August 15, 2025ForestsOpen Access

Estimating Aboveground Biomass of Mangrove Forests in Indonesia Using Spatial Attention Coupled Bayesian Aggregator

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SAC-BA achieved an R2 of 0.82 in estimating aboveground biomass, showcasing its effectiveness.
The model leveraged multi-source remote sensing data to improve accuracy in fragmented mangrove landscapes.
Machine learning techniques were used to train models, which were then fused based on spatial attention weights.
The successful application may enhance carbon assessments and inform strategic mangrove conservation initiatives.

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Spatial attention coupled Bayesian aggregator improves aboveground biomass estimates in mangroves, supporting conservation efforts.

Zhu et al. (2025) studied this question.

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