Drainage Pattern Recognition Method Using Graph Convolutional Networks Combined With Three‐Dimensional Elevation Features

ABSTRACT Drainage pattern recognition plays a crucial role in flood management, hydraulic engineering site selection, and biodiversity maintenance. Although deep learning methods have been widely employed in drainage pattern recognition in recent years, most research has focused on two‐dimensional f...

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Veröffentlicht in:	Transactions in GIS Jg. 29; H. 1
Hauptverfasser:	Qiang, Bo, Liu, Tao, Du, Ping, Li, Pengpeng, Wang, Wenning, Xu, Shenglu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Blackwell Publishing Ltd 01.02.2025
Schlagworte:	Accuracy Artificial neural networks Biodiversity Chebyshev approximation Deep learning Drainage Drainage patterns Flood control Flood management Geographic information systems graph convolutional network Hydraulic engineering Machine learning Mathematical morphology Pattern recognition Polynomials river Site selection Support vector machines three‐dimensional elevation
ISSN:	1361-1682, 1467-9671
Online-Zugang:	Volltext
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