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Sensitivity of volume estimation to error in the measurement and modelling methods
Author: Dang To Kien
Publication Date: 2012
Pages: 30
Publisher: ANU
Keywords: REDD+, community forestland, forest carbon biomass estimation in stem, local villagers
Fulltext:
Abstract:
The accuracy of volume estimations will reflect the sampling methodology, quality of the measurements as well as the methods adopted in the modelling procedure. In this study, the limitedness of it is that we are unable to assess the sampling method due to our limited access to detailed spatial data from each plot and other necessary information. As Westfall and Patterson identified 'in comparision with sampling error, the error due to measurement variation was relatively small; however, systematic biases in measurements produced subtantial errors increases' (Westfal and Patterson, 2007). It is equally important to examine the sensitivity of volume estimation to the latter issues (i.e. data measurement and modelling method). This study focuses on identifying errors and biases in data measurement, followed by examining the sensitivity of volume estimation to error versus without-error checked. The importance of understanding the sensitivity of different aspects of the measurement/modelling is that it allows us to concentrate on the aspects that may offer the greatest improvements/potential problems in the estimation procedure.
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