Tree height is one of the key parameters for estimating forest aboveground biomass (AGB). Traditionally, the tree height is measured by hypsometers, which are widely used to validate Terrestrial Laser Scanner (TLS) and Airborne LiDAR (ALS). However, the measurements from hypsometers are subject to huge uncertainties in comparison with TLS and ALS. The error associated with the height measurements propagate into the AGB estimation models, and eventually downgrade the accuracy of estimated AGB and the subsequent carbon stock. In this research, we test the use of Hypsometer, TLS and ALS in a tropical lowland rainforest to measure the height (H) and Diameter at Breast Height (DBH) and take Airborne LiDAR as a benchmark with high accuracy and fidelity in height measurements. The results revealed that, the field height measured by hypsometer underestimated the tree height with RMSE of 3.11, whereas the TLS underestimated height with RMSE of 1.61, when Airborne LiDAR was used as a benchmark to validate the field measurement and TLS. Due to significant differences in derived height measurements, the AGB and carbon stock also varied remarkably with values of 146.33 Mg and 68.77 Mg from field measurements, 170.86 Mg and 80.31 Mg from TLS, 179.85 Mg and 84.53 Mg using the Airborne LiDAR. Considering the Airborne LiDAR measurement as the most accurate, the AGB and carbon stock from field measurement represent 85.55% of total AGB and carbon stock estimation from Airborne LiDAR. Meanwhile, TLS measurements reflect 95.02% of AGB and carbon stock benchmarked with the measurements from Airborne LiDAR data. The results demonstrate the huge uncertainty in height measurement of large trees in comparison with small trees indicated by the significant differences. It was concluded that AGB and carbon stocks are sensitive to height measurement errors derived from various methods for measuring the tree height, the size of trees as large trees are difficult to
Forest biomass and carbon are critical for ecological monitoring, and yet poorly modelled in complex ecosystems such as the tropical rainforests. To overcome this challenge incurred due to the complex biophysical properties of tropical forests, Airborne and Terrestrial LiDAR (Light Detection and Ranging) technologies have been used combinedly. Airborne LiDAR data 'from above' are largely restricted to analyses of lower canopy layer trees. Its combination with Terrestrial LiDAR allows the assessment of tree crowns under the upper canopy layer, thus opening up new possibilities for a more complete assessment of all the trees in a multi-layer stand. In this study, Airborne LiDAR was used for upper canopy tree measurements while Terrestrial LiDAR was complimented for lower canopy layer trees. The result showed that LiDAR-based tree measurements of DBH and height were highly accurate. We highly improved the accuracy of estimated above-ground biomass (AGB)/ carbon from 87% of Terrestrial and 90% of Airborne LiDAR-based estimates to 97% through combining the use of the two technologies. This approach contributes to the development of efficient techniques for forest monitoring systems and bears the potential to extend the modelling options from remote sensing data to understory layer trees.
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