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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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 |
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1844 |
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1774716090980499456 |