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The Cartographic Journal
The World of Mapping
Volume 59, 2022 - Issue 3
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Refereed Papers

A Comparison of Machine Learning Methods Applied to the Automated Selection of River Networks

Chaode Yana School of Water Conservancy Science and Engineering, Zhengzhou University, Zhengzhou, People’s Republic of China; Yellow River Institute for Ecological Protection & Regionally Coordinated Development, Zhengzhou University, Zhengzhou, People’s Republic of ChinaCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1063-4854View further author information
ORCID Icon,
Xiao Liub School of Water Conservancy Science and Engineering, Zhengzhou University, Zhengzhou, People’s Republic of China; Management Committee of National Xuchang Economic and Technological Development Zone, Xuchang, People’s Republic of ChinaView further author information
,
Muhammad Waseem Bootaa School of Water Conservancy Science and Engineering, Zhengzhou University, Zhengzhou, People’s Republic of China; Yellow River Institute for Ecological Protection & Regionally Coordinated Development, Zhengzhou University, Zhengzhou, People’s Republic of ChinaView further author information
&
Ziwei Panc School of Water Conservancy Science and Engineering, Zhengzhou University, Zhengzhou, People’s Republic of China; School of the Geo- Science & Technology, Zhengzhou University, Zhengzhou, People’s Republic of ChinaView further author information
Pages 187-202 | Published online: 16 Sep 2022

Citations (3)

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Yuhao Kang, Song Gao & Robert E. Roth. Artificial intelligence studies in cartography: a review and synthesis of methods, applications, and ethics. Cartography and Geographic Information Science 0:0, pages 1-32.
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Articles from other publishers (2)

Huafei Yu, Tinghua Ai, Min Yang, Jingzhong Li, Lu Wang, Aji Gao, Tianyuan Xiao & Zhe Zhou. (2023) Integrating domain knowledge and graph convolutional neural networks to support river network selection. Transactions in GIS 27:7, pages 1898-1927.
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Di Wang & Haizhong Qian. (2023) CatBoost-Based Automatic Classification Study of River Network. ISPRS International Journal of Geo-Information 12:10, pages 416.
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