Tree Cover Estimation in Global Drylands from Space Using Deep Learning

Tree Cover Estimation in Global Drylands from Space Using Deep Learning

Accurate tree cover mapping is of paramount importance in many fields, from biodiversity conservation to carbon stock estimation, ecohydrology, erosion control, or Earth system modelling. Despite this importance, there is still uncertainty about global forest cover, particularly in drylands. Recentl...

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Dades bibliogràfiques
Autors principals: Guirado Hernández, Emilio, Alcaraz Segura, Domingo, Cabello Piñar, Francisco Javier, Puertas Ruíz, Sergio, Herrera, Francisco, Tabik, Siham
Format: info:eu-repo/semantics/article
Idioma:English
Publicat: MDPI 2020
Matèries:
convolutional neural networks
data augmentation
deep learning
dry forest
forest mapping
large-scale datasets
transfer learning
Accés en línia:http://hdl.handle.net/10835/7706

Internet

http://hdl.handle.net/10835/7706

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