Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update

The temporal and spatial variability of the Antarctic coastline is a clear indicator of change in extent and mass balance of ice sheets and shelves. In this study, the Canny edge detector was utilized to automatically extract high-resolution information of the Antarctic coastline for 2005, 2010, and...

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Published in:Remote Sensing
Main Authors: Yining Yu, Zhilun Zhang, Mohammed Shokr, Fengming Hui, Xiao Cheng, Zhaohui Chi, Petra Heil, Zhuoqi Chen
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2019
Subjects:
Online Access:https://doi.org/10.3390/rs11161844
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spelling ftmdpi:oai:mdpi.com:/2072-4292/11/16/1844/ 2023-08-20T03:59:55+02:00 Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update Yining Yu Zhilun Zhang Mohammed Shokr Fengming Hui Xiao Cheng Zhaohui Chi Petra Heil Zhuoqi Chen agris 2019-08-08 application/pdf https://doi.org/10.3390/rs11161844 EN eng Multidisciplinary Digital Publishing Institute Environmental Remote Sensing https://dx.doi.org/10.3390/rs11161844 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 11; Issue 16; Pages: 1844 Antarctic coastline coastline extraction remote sensing Canny algorithms ice shelves Text 2019 ftmdpi https://doi.org/10.3390/rs11161844 2023-07-31T22:30:12Z The temporal and spatial variability of the Antarctic coastline is a clear indicator of change in extent and mass balance of ice sheets and shelves. In this study, the Canny edge detector was utilized to automatically extract high-resolution information of the Antarctic coastline for 2005, 2010, and 2017, based on optical and microwave satellite data. In order to improve the accuracy of the extracted coastlines, we developed the Canny algorithm by automatically calculating the local low and high thresholds via the intensity histogram of each image to derive thresholds to distinguish ice sheet from water. A visual comparison between extracted coastlines and mosaics from remote sensing images shows good agreement. In addition, comparing manually extracted coastline, based on prior knowledge, the accuracy of planimetric position of automated extraction is better than two pixels of Landsat images (30 m resolution). Our study shows that the percentage of deviation (<100 m) between automatically and manually extracted coastlines in nine areas around the Antarctica is 92.32%, and the mean deviation is 38.15 m. Our results reveal that the length of coastline around Antarctica increased from 35,114 km in 2005 to 35,281 km in 2010, and again to 35,672 km in 2017. Meanwhile, the total area of the Antarctica varied slightly from 1.3618 × 107 km2 (2005) to 1.3537 × 107 km2 (2010) and 1.3657 × 107 km2 (2017). We have found that the decline of the Antarctic area between 2005 and 2010 is related to the breakup of some individual ice shelves, mainly in the Antarctic Peninsula and off East Antarctica. We present a detailed analysis of the temporal and spatial change of coastline and area change for the six ice shelves that exhibited the largest change in the last decade. The largest area change (a loss of 4836 km2) occurred at the Wilkins Ice Shelf between 2005 and 2010. Text Antarc* Antarctic Antarctic Peninsula Antarctica East Antarctica Ice Sheet Ice Shelf Ice Shelves Wilkins Ice Shelf MDPI Open Access Publishing Antarctic The Antarctic Antarctic Peninsula East Antarctica Wilkins ENVELOPE(59.326,59.326,-67.248,-67.248) Wilkins Ice Shelf ENVELOPE(-72.500,-72.500,-70.416,-70.416) Remote Sensing 11 16 1844
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic Antarctic coastline
coastline extraction
remote sensing
Canny algorithms
ice shelves
spellingShingle Antarctic coastline
coastline extraction
remote sensing
Canny algorithms
ice shelves
Yining Yu
Zhilun Zhang
Mohammed Shokr
Fengming Hui
Xiao Cheng
Zhaohui Chi
Petra Heil
Zhuoqi Chen
Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
topic_facet Antarctic coastline
coastline extraction
remote sensing
Canny algorithms
ice shelves
description The temporal and spatial variability of the Antarctic coastline is a clear indicator of change in extent and mass balance of ice sheets and shelves. In this study, the Canny edge detector was utilized to automatically extract high-resolution information of the Antarctic coastline for 2005, 2010, and 2017, based on optical and microwave satellite data. In order to improve the accuracy of the extracted coastlines, we developed the Canny algorithm by automatically calculating the local low and high thresholds via the intensity histogram of each image to derive thresholds to distinguish ice sheet from water. A visual comparison between extracted coastlines and mosaics from remote sensing images shows good agreement. In addition, comparing manually extracted coastline, based on prior knowledge, the accuracy of planimetric position of automated extraction is better than two pixels of Landsat images (30 m resolution). Our study shows that the percentage of deviation (<100 m) between automatically and manually extracted coastlines in nine areas around the Antarctica is 92.32%, and the mean deviation is 38.15 m. Our results reveal that the length of coastline around Antarctica increased from 35,114 km in 2005 to 35,281 km in 2010, and again to 35,672 km in 2017. Meanwhile, the total area of the Antarctica varied slightly from 1.3618 × 107 km2 (2005) to 1.3537 × 107 km2 (2010) and 1.3657 × 107 km2 (2017). We have found that the decline of the Antarctic area between 2005 and 2010 is related to the breakup of some individual ice shelves, mainly in the Antarctic Peninsula and off East Antarctica. We present a detailed analysis of the temporal and spatial change of coastline and area change for the six ice shelves that exhibited the largest change in the last decade. The largest area change (a loss of 4836 km2) occurred at the Wilkins Ice Shelf between 2005 and 2010.
format Text
author Yining Yu
Zhilun Zhang
Mohammed Shokr
Fengming Hui
Xiao Cheng
Zhaohui Chi
Petra Heil
Zhuoqi Chen
author_facet Yining Yu
Zhilun Zhang
Mohammed Shokr
Fengming Hui
Xiao Cheng
Zhaohui Chi
Petra Heil
Zhuoqi Chen
author_sort Yining Yu
title Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
title_short Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
title_full Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
title_fullStr Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
title_full_unstemmed Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update
title_sort automatically extracted antarctic coastline using remotely-sensed data: an update
publisher Multidisciplinary Digital Publishing Institute
publishDate 2019
url https://doi.org/10.3390/rs11161844
op_coverage agris
long_lat ENVELOPE(59.326,59.326,-67.248,-67.248)
ENVELOPE(-72.500,-72.500,-70.416,-70.416)
geographic Antarctic
The Antarctic
Antarctic Peninsula
East Antarctica
Wilkins
Wilkins Ice Shelf
geographic_facet Antarctic
The Antarctic
Antarctic Peninsula
East Antarctica
Wilkins
Wilkins Ice Shelf
genre Antarc*
Antarctic
Antarctic Peninsula
Antarctica
East Antarctica
Ice Sheet
Ice Shelf
Ice Shelves
Wilkins Ice Shelf
genre_facet Antarc*
Antarctic
Antarctic Peninsula
Antarctica
East Antarctica
Ice Sheet
Ice Shelf
Ice Shelves
Wilkins Ice Shelf
op_source Remote Sensing; Volume 11; Issue 16; Pages: 1844
op_relation Environmental Remote Sensing
https://dx.doi.org/10.3390/rs11161844
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/rs11161844
container_title Remote Sensing
container_volume 11
container_issue 16
container_start_page 1844
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