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Automatic extraction of the Antarctic Ice Cliff Coastline by combining threshold segmentation and edge detection

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

  • Email：wangcaihong@mail.bnu.edu.cn
  • Introduction：王彩虹，研究方向为极地遥感。E-mail： wangcaihong@mail.bnu.edu.cn
WANG Caihong1,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

  • Email：liuyan2013@bnu.edu.cn
  • Introduction：刘岩，研究方向为极地遥感。E-mail： liuyan2013@bnu.edu.cn
LIU Yan1*,  
  • Affiliation：

    School of Geomatics Science and Technology, Sun Yat-sen University, Zhuhai 519082, China

    Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China

    University Corporation for Polar Research (UCPR), Beijing 100875, China

CHENG Xiao234,  
  • Affiliation：

    College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao 266580, China

SUN Genyun5,  
  • Affiliation：

    State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHANG Baogang1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing and Digital Earth, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

WENG Zhilong1,  
  • Affiliation：

    School of Geomatics Science and Technology, Sun Yat-sen University, Zhuhai 519082, China

GUAN Zhenfu2

Resümee

The Antarctic coastline is highly sensitive to global environmental change and is undergoing rapid transformation because of global warming. The retreat of ice shelves has led to increased direct exposure of glaciers to the ocean, forming iceclifftype coastlines that terminate at grounded glaciers. These coastlines are key zones for studying ice sheet instability, and accurate monitoring of their changes is crucial for predicting future sea level rise. However, compared with iceshelf-type coastlines, ice cliff coastlines, with their complex and subtle variations, present considerable challenges, and high-precision extraction algorithms still require further development. This study proposes a dual-boundary fusion algorithm on the basis of the topological closure relationship between threshold- and edge-derived boundaries, enabling the high-precision extraction of continuous coastlines. An automatic error self-assessment method on the basis of different boundary connectivity features is introduced. With typical regions on the Antarctic Peninsula as examples, Sentinel-1 SAR data with 15 m resolution are used to extract ice cliff coastlines. The performance of the dual-boundary fusion algorithm is validated through full-sample assessment across three types of ice cliff coastline interfaces, namely, ice cliff-seawater (sea ice), ice cliff shadow-seawater (sea ice), and ice cliff-mélange. Results show that the proposed algorithm can accurately and automatically extract the first two types of ice cliff coastlines, which account for 92% of the total ice cliff coastline length in the study area. For the ice cliff-sea water (sea ice) interface, the mean error is 0.31 ± 1.13 pixels (at 15 m resolution), with 85.8% of the coastline having zero-pixel error. For the ice cliff shadow-seawater (sea ice) interface, the mean error is 0.56 ± 1.55 pixels, and 74.9% of the coastline has zero-pixel error. By contrast, for the ice cliff-mélange interface, 83.8% of the coastline has an error exceeding 20 pixels in an unsupervised setting; however, the algorithm can automatically identify these large low-accuracy regions for subsequent refinement. The dual-boundary fusion algorithm effectively addresses the accuracy limitations of threshold segmentation and the noise sensitivity of edge detection without requiring training samples. It is computationally efficient and suitable for long-term, high-precision monitoring of most ice cliff coastlines across Antarctica.

Schlüsselwort

Antarctic icecliff coastline;automatic coastline extraction;dual-boundary fusion algorithm;threshold segmentation;edge detection;Sentinel-1 SAR GRD data

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