Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice...

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Detalles Bibliográficos
Autores principales: Ließ, Mareike, Schmidt, Johannes, Glaser, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4851371/
https://www.ncbi.nlm.nih.gov/pubmed/27128736
http://dx.doi.org/10.1371/journal.pone.0153673

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4851371/
https://www.ncbi.nlm.nih.gov/pubmed/27128736
http://dx.doi.org/10.1371/journal.pone.0153673

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