Carbon Stock Prediction in Managed Forest Ecosystems Using Bayesian and Frequentist Geostatistical Techniques and New Generation Remote Sensing Metrics

Carbon Stock Prediction in Managed Forest Ecosystems Using Bayesian and Frequentist Geostatistical Techniques and New Generation Remote Sensing Metrics

The study compares the performance of a hierarchical Bayesian geostatistical methodology with a frequentist geostatistical approach, specifically, Kriging with External Drift (KED), for predicting C stock using prediction aides from the Landsat-8 and Sentinel-2 multispectral remote sensing platforms...

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Bibliographic Details
Main Authors: Tsikai Solomon Chinembiri, Onisimo Mutanga, Timothy Dube
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Remote Sensing
Subjects:
Bayesian methodology
classical geostatistics
multispectral remote sensing
carbon stock
plantation forest
managed ecosystem
Online Access:https://www.mdpi.com/2072-4292/15/6/1649

Internet

https://www.mdpi.com/2072-4292/15/6/1649

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