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Stand parameter extraction based on video point cloud data

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Abstract

Monitoring sample plots is important for the sustainable management of forest ecosystems. Acquiring resource data in the field is labor-intensive, time-consuming and expensive. With the rapid development of hardware technology and photogrammetry, forest researchers have turned two-dimensional images into three-dimensional point clouds to obtain resource information. This paper presents a method of sample plot analysis using two charge-coupled device (CCD) cameras based on video photography. A handheld CCD camera was used to shoot the sample plot by surrounding a central tree. Video-based point clouds were used to detect and model individual tree trunks in the sample plots and the DBH of each was estimated. The experimental results were compared with field measurement data. The results show that the relative root mean squared error (rRMSE) of the DBH estimates of individual trees was 2.1–5.7%, acceptable for practical applications in traditional forest inventories. The rRMSE of height estimates was 2.7–36.3%. Average DBH and heights, and tree density and volume were calculated. Video-based methods require compact observation instruments, involve low costs during field investigations, acquire data with high efficiency, and point cloud data can be processed automatically. Furthermore, this method can directly extract information on the relative position of trees, which is important to show distribution visually and provides a basis for researchers to regulate stand density. Additionally, video photography with its unique advantages is a technology warranting future attention for forest inventories and ecological construction.

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Acknowledgements

We are grateful to the staff of the Precision Forestry Key Laboratory of Beijing, Beijing Forestry University. We are also very thankful for the prompt response of the Journal of Forestry Research and its reviewers. The reviewers’ comments were highly beneficial for improving the manuscript draft.

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Authors and Affiliations

  1. Precision Forestry Key Laboratory of Beijing, Beijing Forestry University, Beijing, 100083, People’s Republic of China

    Ziyu Zhao, Zhongke Feng & Yudong Li

  2. College of Natural Resources and Environment, Northwest A&F University, Xian, 712100, People’s Republic of China

    Jincheng Liu

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  1. Ziyu Zhao
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Contributions

ZZ and ZF conceived and designed the experiments; ZZ and JL performed the experiments; ZZ and YL analyzed the data; ZZ wrote the main manuscript. All authors contributed in writing and discussing the paper.

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Correspondence to Zhongke Feng.

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Project funding: The work was funded partly by the National Natural Science Foundation of China (Grant number funded this research U1710123) and the Fundamental Research Funds for the Central Universities (No. 2015ZCQ-LX-01).

The online version is available at http://www.springerlink.com

Corresponding editor: Tao Xu.

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Zhao, Z., Feng, Z., Liu, J. et al. Stand parameter extraction based on video point cloud data. J. For. Res. 32, 1553–1565 (2021). https://doi.org/10.1007/s11676-020-01173-z

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  • DOI: https://doi.org/10.1007/s11676-020-01173-z

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