Operational implementation of a LiDAR inventory in Boreal Ontario

Author:

Woods Murray1,Pitt Doug2,Penner Margaret3,Lim Kevin4,Nesbitt Dave1,Etheridge Dave5,Treitz Paul6

Affiliation:

1. Ontario Ministry of Natural Resources, Southern Science & Information Section, 3301 Trout Lake Road, North Bay, Ontario P1A 4L7.

2. Canadian Wood Fibre Centre, Canadian Forest Service, 1219 Queen St. E., Sault Ste. Marie, Ontario P6A 2E5

3. Forest Analysis Ltd. RR#4, 1188 Walker Lake Dr., Huntsville, Ontario P1H 2J6

4. Lim Geomatics Inc., P.O. Box 45089, 680 Eagleson Road, Ottawa, Ontario K2M 2G0

5. Ontario Ministry of Natural Resources, Northeast Science & Information Section, P.O. Bag 3020, South Porcupine, Ontario P0N 1H0

6. Department of Geography, Queen's University, Kingston, Ontario K7L 3N6

Abstract

An 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 m2 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.

Publisher

Canadian Institute of Forestry

Subject

Forestry

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