Next Article in Journal
The ASI Integrated Sounder-SAR System Operating in the UHF-VHF Bands: First Results of the 2018 Helicopter-Borne Morocco Desert Campaign
Previous Article in Journal
Consecutive Dual-Vortex Interactions between Quadruple Typhoons Noru, Kulap, Nesat and Haitang during the 2017 North Pacific Typhoon Season
Previous Article in Special Issue
Spatio-Temporal Analysis of Ice Sheet Snowmelt in Antarctica and Greenland Using Microwave Radiometer Data
Open AccessArticle

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

1
State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
2
School of Geospatial Engineering and Science, Sun Yat-Sen University, Guangzhou 510275, China
3
University Corporation for Polar Research, Beijing 100875, China
4
Science and Technology Branch, Environment Canada, Toronto, ON M3H5T4, Canada
5
Geospatial Science, Applications & Technology Center, Department of Geography, Texas A&M University, 3147 TAMU, College Station, TX 77843-3147, USA
6
Australian Antarctica Division and Antarctica Climate and Ecosystems Cooperative Research Centre, University of Tasmania, Hobart, TAS 7001, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1844; https://doi.org/10.3390/rs11161844
Received: 30 May 2019 / Revised: 28 July 2019 / Accepted: 1 August 2019 / Published: 8 August 2019
  |  
PDF [3580 KB, uploaded 8 August 2019]
  |  

Abstract

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. View Full-Text
Keywords: Antarctic coastline; coastline extraction; remote sensing; Canny algorithms; ice shelves Antarctic coastline; coastline extraction; remote sensing; Canny algorithms; ice shelves
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Yu, Y.; Zhang, Z.; Shokr, M.; Hui, F.; Cheng, X.; Chi, Z.; Heil, P.; Chen, Z. Automatically Extracted Antarctic Coastline Using Remotely-Sensed Data: An Update. Remote Sens. 2019, 11, 1844.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top