A combined multi-source data and deep learning approach for retrieving snow depth on Antarctic Sea ice during the melting season

IF 3.7 1区 地球科学 Q1 GEOGRAPHY, PHYSICAL
Zhongnan Yan, Qing Ji, Bin He, Yizhuo Chen, Yueyun Wang, Xiaoping Pang
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引用次数: 0

Abstract

Snow on the Antarctic sea ice is a crucial component of the cryosphere. In response to the dynamic and highly heterogeneous Antarctic snow during the sea ice melting season, this study employed a c...
多源数据和深度学习相结合的南极海冰融化季节雪深检索方法
南极海冰上的雪是冰冻圈的重要组成部分。针对海冰融化季节南极雪的动态性和高度异质性,这项研究采用了一种...
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来源期刊
CiteScore
6.50
自引率
3.90%
发文量
88
审稿时长
3 months
期刊介绍: The International Journal of Digital Earth is a response to this initiative. This peer-reviewed academic journal (SCI-E) focuses on the theories, technologies, applications, and societal implications of Digital Earth and those visionary concepts that will enable a modeled virtual world. The journal encourages papers that: Progress visions for Digital Earth frameworks, policies, and standards; Explore geographically referenced 3D, 4D, or 5D models to represent the real planet, and geo-data-intensive science and discovery; Develop methods that turn all forms of geo-referenced data, from scientific to social, into useful information that can be analyzed, visualized, and shared; Present innovative, operational applications and pilots of Digital Earth technologies at a local, national, regional, and global level; Expand the role of Digital Earth in the fields of Earth science, including climate change, adaptation and health related issues,natural disasters, new energy sources, agricultural and food security, and urban planning; Foster the use of web-based public-domain platforms, social networks, and location-based services for the sharing of digital data, models, and information about the virtual Earth; and Explore the role of social media and citizen-provided data in generating geo-referenced information in the spatial sciences and technologies.
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