首页|Aboveground biomass estimation of an old-growth mangrove forest using airborne LiDAR in the Philippines

Aboveground biomass estimation of an old-growth mangrove forest using airborne LiDAR in the Philippines

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  • Wiley
Monitoring mangrove forest biomass is vital for assessing their carbon sequestration potential. This study uses airborne LiDAR data to estimate the aboveground biomass (AGB) of an old-growth mangrove forest in the Katunggan It Ibajay Ecopark (KII Ecopark) on Panay Island, Philippines. To establish a relationship between the LiDAR canopy height profile with the field observed AGB at the plot level, we tested 20 LiDAR derived relative height (RH) metrics. First, we tested a relationship between field observed Lorey's mean canopy height (H_m) and RH metrics, which were then used to estimate AGB by applying a previously established allometric model. Second, we tested the direct relationship between RH metrics and observed AGB. Among RH metrics, RH_(95) showed the best correspondence with the Hm (R~2 = 0.79) and when it was applied to the previously developed allometric for AGB estimation, the results showed a large underestimation of AGB (R~2 = 0.46) for plots with higher canopy heights. Conversely, the direct method using a power regression model with RH_(95) and observed AGB provided a better estimate (R~2 = 0.58). However, both models still underestimated AGB at the KII Ecopark. We conclude that, LiDAR-based AGB estimation using H_m as a single variable can result in considerable underestimation, especially in old-growth mangrove forests such as KII Ecopark. Further studies are necessary to develop accurate models for estimating AGB in such special types of mangroves which is important for mangrove monitoring, reporting and verification (MRV).

AGBblue carboncarbon storageforest biomassremote sensing

Mohammad Shamim Hasan Mandal、Rempei Suwa、Rene N. Rollon、Giannina Marie G. Albano、Green Ann A. Cruz、Kenji Ono、Yasmin H. Primavera-Tirol、Ariel C. Blanco、Kazuo Nadaoka

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Forestry Division, Japan International Research Center for Agricultural Sciences,Ibaraki, Japan

Institute of Environmental Science and Meteorology, College of Science,University of the Philippines, Quezon City, Philippines

Forestry and Forest Products Research Institute, Ibaraki, Japan

College of Fisheries and Marine Sciences,Aklan State University, New Washington,Aklan, Philippines

Department of Geodetic Engineering,College of Engineering, University of the Philippines, Quezon City, Philippines

School of Environment and Society,Tokyo Institute of Technology, Tokyo,Japan||Kajima Technical Research Institute,Tokyo, Japan

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2025

10.1111/1440-1703.12503

Ecological research

Ecological research

ISSN：0912-3814
年,卷(期)：2025.40(2)
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