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Scientia Silvae Sinicae ›› 2014, Vol. 50 ›› Issue (6): 42-54.doi: 10.11707/j.1001-7488.20140606

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Comparison of Several Compatible Biomass Models and Estimation Approaches

Fu Liyong1, Lei Yuancai1, Zeng Weisheng2   

  1. 1. Research Institute of Forest Resources Information Techniques, CAF Beijing 100091;
    2. Academy of Forest Inventory and Planning, State Forestry Administration Beijing 100714
  • Received:2013-06-19 Revised:2013-08-29 Online:2014-06-25 Published:2014-07-07
  • Contact: 雷渊才

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Abstract:

So far, the approaches of nonlinear seemingly unrelated regression (NSUR), nonlinear adjustment in proportion (NAP) and nonlinear simultaneous equations (NSE) have been proposed to establish compatible biomass models. However, to our knowledge, systemic comparison of these methods is not studied. Therefore, the three methods NSUR, NAP and NSE were compared based on predictive accuracy using 150 masson pine (Pinus massoniana) biomass data in this study. Two alternative approaches, controlling jointly from level to level by ratio functions and controlling directly under total biomass by proportion functions were considered for the two approaches of NAP and NSE. Six candidate tree variables of diameter at breast height, tree height, ground diameter, age, under branch height and crown width were evaluated for their contribution to biomass models improvement. Single variable, bivariate and multivariate (three variables) biomass models were established based on the first three of the most significant tree characteristics. Heteroskedasticity in the biomass models was removed by weighted least square regression. Compatible biomass models were established and estimated based on single variable, bivariate and multivariate using NSUR, NAP and NSE. The results showed that the three analyzed methods could ensure efficiently that components of biomass added up to the total biomass with high prediction accuracy. However, overall, NSE had the highest prediction accuracy and most stable, following by NSUR, and NAP was the worst. For balancing the model prediction accuracy and survey cost, the NSE of controlling directly under total biomass with diameter at breast height and height as stand variables was proposed to construct compatible biomass model at considering or no considering stand origin situation based on the systemic comparison of modelling and validation data sets.

Key words: nonlinear seemingly unrelated regression, adjustment in proportion, nonlinear simultaneous equations, compatible, biomass model

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