Converting diameter measurements of Pinus radiata taken at different breast heights |
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Authors: | Yuhuan Zhang Yun Li Huiquan Bi |
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Affiliation: | 1. School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China;2. Forest Science, New South Wales Department of Primary Industries, Parramatta NSW 2124, Australia;3. School of Forest and Ecosystem Science, University of Melbourne, Creswick Vic. 3363, Australia |
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Abstract: | Two compatible conversion factors for converting diameter measurements taken at different breast heights were derived for Pinus radiata using taper data from more than 3000 trees. The two breast heights used for conversion were 1.3 and 1.4 m above ground, as defined in Australia and New Zealand, two major radiata-growing countries in the world. The conversion factors were estimated through three alternative statistical methods including simple least squares regression, seemingly unrelated regression and errors-in-variables models. The three sets of estimates were almost identical and had similar conversion accuracy, although the second method was slightly better. The conversion factors were more accurate than overbark taper equations used for the same purpose. The factor was 0.9916 for converting diameter measured at 1.3 to that at 1.4 m above ground, and the inverse of this value, 1.0084, was for the vice versa. When calculating tree and stand volume and biomass using equations with diameter at a different breast height as a predictor to that of the input data, the bias, either over or under estimation, could be between 1.67% and 2.00% without conversion. These conversion factors will facilitate the sharing of data among radiata growing countries with different definitions of breast height, but more importantly it will help correct the bias in stand volume and biomass estimation caused by the seemingly negligible difference in breast height when software for forest resource management and decision support developed in one country is applied in another. Such bias when accumulated over a large management area may not be financially insignificant for an astute forest management agency. |
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Keywords: | diameter volume biomass estimation conversion tables and factors bias correction factors regression models equations |
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