Estimation of forest carbon storage with small samples based on Bayesian hierarchical model
Year: 2026
Type: article
Abstract: Enhancing forest carbon sequestration capacity is vital for carbon neutrality and climate mitigation. Accurate estimation of forest carbon storage and its potential provide essential support; however, the accuracy of forest carbon storage estimation is often limited by sample size and vegetation heterogeneity induced by complex terrain. This study focuses on the Three Parallel Rivers Region, using Yunnan Forest inventory and multi-source remote sensing data to develop a Bayesian Hierarchical Model, an Ordinary Least Squares model, and a Random Forest model for comparison. The aim is to verify the advantages and applicability of the Bayesian Hierarchical Model under small-sample conditions, enhance the accuracy of forest carbon storage estimation, and identify the optimal remote sensing data source for the study area. Results indicate that the Bayesian Hierarchical Model performs best across datasets, achieving the highest accuracy ( R 2 = 0.83 ) and remaining robust as sample size declines; a comparison of model accuracy based on Landsat 8 OLI imagery, Sentinel-2 imagery, and their combination shows that the combined use of the two datasets yields the optimal model fitting performance, indicating complementary information between the two data sources; spatial distribution analysis reveals that forest carbon storage is higher in the northern and central parts of the Three Parallel Rivers Region, while relatively lower in the southern and eastern parts. Overall, in situations where the sample size is insufficient or the data distribution exhibits significant heterogeneity, the Bayesian Hierarchical Modeling approach can fully leverage the advantages of multi-source remote sensing data, thereby improving the accuracy of forest carbon storage estimation.
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
SDGs: Climate action, Life on land
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7204440097