Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows

The freshwater flux from icebergs into the Southern Ocean plays an important role in the global climate through its impact on the deep-water formation. Large uncertainties exist in the ice volume transported by Southern Ocean icebergs due to the sparse spatial and temporal coverage of observations,...

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Published in:Remote Sensing
Main Authors: Zhenfu Guan, Xiao Cheng, Yan Liu, Teng Li, Baogang Zhang, Zhitong Yu
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/rs13030430
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spelling ftmdpi:oai:mdpi.com:/2072-4292/13/3/430/ 2023-08-20T04:02:27+02:00 Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows Zhenfu Guan Xiao Cheng Yan Liu Teng Li Baogang Zhang Zhitong Yu agris 2021-01-26 application/pdf https://doi.org/10.3390/rs13030430 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs13030430 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 13; Issue 3; Pages: 430 iceberg freeboard shadow height Antarctic Landsat-8 optical remote sensing Text 2021 ftmdpi https://doi.org/10.3390/rs13030430 2023-08-01T00:56:30Z The freshwater flux from icebergs into the Southern Ocean plays an important role in the global climate through its impact on the deep-water formation. Large uncertainties exist in the ice volume transported by Southern Ocean icebergs due to the sparse spatial and temporal coverage of observations, especially observations of ice thickness. The iceberg freeboard is a critical geometric parameter for measuring the thickness of an iceberg and then estimating its volume. This study developed a new, highly efficient shadow-height method to precisely measure the freeboard of various icebergs surrounded by sea ice using Landsat-8 Operational Land Imager 15-m bi-temporal panchromatic image shadows at low-solar-elevation angles. We evaluated and validated shadow length precision according to bi-temporal measurements and comparison with the measurements from the unmanned aerial vehicle. We determined freeboard precision according to shadow length precision and solar elevation angle. In our case study area, 4832 available freeboard measuring points with shadow length precision better than 2 pixels covered 376 icebergs with sizes ranging from 0.002 to 0.7 km² and with freeboard ranging from 2.3 to 83.4 m. At the solar elevation angles of 5.2°, the freeboard precision of 64.1% data could reach 1 m and 86.9% could reach 2 m. Our proposed method effectively filled in the data gap of existing freeboard measurement methods. Text Antarc* Antarctic Iceberg* Sea ice Southern Ocean MDPI Open Access Publishing Antarctic Southern Ocean Remote Sensing 13 3 430
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic iceberg
freeboard
shadow height
Antarctic
Landsat-8
optical remote sensing
spellingShingle iceberg
freeboard
shadow height
Antarctic
Landsat-8
optical remote sensing
Zhenfu Guan
Xiao Cheng
Yan Liu
Teng Li
Baogang Zhang
Zhitong Yu
Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
topic_facet iceberg
freeboard
shadow height
Antarctic
Landsat-8
optical remote sensing
description The freshwater flux from icebergs into the Southern Ocean plays an important role in the global climate through its impact on the deep-water formation. Large uncertainties exist in the ice volume transported by Southern Ocean icebergs due to the sparse spatial and temporal coverage of observations, especially observations of ice thickness. The iceberg freeboard is a critical geometric parameter for measuring the thickness of an iceberg and then estimating its volume. This study developed a new, highly efficient shadow-height method to precisely measure the freeboard of various icebergs surrounded by sea ice using Landsat-8 Operational Land Imager 15-m bi-temporal panchromatic image shadows at low-solar-elevation angles. We evaluated and validated shadow length precision according to bi-temporal measurements and comparison with the measurements from the unmanned aerial vehicle. We determined freeboard precision according to shadow length precision and solar elevation angle. In our case study area, 4832 available freeboard measuring points with shadow length precision better than 2 pixels covered 376 icebergs with sizes ranging from 0.002 to 0.7 km² and with freeboard ranging from 2.3 to 83.4 m. At the solar elevation angles of 5.2°, the freeboard precision of 64.1% data could reach 1 m and 86.9% could reach 2 m. Our proposed method effectively filled in the data gap of existing freeboard measurement methods.
format Text
author Zhenfu Guan
Xiao Cheng
Yan Liu
Teng Li
Baogang Zhang
Zhitong Yu
author_facet Zhenfu Guan
Xiao Cheng
Yan Liu
Teng Li
Baogang Zhang
Zhitong Yu
author_sort Zhenfu Guan
title Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
title_short Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
title_full Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
title_fullStr Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
title_full_unstemmed Effectively Extracting Iceberg Freeboard Using Bi-Temporal Landsat-8 Panchromatic Image Shadows
title_sort effectively extracting iceberg freeboard using bi-temporal landsat-8 panchromatic image shadows
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/rs13030430
op_coverage agris
geographic Antarctic
Southern Ocean
geographic_facet Antarctic
Southern Ocean
genre Antarc*
Antarctic
Iceberg*
Sea ice
Southern Ocean
genre_facet Antarc*
Antarctic
Iceberg*
Sea ice
Southern Ocean
op_source Remote Sensing; Volume 13; Issue 3; Pages: 430
op_relation https://dx.doi.org/10.3390/rs13030430
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs13030430
container_title Remote Sensing
container_volume 13
container_issue 3
container_start_page 430
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