4.4 Article

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

期刊

NEW FORESTS
卷 52, 期 5, 页码 843-862

出版社

SPRINGER
DOI: 10.1007/s11056-020-09827-w

关键词

Canopy height model (CHM); DSM; Forest parameters; ITD; Low-cost UAV; Remote sensing

类别

资金

  1. science and technology major project of Fujian province, China [2018NZ0101]
  2. National Natural Science Foundation of China [31770760]
  3. China Scholarship Council [201908350124, 202008350151]

向作者/读者索取更多资源

This study utilized a low-cost unmanned aerial vehicle to assess tree height and density in a newly forested area in Fujian, China. The results showed that UAVs can accurately monitor forest parameters and have the potential to supplement or replace traditional field inventory methods.
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 R-2 value of 0.89, RMSE value of 0.22 m when compared to a field survey. At the stand-level, tree height assessment yielded R-2 = 0.95, RMSE = 0.12 m, and tree density assessment yielded R-2 = 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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