Accuracy Assessment of Above-Ground Carbon Estimation in Oil Palm Plantations Using UAV-Based Geo-Information Technology
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Abstract
Accurate estimation of above-ground carbon is essential for carbon accounting and carbon credit verification. However, field-based tree height measurements are constrained in areas with dense canopy cover. This study aims to develop and evaluate the accuracy of a method for estimating oil palm tree height and above-ground carbon across different age classes Using Unmanned Aerial Vehicle (UAV) data. The study was conducted in oil palm plantations aged 6, 8, and 10 years in Phatthalung Province, Thailand, with sample sizes of 39, 54 and 43 trees, respectively (a total of 136 trees). UAV imagery combined with Global Navigation Satellite System (GNSS) data was used to generate a Digital Surface Model (DSM), Digital Terrain Model (DTM), and Canopy Height Model (CHM), and accuracy was assessed by comparison with total station measurements. The results indicate that the 6 year and 10 year plantations showed good agreement (R² = 0.703 and 0.731; RMSE = 0.972 and 0.843 m, respectively), whereas the 8-year plantation exhibited the highest error (RMSE = 1.076 m), mainly due to canopy overlap and uncertainties in the terrain model. In terms of carbon, the estimated values were 3,317.565, 10,362.015 and 8,761.218 kg C, with the highest value observed in the 8 year plantation. The findings suggest that although the height estimation errors ranged from 0.84 to 1.08 m, they remain within an acceptable level and can support MRV systems and plot-level carbon credit assessment.
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