Operational implementation of a LiDAR inventory in Boreal Ontario
2011; Canadian Institute of Forestry; Volume: 87; Issue: 04 Linguagem: Inglês
10.5558/tfc2011-050
ISSN1499-9315
AutoresMurray Woods, Doug Pitt, Margaret Penner, Kevin Lim, Dave Nesbitt, Dave Etheridge, Paul Treitz,
Tópico(s)Forest ecology and management
ResumoAn existing Light Detection and Ranging (LiDAR) data set captured on the Romeo Malette Forest near Timmins, Ontario, was used to explore and demonstrate the feasibility of such data to enrich existing strategic forest-level resource inventory data. Despite suboptimal calibration data, stand inventory variables such as top height, average height, basal area, gross total volume, gross merchantable volume, and above-ground biomass were estimated from 136 calibration plots and validated on 138 independent plots, with root mean square errors generally less than 20% of mean values. Stand densities (trees per ha) were estimated with less precision (30%). These relationships were used as regression estimators to predict the suite of variables for each 400 m 2 tile on the 630 000-ha forest, with predictions capable of being aggregated in any user-defined manner—for a stand, block, or forest—with appropriate estimates of statistical precision. This pilot study demonstrated that LiDAR data may satisfy growing needs for inventory data to scale operational/tactical, through strategic needs, as well as provide spatial detail for planning and the optimization of forest management activities.
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