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 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 coincides with depth contours and indicates a westward drift of the bergs throughout the whole region.

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Cite this as

Mazur, Aleksandra Katarzyna, Wåhlin, Anna, Krężel, Adam (2016). Dataset: Icebergs in the Amundsen Sea (Antarctica) determined from ENVISAT ASAR WSM data using object-based image analysis approach, link to ESRI GDB files. https://doi.org/10.1594/PANGAEA.856847

DOI retrieved: 2016

Additional Info

Field Value
Imported on November 29, 2024
Last update November 29, 2024
License CC-BY-3.0
Source https://doi.org/10.1594/PANGAEA.856847
Author Mazur, Aleksandra Katarzyna
Given Name Aleksandra Katarzyna
Family Name Mazur
More Authors
Wåhlin, Anna
Krężel, Adam
Source Creation 2016
Publication Year 2016
Subject Areas
Name: Ecology

Name: HumanDimensions

Name: LandSurface

Related Identifiers
Title: An object-based SAR image iceberg detection algorithm applied to the Amundsen Sea
Identifier: https://doi.org/10.1016/j.rse.2016.11.013
Type: DOI
Relation: IsSupplementTo
Year: 2017
Source: Remote Sensing of Environment
Authors: Mazur Aleksandra Katarzyna , Wåhlin Anna , Krężel Adam .