Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ...
An object-based method for automatic iceberg detection from Advanced Synthetic Aperture Radar (ASAR) images has been developed and applied in the Amundsen Sea, Antarctica. The automatic identification is based on brightness and spatial parameters of the ASAR images at five scale levels, and was veri...
Main Authors: | , , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
PANGAEA
2016
|
Subjects: | |
Online Access: | https://dx.doi.org/10.1594/pangaea.856847 https://doi.pangaea.de/10.1594/PANGAEA.856847 |
id |
ftdatacite:10.1594/pangaea.856847 |
---|---|
record_format |
openpolar |
spelling |
ftdatacite:10.1594/pangaea.856847 2024-09-15T17:38:59+00:00 Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... Mazur, Aleksandra Katarzyna Wåhlin, Anna Krężel, Adam 2016 application/zip https://dx.doi.org/10.1594/pangaea.856847 https://doi.pangaea.de/10.1594/PANGAEA.856847 en eng PANGAEA https://dx.doi.org/10.1016/j.rse.2016.11.013 Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 dataset Supplementary Dataset Dataset 2016 ftdatacite https://doi.org/10.1594/pangaea.85684710.1016/j.rse.2016.11.013 2024-08-01T10:57:37Z An object-based method for automatic iceberg detection from Advanced Synthetic Aperture Radar (ASAR) images has been developed and applied in the Amundsen Sea, Antarctica. The automatic identification is based on brightness and spatial parameters of the ASAR images at five scale levels, and was verified with manual classification in four areas chosen to represent varying environmental conditions. The presented algorithm works comparatively well with images of the ocean in freezing temperatures and strong wind conditions, common in the Amundsen Sea. The detection rate was 96.2% which corresponds to 93.2% of the icebergs area, for all seasons. The algorithm generated 3.8% errors in the form of 'misses' and 7.0% of 'false alarms', mainly caused by the presence of ice floes.The method was applied on 432 radar images acquired in 2011 under different meteorological, oceanographic and sea ice conditions. As an output a map showing the probability of finding icebergs has been created. It shows that high probability ... : Format of GDB files:1) Longitude of a center (X_deg)2) Latitude of a centre (Y_deg)3) Area in km**2 (Area_km2)4) Perimeter in km (Perim_km)Projection: Lambert Azimuthal Equal Area: Datum: WGS-84; central_meridian = -115; latitude_of_origin = -90; false_easting = 0.0; false_northing = 0.0 ... Dataset Amundsen Sea Antarc* Antarctica Sea ice DataCite |
institution |
Open Polar |
collection |
DataCite |
op_collection_id |
ftdatacite |
language |
English |
description |
An object-based method for automatic iceberg detection from Advanced Synthetic Aperture Radar (ASAR) images has been developed and applied in the Amundsen Sea, Antarctica. The automatic identification is based on brightness and spatial parameters of the ASAR images at five scale levels, and was verified with manual classification in four areas chosen to represent varying environmental conditions. The presented algorithm works comparatively well with images of the ocean in freezing temperatures and strong wind conditions, common in the Amundsen Sea. The detection rate was 96.2% which corresponds to 93.2% of the icebergs area, for all seasons. The algorithm generated 3.8% errors in the form of 'misses' and 7.0% of 'false alarms', mainly caused by the presence of ice floes.The method was applied on 432 radar images acquired in 2011 under different meteorological, oceanographic and sea ice conditions. As an output a map showing the probability of finding icebergs has been created. It shows that high probability ... : Format of GDB files:1) Longitude of a center (X_deg)2) Latitude of a centre (Y_deg)3) Area in km**2 (Area_km2)4) Perimeter in km (Perim_km)Projection: Lambert Azimuthal Equal Area: Datum: WGS-84; central_meridian = -115; latitude_of_origin = -90; false_easting = 0.0; false_northing = 0.0 ... |
format |
Dataset |
author |
Mazur, Aleksandra Katarzyna Wåhlin, Anna Krężel, Adam |
spellingShingle |
Mazur, Aleksandra Katarzyna Wåhlin, Anna Krężel, Adam Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
author_facet |
Mazur, Aleksandra Katarzyna Wåhlin, Anna Krężel, Adam |
author_sort |
Mazur, Aleksandra Katarzyna |
title |
Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
title_short |
Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
title_full |
Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
title_fullStr |
Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
title_full_unstemmed |
Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files ... |
title_sort |
icebergs in the amundsen sea (antarctica) determined from envisat asar wsm data using object-based image analysis approach, link to esri gdb files ... |
publisher |
PANGAEA |
publishDate |
2016 |
url |
https://dx.doi.org/10.1594/pangaea.856847 https://doi.pangaea.de/10.1594/PANGAEA.856847 |
genre |
Amundsen Sea Antarc* Antarctica Sea ice |
genre_facet |
Amundsen Sea Antarc* Antarctica Sea ice |
op_relation |
https://dx.doi.org/10.1016/j.rse.2016.11.013 |
op_rights |
Creative Commons Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/legalcode cc-by-3.0 |
op_doi |
https://doi.org/10.1594/pangaea.85684710.1016/j.rse.2016.11.013 |
_version_ |
1810476618094739456 |