A multi-source data approach to carbon stock prediction using Bayesian hierarchical geostatistical models in plantation forest ecosystems

A multi-source data approach to carbon stock prediction using Bayesian hierarchical geostatistical models in plantation forest ecosystems

ABSTRACTModeling of environmental phenomena is usually confounded by the influence of multiple factors existing at different time and spatial scales. Bayesian modeling is presumed to be the best approach for modeling such complex systems. Using a Bayesian hierarchical inferential framework, we emplo...

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Bibliographic Details
Main Authors: Tsikai S. Chinembiri, Onisimo Mutanga, Timothy Dube
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:GIScience & Remote Sensing
Subjects:
Bayesian
hierarchical
geostatistics
MCMC
prediction
remote sensing
Online Access:https://www.tandfonline.com/doi/10.1080/15481603.2024.2303868

Internet

https://www.tandfonline.com/doi/10.1080/15481603.2024.2303868

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