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Croatian Journal of Forest Engineering : Journal for Theory and Application of Forestry Engineering, Vol. 38 No. 1, 2017.

Original scientific paper

Developing a Volume Model Using South NTS-372R Total Station without Tree Felling in a Populus canadensis Moench Plantation in Beijing, China

Zhongke Feng ; Beijing Forestry University Forestry College Precision Forestry Key Laboratory of Beijing No.35 Tsinghua East Road Haidian District,Beijing CHINA
Fei Yan ; Beijing Forestry University Forestry College Precision Forestry Key Laboratory of Beijing No.35 Tsinghua East Road Haidian District,Beijing CHINA
Mohammad Rahmat Ullah ; Beijing Forestry University College of Forestry No.35 Tsinghua East Road Haidian District,Beijing CHINA
Yi Dang ; Beijing Forestry University College of Forestry No.35 Tsinghua East Road Haidian District,Beijing CHINA

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Abstract

Volume table preparation using the traditional method and a collection model requires the harvest of approximately 200–300 trees of individual species. Although high precision could be achieved using that method, it causes huge damage to the forest. To minimize these losses, in this study, a South NTS-372R total station with a precise angle and distance measurement mode was used to measure 507 trees of Populus canadensis Moench without single tree felling. Moreover, the C# programming language was used in this study and the collected volume data were inserted in the total station. Using this method, a real-time precise measurement of volume could be achieved. After data collection, the optimal binary volume model of Populus canadensis Moench could be obtained through a comparative analysis. It turns out that the Yamamoto model is the optimal binary volume model (also known as two predictor variable model), with 0.9641 as the coefficient of determination (R2) and 0.19 m3 as the standard deviation of estimated value (SEE), which presents a good imitative effect. Moreover, it showed relative stability with the general relative error (TRE) of –0.12% and the mean system error (MSE) of –1.24%. The mean predicted error (MPE) of 1.18% and the mean predicted standard error (MPSE) of 9.25% showed high estimated precision of the average and individual tree volumes. The model has only three parameters, so it is suitable for volume table preparation. Finally, this study will present some new technical methods and means for volume modeling for further application in forestry.

Keywords

total station; volume model; Populus canadensis

Hrčak ID:

174458

URI

https://hrcak.srce.hr/174458

Publication date:

20.1.2017.

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