Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine

Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyl...

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Detalles Bibliográficos
Autores principales: Reyes-Muñoz, Pablo, Pipia, Luca, Salinero-Delgado, Matías, Belda, Santiago, Berger, Katja, Estévez, José, Morata, Miguel, Rivera-Caicedo, Juan Pablo, Verrelst, Jochem
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613398/
https://www.ncbi.nlm.nih.gov/pubmed/36016907
http://dx.doi.org/10.3390/rs14061347

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7613398/
https://www.ncbi.nlm.nih.gov/pubmed/36016907
http://dx.doi.org/10.3390/rs14061347

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