| Authors |
Xiaomin Li, Dan Zhao, Junhua Chen, Jinchen Wu, Xuan Mu, Zhaoju Zheng, Cong Xu, Chunjie Fan, Yuan Zeng, Bingfang Wu |
| Intro |
Accurate estimation of plantation aboveground biomass (AGB) is critical for quantifying
carbon cycles and informing sustainable forest resource management, but enhancing
estimation accuracy remains a key challenge. Although tree height and stand age are recognized
as critical predictors for enhancing AGB models in addition to spectral vegetation
indices, their individual and combined contributions in regional plantation forests remain
insufficiently quantified, especially concerning the potential for leveraging the distinct
characteristics of fast-growing plantations to facilitate AGB estimation. This study developed
multi-source remote sensing-based Eucalyptus AGB estimation models for Nanning,
Guangxi, integrating stand age and tree height to assess their impacts. Stand age was
mapped from Landsat time-series imagery, and tree height was derived from UAV-LiDAR
data. Plot-level reference AGB was obtained using fused UAV and terrestrial LiDAR point
clouds. A random forest model, incorporating these variables with Sentinel-2 spectral
information and topography, then achieved regional AGB estimation. The findings demonstrate
that (1) tree height serves as the most influential predictor for AGB estimation at the
regional scale, yielding a robust model performance (R2 = 0.84). (2) Tree height captures the
majority of the explanatory power associated with stand age. Once tree height was included
as a predictor, the subsequent addition of stand age offered no significant improvement in
model accuracy (R2 = 0.85). (3) Given the challenges in obtaining precise tree height data
and the robust correlation between stand age and tree height in fast-growing plantations,
the integration of stand age substantially improved the accuracy of AGB estimations (from
the spectral model of R2 = 0.54 to R2 = 0.74), with performance approaching that of tree
height-based models (ΔR2 = 0.10). Consequently, in fast-growing plantations, which are
often characterized by high stand homogeneity, a hybrid model incorporating stand age
can offer a reliable and cost-effective solution for AGB estimation. |
English
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