The role of lake size and local phenomena for monitoring ground-fast lake ice

In this study, we assess the effect of the lake size on the accuracy of a threshold-based classification of ground-fast and floating lake ice from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. For that purpose, two new methods (flood-fill and watershed method) are introduced and the results bet...

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Published in:International Journal of Remote Sensing
Main Authors: Pointner, Georg, Bartsch, Annett, Forbes, Bruce C., Kumpula, Timo
Format: Text
Language:English
Published: Taylor & Francis 2018
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376958/
https://doi.org/10.1080/01431161.2018.1519281
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spelling ftpubmed:oai:pubmedcentral.nih.gov:6376958 2023-05-15T18:45:33+02:00 The role of lake size and local phenomena for monitoring ground-fast lake ice Pointner, Georg Bartsch, Annett Forbes, Bruce C. Kumpula, Timo 2018-09-26 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376958/ https://doi.org/10.1080/01431161.2018.1519281 en eng Taylor & Francis http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376958/ http://dx.doi.org/10.1080/01431161.2018.1519281 © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. CC-BY Article Text 2018 ftpubmed https://doi.org/10.1080/01431161.2018.1519281 2019-03-03T01:27:32Z In this study, we assess the effect of the lake size on the accuracy of a threshold-based classification of ground-fast and floating lake ice from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. For that purpose, two new methods (flood-fill and watershed method) are introduced and the results between the three classification approaches are compared regarding different lake size classes for a study area covering most of the Yamal Peninsula in Western Siberia. The focus is on April, the stage of maximum lake ice thickness, for the years 2016 and 2017. The results indicate that the largest lakes are likely most prone to errors by the threshold classification. The newly introduced methods seem to improve classification results. The results also show differences in fractions of ground-fast lake ice between 2016 and 2017, which might reflect differences in temperatures between the winters with severe impact on wildlife and freshwater fish resources in the region. Patterns of low backscatter responsible for the classification errors in the centre of the lakes were investigated and compared to the optical Sentinel-2 imagery of late-winter. Strong similarities between some patterns in the optical and SAR data were identified. They might be zones of thin ice, but further research is required for clarification of this phenomenon and its causes. Text Yamal Peninsula Siberia PubMed Central (PMC) Fast Lake ENVELOPE(-108.251,-108.251,59.983,59.983) Yamal Peninsula ENVELOPE(69.873,69.873,70.816,70.816) International Journal of Remote Sensing 40 3 832 858
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
spellingShingle Article
Pointner, Georg
Bartsch, Annett
Forbes, Bruce C.
Kumpula, Timo
The role of lake size and local phenomena for monitoring ground-fast lake ice
topic_facet Article
description In this study, we assess the effect of the lake size on the accuracy of a threshold-based classification of ground-fast and floating lake ice from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. For that purpose, two new methods (flood-fill and watershed method) are introduced and the results between the three classification approaches are compared regarding different lake size classes for a study area covering most of the Yamal Peninsula in Western Siberia. The focus is on April, the stage of maximum lake ice thickness, for the years 2016 and 2017. The results indicate that the largest lakes are likely most prone to errors by the threshold classification. The newly introduced methods seem to improve classification results. The results also show differences in fractions of ground-fast lake ice between 2016 and 2017, which might reflect differences in temperatures between the winters with severe impact on wildlife and freshwater fish resources in the region. Patterns of low backscatter responsible for the classification errors in the centre of the lakes were investigated and compared to the optical Sentinel-2 imagery of late-winter. Strong similarities between some patterns in the optical and SAR data were identified. They might be zones of thin ice, but further research is required for clarification of this phenomenon and its causes.
format Text
author Pointner, Georg
Bartsch, Annett
Forbes, Bruce C.
Kumpula, Timo
author_facet Pointner, Georg
Bartsch, Annett
Forbes, Bruce C.
Kumpula, Timo
author_sort Pointner, Georg
title The role of lake size and local phenomena for monitoring ground-fast lake ice
title_short The role of lake size and local phenomena for monitoring ground-fast lake ice
title_full The role of lake size and local phenomena for monitoring ground-fast lake ice
title_fullStr The role of lake size and local phenomena for monitoring ground-fast lake ice
title_full_unstemmed The role of lake size and local phenomena for monitoring ground-fast lake ice
title_sort role of lake size and local phenomena for monitoring ground-fast lake ice
publisher Taylor & Francis
publishDate 2018
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376958/
https://doi.org/10.1080/01431161.2018.1519281
long_lat ENVELOPE(-108.251,-108.251,59.983,59.983)
ENVELOPE(69.873,69.873,70.816,70.816)
geographic Fast Lake
Yamal Peninsula
geographic_facet Fast Lake
Yamal Peninsula
genre Yamal Peninsula
Siberia
genre_facet Yamal Peninsula
Siberia
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6376958/
http://dx.doi.org/10.1080/01431161.2018.1519281
op_rights © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
http://creativecommons.org/licenses/by/4.0/
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
op_rightsnorm CC-BY
op_doi https://doi.org/10.1080/01431161.2018.1519281
container_title International Journal of Remote Sensing
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