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DOI	10.1016/j.rse.2020.111770
	Detection of sub-canopy forest structure using airborne LiDAR
	Jarron L.R.; Coops N.C.; MacKenzie W.H.; Tompalski P.; Dykstra P.
发表日期	2020
ISSN	00344257
卷号	244
英文摘要	Knowledge on forest structure is vital for sustainable forest management decisions. Currently, Airborne Laser Scanning (ALS) has been well established as an effective tool to delineate and characterize the structure of canopies across a range of forested biomes. However, the use of ALS to provide information on sub-canopy structure is less well developed. Sub-canopy structure consists of suppressed mature trees, regenerating tree saplings, shrubs, herbs, snags and coarse-woody-debris. With the increasing density of ALS point clouds, new opportunities exist to describe these sub-canopy structural components in forests that were previously difficult to detect using passive remote sensing technologies. In this research we use discrete return ALS data acquired at a density of 23 points × m2 to estimate sub-canopy forest structure for 48,000 ha of conifer dominated forest in central British Columbia, Canada. We first segmented the forest vertical structure into canopy and sub-canopy based on Lorey's mean height (HL). HL, which favours larger trees as a baseline for canopy height, provides separation between the taller trees that dominate the canopy and smaller trees that represent the sub-canopy. We defined sub-canopy trees as those <70% of HL. Both ground-truthed forest inventory data and the ALS point cloud were then segmented into canopy and sub-canopy components. A mixture of standard height-based and density-based ALS metrics were then computed to develop predictive models of sub-canopy component of the stands. Models were calibrated with 28 ground plots and developed using stepwise regression with the strongest predictors being a combination of height, structure and cover-based metrics. Two model sets were developed, one for the entire point cloud, and another for an isolated sub-canopy point cloud defined by HL. The isolated sub-canopy set of models resulted in stronger cross-validated R-squared values of 0.88, 0.68, and 0.55 for tree volume, basal area and number of sub-canopy trees, respectively. We then applied these models over the entire study area to characterize the sub-canopy structure, resulting inventory can be used by land managers for a number of purposes including selecting candidate locations for selective logging to preserve mid-term timber opportunities, fire susceptibility and carbon sequestration modelling, and wildlife habitat values. © 2020
英文关键词	Canopy; Forest inventory; Forest structure; LiDAR; Understorey
语种	英语
scopus关键词	Remote sensing; Airborne Laser scanning; British Columbia , Canada; Carbon sequestration; Forest inventory data; Passive remote sensing; Structural component; Sustainable forest management; Vertical structures; Reforestation; basal area; biome; detection method; Doppler lidar; forest canopy; forest cover; laser method; lidar; remote sensing; satellite data; selective logging; British Columbia; Canada; Coniferophyta
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179322
作者单位	Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada; Ministry of Forests, Lands and Natural Resource Operations, Skeena-Stikine District Office, 3333 Tatlow Rd., Bag 6000, Smithers, British Columbia V0J 2N0, Canada; Ministry of Forests, Lands and Natural Resource Operations, PO BOX 9513, Victoria, British Columbia V8W9C2, Canada
推荐引用方式 GB/T 7714	Jarron L.R.,Coops N.C.,MacKenzie W.H.,et al. Detection of sub-canopy forest structure using airborne LiDAR[J],2020,244.
APA	Jarron L.R.,Coops N.C.,MacKenzie W.H.,Tompalski P.,&Dykstra P..(2020).Detection of sub-canopy forest structure using airborne LiDAR.Remote Sensing of Environment,244.
MLA	Jarron L.R.,et al."Detection of sub-canopy forest structure using airborne LiDAR".Remote Sensing of Environment 244(2020).