Climate change impacts on biomes and aridity in Peru
The preliminary results showed that random forest worked best for the PB imbalanced data, having a 0.84 weighted average in precision and recall metric. The model reproduces 9 of the PB with low error 4.5% and overestimates 34.52 % one of them in the Amazon. Furthermore, there is an increasing slight trend (not significant) of AI at the drainage-scale, mainly in the Pacific. We hypothesize that there is a migration of dryland subtypes from dry to wet areas in the present time.
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| Main Authors: | , , , , , |
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| Format: | info:eu-repo/semantics/conferenceObject biblioteca |
| Language: | eng |
| Published: |
European Geosciences Union
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| Subjects: | Cambio Climático, Biomasa, Ecosistemas, |
| Online Access: | https://hdl.handle.net/20.500.12542/842 |
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