%0 Journal Article
%T A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)
%A Sean P Healey
%A Paul L Patterson
%A Sassan Saatchi
%A Michael A Lefsky
%A Andrew J Lister
%A Elizabeth A Freeman
%J Carbon Balance and Management
%D 2012
%I BioMed Central
%R 10.1186/1750-0680-7-10
%X We propose a method of identifying a subset of the GLAS data which can justifiably be treated as a simple random sample in model-based biomass estimation. The relatively uniform spatial distribution and locally arbitrary positioning of the resulting sample is similar to the design used by the US national forest inventory (NFI). We demonstrated model-based estimation using a sample of GLAS data in the US state of California, where our estimate of biomass (211 Mg/hectare) was within the 1.4% standard error of the design-based estimate supplied by the US NFI. The standard error of the GLAS-based estimate was significantly higher than the NFI estimate, although the cost of the GLAS estimate (excluding costs for the satellite itself) was almost nothing, compared to at least US$ 10.5 million for the NFI estimate.Global application of model-based estimation using GLAS, while demanding significant consolidation of training data, would improve inter-comparability of international biomass estimates by imposing consistent methods and a globally coherent sample frame. The methods presented here constitute a globally extensible approach for generating a simple random sample from the global GLAS dataset, enabling its use in forest inventory activities.Methods are needed to monitor the magnitude and spatial distribution of global forest carbon storage, an important component of the global carbon cycle. Initiatives such as REDD (United Nations Collaborative Programmed on Reducing Emissions from Deforestation and Degradation in Developing Countries) depend upon accurate, precise, and consistent national-level reporting of forest carbon storage. Traditionally, estimates of carbon storage in the context of international monitoring have come from field-based inventories [1]. In such inventories, well-developed principles of sample design support straightforward derivation of estimates and uncertainties. However, many countries do not have national forest inventories, and among those th
%K Biomass
%K Forest monitoring
%K Remote sensing
%K Lidar
%U http://www.cbmjournal.com/content/7/1/10