A Comparison of Airborne Laser Scanning and Image Point Cloud Derived Tree Size Class Distribution Models in Boreal Ontario

被引:32
作者
Penner, Margaret [1 ]
Woods, Murray [2 ]
Pitt, Douglas G. [3 ]
机构
[1] Forest Anal Ltd, Huntsville, ON P1H 2J6, Canada
[2] Ontario Minist Nat Resources & Forestry, Forest Resource Inventory Unit, North Bay, ON P1A 4L7, Canada
[3] Nat Resources Canada, Canadian Wood Fibre Ctr, Canadian Forest Serv, Sault Ste Marie, ON P6A 2E5, Canada
来源
FORESTS | 2015年 / 6卷 / 11期
关键词
airborne laser scanning (ALS); LiDAR; forest inventory; image point cloud (IPC); semi-global matching (SGM); diameter distribution; parametric; nonparametric; DIAMETER DISTRIBUTIONS; FOREST INVENTORY; CANOPY HEIGHT; LIDAR; ATTRIBUTES; VARIABLES; STANDS;
D O I
10.3390/f6114034
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Airborne Laser Scanning (ALS) metrics have been used to develop area-based forest inventories; these metrics generally include estimates of stand-level, per hectare values and mean tree attributes. Tree-based ALS inventories contain desirable information on individual tree dimensions and how much they vary within a stand. Adding size class distribution information to area-based inventories helps to bridge the gap between area- and tree-based inventories. This study examines the potential of ALS and stereo-imagery point clouds to predict size class distributions in a boreal forest. With an accurate digital terrain model, both ALS and imagery point clouds can be used to estimate size class distributions with comparable accuracy. Nonparametric imputations were generally superior to parametric imputations; this may be related to the limitation of using a unimodal Weibull function on a relatively small prediction unit (e.g., 400 m(2)).
引用
收藏
页码:4034 / 4054
页数:21
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