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Assessing tree height and density of a young forest using a consumer unmanned aerial vehicle (UAV)

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Abstract

Accurate, cost-effective monitoring and management of young forests is important for future stand quality. There is a critical need for a rapid assessment tool for forest monitoring and management. This study uses a low-cost unmanned aerial vehicle (UAV) to complete a tree height and tree density assessment in a newly forested Chinese fir (Cunninghamia lanceolata (Lamb) Hook) planting (15 sample plots), Shunchang County, Fujian, China (1.12 ha). Images obtained from a Phantom4-Multispectral UAV were used to generate a digital surface model (DSM) with DJI Terra software (0.02 m spatial resolution). Based on the DSM, the individual trees were identified and the height of each corresponding tree was determined. The impacts of factors related to individual tree detection (ITD) and tree height accuracy were also analyzed. For the tree-level, the highest accuracy of ITD for Chinese fir was 98.93% (F-score = 98.93%). Remotely sensed individual tree heights produced an R2 value of 0.89, RMSE value of 0.22 m when compared to a field survey. At the stand-level, tree height assessment yielded R2 = 0.95, RMSE = 0.12 m, and tree density assessment yielded R2 = 0.99, RMSE = 48 tree ha−1. The results highlight that UAVs can successfully monitor forest parameters and hold great potential as a supplement or substitute tool in field inventory.

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Acknowledgements

This research was funded by the science and technology major project of Fujian province, China (Grant number 2018NZ0101), the National Natural Science Foundation of China (Grant numbers 31770760) and the scholarship program of China Scholarship Council (Grant number 201908350124 and 202008350151). We wish to thank Dr. Elena Mikhailova for her assistance in review and editing. We also thank the anonymous reviewers and editors for their professional comments and suggestions.

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  1. Zhenbang Hao and Lili Lin these authors contributed equally to this work.

Authors and Affiliations

  1. Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Fuzhou, 350002, Fujian, China

    Zhenbang Hao, Lili Lin, Yusen Jiang, Minghui Li, Nibin Wei, Kunyong Yu & Jian Liu

  2. University Key Lab for Geomatics Technology and Optimized Resources Utilization in Fujian Province, No. 15 Shangxiadian Road, Fuzhou, 350002, Fujian, China

    Zhenbang Hao, Lili Lin, Yusen Jiang, Minghui Li, Nibin Wei, Kunyong Yu & Jian Liu

  3. Department of Forestry and Environmental Conservation, Clemson University, Clemson, SC, 29634, USA

    Christopher J. Post

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Appendix 1

Fig. 11
figure 11

Workflow of tree height extraction using ModelBuilder. The dark blue color represents the input file; the light blue color represents the input parameters; the yellow color represents the ArcGIS tool used in the model; the light green color represents the intermediate data; the dark green color represents the output result

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Appendix 2

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A visual modeling environment for tree height estimation

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Hao, Z., Lin, L., Post, C.J. et al. Assessing tree height and density of a young forest using a consumer unmanned aerial vehicle (UAV). New Forests 52, 843–862 (2021). https://doi.org/10.1007/s11056-020-09827-w

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