Canadian Forest Service Publications

A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area based approach. 2013. White, J., Wulder, M., Whitehead, R. BC Forest Professional 20(6):20-21.

Year: 2013

Issued by: Pacific Forestry Centre

Catalog ID: 35300

Language: English

Availability: PDF (download)

Mark record


Airborne laser scanning (ALS; also referred to as Light Detection and Ranging or LiDAR) can map terrain and forest canopy structure at higher accuracy and finer resolution than air photo interpretation (Figure 1). Many forest companies have realized cost reductions by using ALS data in operational planning and there is growing interest in using ALS data to produce enhanced forest inventories (EFI). For more information on EFI, readers can refer to the January – February 2013 issue of BC Forest Professional (Operational Implementation of LiDAR for Forest Inventory Purposes in Ontario, p. 14). Recently, Western Forest Products and BC Timber Sales shared the cost of acquiring ALS data for more than 100,000 hectares of forest land on northern Vancouver Island, and are partnered with the Forest Analysis and Inventory Branch to ensure the EFI will meet vegetation resources inventory (VRI) standards.

Plain Language Summary

Airborne Laser Scanning (ALS) data—also known as Light Detection and Ranging (LiDAR)—enables the accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed digital elevation models and the estimation of a range of forest inventory attributes (e.g., height, basal area, and volume). A best practices guide brings together state-of-the-art approaches, methods, and data to provide non-experts more detailed information about complex topics. With this guide, our goal is to inform and enable readers interested in using ALS data to characterize, in an operational forest inventory context, large forest areas in a cost-effective manner. The best practices presented in the guide are based on more than 25 years of scientific research. In this document we describe the process required to generate forest inventory attributes from ALS data from start to finish, recommending best practices for each stage, from ground sampling and statistics, through to sophisticated spatial data processing and analysis. As the collection of ground plot data for model calibration and validation is a critical component of the recommended approach, we have placed appropriate emphasis on this section of the guide.