Wet-GC: A Novel Multimodel Graph Convolutional Approach for Wetland Classification Using Sentinel-1 and 2 Imagery With Limited Training Samples

Wet-GC: A Novel Multimodel Graph Convolutional Approach for Wetland Classification Using Sentinel-1 and 2 Imagery With Limited Training Samples

Wetland is one of the most productive resources on earth, and it provides vital habitats for several unique species of flora and fauna. Over the last decade, mapping and monitoring wetlands by utilizing deep learning (DL) models and remote sensing data gained popularity due to the importance of wetl...

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Bibliographic Details
Main Authors: Hamid Jafarzadeh, Masoud Mahdianpari, Eric W. Gill
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Canada
classification
convolutional neural network (CNN)
deep learning (DL)
graph convolutional network (GCN)
remote sensing (RS)
Online Access:https://ieeexplore.ieee.org/document/9803207/

Internet

https://ieeexplore.ieee.org/document/9803207/

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