet |
Antarctic Antarctic Peninsula Dundee Dundee Island The Antarctic The Sentinel |
genre |
Antarc* Antarctic Antarctic Peninsula Dundee Island |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Dundee Island |
op_source |
Anuário do Instituto de Geociências, Vol 41, Iss 3, Pp 96-103 (2019) |
op_relation |
0101-9759 1982-3908 http://www.anuario.igeo.ufrj.br/2018_03/2018_3_96_103.pdf http://dx.doi.org/10.11137/2018_3_96_103 |
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op_doi |
https://doi.org/10.11137/2018_3_96_103 |
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Anuário do Instituto de Geociências - UFRJ |
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41 |
container_issue |
3 |
container_start_page |
96 |
op_container_end_page |
103 |
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