Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

Soil respiration inherently shows strong spatial variability. It is difficult to obtain an accurate characterization of soil respiration with an insufficient number of monitoring points. However, it is expensive and cumbersome to deploy many sensors. To solve this problem, we proposed employing the...

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Detalles Bibliográficos
Autores principales: Hu, Junguo, Zhou, Jian, Zhou, Guomo, Luo, Yiqi, Xu, Xiaojun, Li, Pingheng, Liang, Junyi
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/PMC4726581/
https://www.ncbi.nlm.nih.gov/pubmed/26807579
http://dx.doi.org/10.1371/journal.pone.0146589

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726581/
https://www.ncbi.nlm.nih.gov/pubmed/26807579
http://dx.doi.org/10.1371/journal.pone.0146589

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