Modelling individual tree aboveground biomass using discrete return Lidar in lowland Dipterocarp forest of Malaysia

Tropical forests in Southeast Asia have declined acutely over the past several decades (William 2007). In particular, according to a new global forest map in partnership with Google, Malaysia had the world’s highest rate of forest loss between 2000 and 2012 (Butler 2013). Reducing emissions from deforestation and forest degradation (REDD+) is the framework for conserving and enhancing carbon stocks of forested area in the tropics (UNFCC 2007). For REDD+ implementation, accurate estimation and monitoring of carbon stocks are required at the national and subnational levels. To establish robust and transparent monitoring systems, a combination of ground-based sampling and remote sensing approaches was recommended (UNFCCC 2009). Aboveground biomass (AGB) of trees in tropical forests account for significant part of the total carbon pool (Houghton et al. 2001). Therefore, estimating AGB is critical MODELLING INDIVIDUAL TREE ABOVEGROUND BIOMASS USING DISCRETE RETURN LIDAR IN LOWLAND DIPTEROCARP FOREST OF MALAYSIA

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