气候变化领域集成服务门户(CCPortal): Calving front machine (CALFIN): Glacial termini dataset and automated deep learning extraction method for Greenland, 1972-2019

CCPortal

DOI	10.5194/tc-15-1663-2021
	Calving front machine (CALFIN): Glacial termini dataset and automated deep learning extraction method for Greenland, 1972-2019
	Cheng D.; Hayes W.; Larour E.; Mohajerani Y.; Wood M.; Velicogna I.; Rignot E.
发表日期	2021
ISSN	19940416
起始页码	1663
结束页码	1675
卷号	15 期号:3
英文摘要	Sea level contributions from the Greenland Ice Sheet are influenced by the rapid changes in glacial terminus positions. The documentation of these evolving calving front positions, for which satellite imagery forms the basis, is therefore important. However, the manual delineation of these calving fronts is time consuming, which limits the availability of these data across a wide spatial and temporal range. Automated methods face challenges that include the handling of clouds, illumination differences, sea ice mélange, and Landsat 7 scan line corrector errors. To address these needs, we develop the Calving Front Machine (CALFIN), an automated method for extracting calving fronts from satellite images of marine-terminating glaciers, using neural networks. The results are often indistinguishable from manually curated fronts, deviating by on average 86.76 ± 1.43 m from the measured front. Landsat imagery from 1972 to 2019 is used to generate 22 678 calving front lines across 66 Greenlandic glaciers. This improves on the state of the art in terms of the spatiotemporal coverage and accuracy of its outputs and is validated through a comprehensive intercomparison with existing studies. The current implementation offers a new opportunity to explore subseasonal and regional trends on the extent of Greenland's margins and supplies new constraints for simulations of the evolution of the mass balance of the Greenland Ice Sheet and its contributions to future sea level rise. © 2019 EDP Sciences. All rights reserved.
英文关键词	automation; data set; extraction method; machinery; mass balance; model validation; satellite imagery; sea ice; sea level; Arctic; Greenland; Greenland Ice Sheet
语种	英语
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/202289
作者单位	University of California at Irvine, Irvine, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; eScience Institute, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, United States
推荐引用方式 GB/T 7714	Cheng D.,Hayes W.,Larour E.,et al. Calving front machine (CALFIN): Glacial termini dataset and automated deep learning extraction method for Greenland, 1972-2019[J],2021,15(3).
APA	Cheng D..,Hayes W..,Larour E..,Mohajerani Y..,Wood M..,...&Rignot E..(2021).Calving front machine (CALFIN): Glacial termini dataset and automated deep learning extraction method for Greenland, 1972-2019.Cryosphere,15(3).
MLA	Cheng D.,et al."Calving front machine (CALFIN): Glacial termini dataset and automated deep learning extraction method for Greenland, 1972-2019".Cryosphere 15.3(2021).