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Forests 2016, 7(11), 259; doi:10.3390/f7110259

Estimation of Voxel-Based Above-Ground Biomass Using Airborne LiDAR Data in an Intact Tropical Rain Forest, Brunei

1
Department of Climate Environment, Korea University, Seoul 02841, Korea
2
Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea
3
Eco, Environment, Education (E3) Co., Ltd., Seoul 07547, Korea
4
Environmental and Life Sciences , Faculty of Science, Universiti Brunei Darussalam, Bandar Seri Begawan BE1410, Brunei Darussalam
*
Author to whom correspondence should be addressed.
Academic Editors: Juha Hyyppä and Timothy A. Martin
Received: 27 July 2016 / Revised: 23 October 2016 / Accepted: 25 October 2016 / Published: 31 October 2016
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Abstract

The advancement of LiDAR technology has enabled more detailed evaluations of forest structures. The so-called “Volumetric pixel (voxel)” has emerged as a new comprehensive approach. The purpose of this study was to estimate plot-level above-ground biomass (AGB) in different plot sizes of 20 m × 20 m and 30 m × 30 m, and to develop a regression model for AGB prediction. Both point cloud-based (PCB) and voxel-based (VB) metrics were used to maximize the efficiency of low-density LiDAR data within a dense forest. Multiple regression model AGB prediction performance was found to be greatest in the 30 m × 30 m plots, with R2, adjusted R2, and standard deviation values of 0.92, 0.87, and 35.13 Mg∙ha−1, respectively. Five out of the eight selected independent variables were derived from VB metrics and the other three were derived from PCB metrics. Validation of accuracy yielded RMSE and NRMSE values of 27.8 Mg∙ha−1 and 9.2%, respectively, which is a reasonable estimate for this structurally complex intact forest that has shown high NRMSE values in previous studies. This voxel-based approach enables a greater understanding of complex forest structure and is expected to contribute to the advancement of forest carbon quantification techniques. View Full-Text
Keywords: LiDAR; volumetric pixel; voxel; forest biomass; forest carbon stock; REDD+; climate change LiDAR; volumetric pixel; voxel; forest biomass; forest carbon stock; REDD+; climate change
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, E.; Lee, W.-K.; Yoon, M.; Lee, J.-Y.; Son, Y.; Abu Salim, K. Estimation of Voxel-Based Above-Ground Biomass Using Airborne LiDAR Data in an Intact Tropical Rain Forest, Brunei. Forests 2016, 7, 259.

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