气候变化领域集成服务门户(CCPortal): Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth

CCPortal

DOI	10.1016/j.foreco.2020.117949
	Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth
	Vanderwel M.C.; Lopez E.L.; Sprott A.H.; Khayyatkhoshnevis P.; Shovon T.A.
发表日期	2020
ISSN	0378-1127
卷号	461
英文摘要	Unmanned aerial vehicles (UAVs) have opened new opportunities for measuring 3D canopy structure from aerial imagery. Image data collected with a UAV can be processed to generate detailed information on local canopy structure around an individual tree, which may be a useful proxy for the amount of competition that tree experiences from its neighbours. Structural indices of competition traditionally have been derived from ground-based plot data, and it is not clear whether aerial canopy data from a UAV are as effective as ground data for modelling the effects of competition on individual-tree growth. Here, we compare the relative performance of four ground-based competition indices derived from plot data, five canopy-based competition indices derived from UAV data, and one hybrid index that uses both data types, for predicting the radial growth of two northern tree species (white spruce, lodgepole pine). Ground-based and canopy-based competition indices were both represented among the top-performing models for each species, but no single index was unambiguously favoured over all others. Of the ten competition indices we considered, the mean canopy height within 15 m of a subject tree had the strongest performance across both species, including the best performance for lodgepole pine (R2 = 0.29) and third-best performance for white spruce (R2 = 0.42). Models with mean canopy height also revealed interactions between competition and soil moisture, with growth reductions from competition limited to dry sites for white spruce and to mesic sites for lodgepole pine. Although we did not identify a systematic advantage for either ground-based or canopy-based competition indices, indices that were centred on the subject tree tended to perform better than plot-based indices that were not. Overall, our comparison showed that canopy-based metrics such as mean canopy height can be at least as effective as traditional ground-based metrics for measuring the effects of local competition on tree growth. As a new research tool in forest ecology, UAVs thus offer a valuable approach for measuring neighbourhood crowding and its effects on the performance of individual trees. © 2020 Elsevier B.V.
关键词	Aerial photography Antennas Ecology Indexing (materials working)Soil moisture Unmanned aerial vehicles (UAV)Canopy structure Competition index Picea glauca Pinus contorta Tree growth Forestry coniferous tree data set growth index method neighborhood satellite data satellite imagery soil moisture tree unmanned vehicle Air Craft Competition Data Ecology Forestry Picea Glauca Pinus Contorta Trees Picea glauca Pinus contorta
语种	英语
来源机构	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/132972
推荐引用方式 GB/T 7714	Vanderwel M.C.,Lopez E.L.,Sprott A.H.,et al. Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth[J]. Forest Ecology and Management,2020,461.
APA	Vanderwel M.C.,Lopez E.L.,Sprott A.H.,Khayyatkhoshnevis P.,&Shovon T.A..(2020).Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth.,461.
MLA	Vanderwel M.C.,et al."Using aerial canopy data from UAVs to measure the effects of neighbourhood competition on individual tree growth".461(2020).