The simultaneous equations models for the application in forestry

DOI

10.2991/essaeme-18.2018.1How to use a DOI?

Keywords

compatible biomass equations, simultaneous equations, measure error model

Abstract

In accordance with weakness of traditional biomass models in which the sum of the above- and below-ground tree components was not equal to the whole tree, compatible biomass equations were developed for the above- and below-ground tree components of 11 kinds of tree species in Heilongjiang Province. The data used to develop biomass models are from 299 trees that were collected from 69 sample plots, and represented a wide range of stand and site conditions in Heilongjiang Province. Based on the total biomass model as restrictions, the compatible tree biomass equations for each component (stems, branches, foliages, and roots) were separately established by considering diameter at breast height (D) as independent variables in the form of simultaneous equations with measure error of independent variables. The evaluation and validation procedures for tree biomass models were performed by using the following statistical criterions: the coefficient of determination (R2), sum square of error (SEE), Mean Bias (MB), and Mean Absolute Bias (MAB). The results showed that although parameter estimation accuracy of compatible biomass equations was not better than traditional biomass models, the compatible biomass equations could effectively overcome the weakness of un-compatible of traditional biomass models.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fuxiang Liu
PY  - 2018/07
DA  - 2018/07
TI  - The simultaneous equations models for the application in forestry
BT  - Proceedings of the 2018 4th International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2018)
PB  - Atlantis Press
SP  - 1
EP  - 6
SN  - 2352-5398
UR  - https://doi.org/10.2991/essaeme-18.2018.1
DO  - 10.2991/essaeme-18.2018.1
ID  - Liu2018/07
ER  -