Global mangrove soil organic carbon stocks dataset at 30 m resolution for the year 2020 based on spatiotemporal predictive machine learning

This dataset presents global soil organic carbon stocks in mangrove forests at 30 m resolution, predicted for 2020. We used spatiotemporal ensemble machine learning to produce predictions of soil organic carbon content and bulk density (BD) to 1 m soil depth, which were then aggregated to calculate...

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Detalles Bibliográficos
Autores principales: Maxwell, Tania L., Hengl, Tomislav, Parente, Leandro L., Minarik, Robert, Worthington, Thomas A., Bunting, Pete, Smart, Lindsey S., Spalding, Mark D., Landis, Emily
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562832/
https://www.ncbi.nlm.nih.gov/pubmed/37823063
http://dx.doi.org/10.1016/j.dib.2023.109621

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10562832/
https://www.ncbi.nlm.nih.gov/pubmed/37823063
http://dx.doi.org/10.1016/j.dib.2023.109621

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