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This study estimated aboveground carbon stock (AGC) using field data and integrated multi-source remote sensing imagery to understand the effects of Pantana phyllostachysae Chao (P. phyllostachysae) stress. AGC remote sensing inversion was performed while accounting for P. phyllostachysae stress, and changes were analyzed. Results indicate: (1) Carbon content coefficients of Moso bamboo leaves, branches, and culms under pest stress ranged from 0.422 to 0.543\g/g, decreasing with increased stress. (2) A random forest model using multi-source data demonstrated the best performance (R2 = 0.688), estimating average AGC at 28.427 t/ha and total carbon sequestration at 913.902 MtC (Million tons of Carbon). (3) Increased pest stress resulted in gradual reductions in AGC. (4) Pest stress is estimated to result in a carbon sequestration loss of 77.443 MtC. The AGC estimation model indicates that P. phyllostachysae significantly reduces AGC, providing crucial data for understanding carbon cycling and enhancing carbon sink management in Moso bamboo forests. © 2025 American Society for Photogrammetry and Remote Sensing. All rights reserved.
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Photogrammetric Engineering and Remote Sensing
ISSN: 0099-1112
Year: 2025
Issue: 4
Volume: 91
Page: 213-224
1 . 0 0 0
JCR@2023
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