[A-CG35] Global Carbon Cycle Observation and Analysis

[ACG35-P07] Above-ground biomass estimation of an old-growth mangrove forest using airborne LiDAR in the Philippines

*Mohammad Shamim Hasan Mandal¹, Rempei Suwa², Rene Rollon³, Giannina Marie G. Albano³, Green Ann A. Cruz³, Kenki Ono⁴, Yasmin H. Primavera-Tirol⁵, Ariel C. Blanco³, Kazuo Nadaoka⁶ (1.Hiroshima Univ., Japan, 2.JIRCAS, Japan, 3.Univ. of the Philippines, Philippines, 4.FFPRI, Japan, 5.Aklan State Univ., Philippines, 6.Tokyo Institute of Tech., Japan)

Keywords:Remote sensing, Canopy Height Model (CHM), AGB, Blue carbon

Mangrove tree height estimation from airborne light detection and ranging (LiDAR) is very useful to estimate above-ground biomass (AGB). Allometric equations are often applied to estimate AGB from the LiDAR-derived canopy height model (CHM). However, such an application can provide an underestimation of AGB, especially in an old-growth mangrove forest where trees with large diameters at breast height (DBH) dominate. The present study estimated plot-based AGB from LiDAR canopy height at an old-growth natural mangrove forest in the Panay islands, Philippines. Using LiDAR-derived CHM, we constructed models to estimate Lorey’s mean height (H_m) and AGB. We found that 95% relative height (RH₉₅) of the CHM had higher correspondence with H_m (R² = 0.78) and AGB (R² = 0.66). LiDAR-based AGB models underestimated AGB for plots with larger DBH. Generalized estimation of AGB based on LiDAR data using allometric models is important to measure the biomass of mangrove forests on a regional to global scale. However, careful consideration should be made to incorporate mangrove trees DBH, especially for old-growth mangrove forests.