Landsat-8 and Sentinel-2 Based Prediction of Forest Plantation C Stock Using Spatially Varying Coefficient Bayesian Hierarchical Models

This study sought to establish the performance of Spatially Varying Coefficient (SVC) Bayesian Hierarchical models using Landsat-8, and Sentinel-2 derived auxiliary information in predicting plantation forest carbon (C) stock in the eastern highlands of Zimbabwe. The development and implementation o...

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Detalles Bibliográficos

Principais autores:	Tsikai Solomon Chinembiri, Onisimo Mutanga, Timothy Dube
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2022-11-01
Series:	Remote Sensing
Assuntos:	Bayesian hierarchical modelling geostatistics <i>Eucalyptus grandis</i> <i>Eucalyptus camaldulensis</i> <i>Pinus patula</i> spatial random effects
Acceso en liña:	https://www.mdpi.com/2072-4292/14/22/5676
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