Modeling land susceptibility to wind erosion hazards using LASSO regression and graph convolutional networks
Predicting land susceptibility to wind erosion is necessary to mitigate the negative impacts of erosion on soil fertility, ecosystems, and human health. This study is the first attempt to model wind erosion hazards through the application of a novel approach, the graph convolutional networks (GCNs),...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-05-01
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| Series: | Frontiers in Environmental Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fenvs.2023.1187658/full |