Abstract
The study was carried out at Yellapur Forest Division, Karnataka, with 86.97% forest area, exploring aboveground carbon (AGC) variations across different forest types and their correlation with LiDAR metrics. Ten one-hectare permanent plots were established, with 3 in dry and moist deciduous each, and 4 in semievergreen forests. All trees with >30 cm girth at breast height were inventoried. AGC estimates were 308.28 mg ha–1 in semi-evergreen, 207.77 mg ha–1 in moist deciduous, and 117.88 mg ha–1 in dry deciduous forests. LiDAR data were acquired using a Nextcore Lumos XM120 UAV LiDAR system. In dry deciduous and moist deciduous forests, the 95th height percentile correlated strongly with observed AGC, yielding predicted AGC values of 118.56 mg ha–1 and 208.86 mg ha–1, with R2 values of 0.91 and 0.83, respectively. Conversely, in semi-evergreen forests, the 50th height percentile outperformed other metrics, resulting in a predicted AGC of 310.90 mg ha–1 (R2 =0.57).
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