Canadian Forest Service Publications
Moving toward consistent ALS monitoring of forest attributes across Canada: A consortium approach. 2013. Hopkinson, C.; Chasmer, L.; Colville, D.; Fournier, R.A.; Hall, R.J.; Luther, J.E.; Milne, T.; Petrone, R.M.; St-Onge, B. Photogrammetric Engineering and Remote Sensing 79(2):159-173.
Issued by: Northern Forestry Centre
Catalog ID: 34347
As airborne laser scanning (ALS) gains wider adoption to support forest operations in Canada, the consistency and quality of derivative products that support long-term monitoring and planning are becoming a key issues for managers. The Canadian Consortium for Lidar Environmental Applications Research (C-CLEAR) has supported almost 200 projects across Canada since 2000, with forest-related studies being a dominant theme. In 2010 and 2011, field operations were mobilized to support 13 ALS projects spanning almost the full longitudinal gradient of Canada’s forests. This paper presents case studies for seven plus an overview of some best practices and data processing workflow tools that have resulted from these consortium activities. Although the projects and research teams are spread across Canada, the coordination and decade of experience provided through C-CLEAR have brought common methodological elements to all. It is clear that operational, analytical and reporting guidelines that adhere to community accepted standards are required if the benefits promised by ALS forestry are to be realized. A national Lidar Institute that builds upon the C-CLEAR model and focuses on developing standards, guidelines, and certified training would address this need.
Plain Language Summary
The use of airborne laser scanning (ALS), also known as LiDAR (Light Detection And Ranging), to meet the needs for a range of forestry information has grown immensely in recent years. How we acquire ALS data, however, can cause considerable differences in estimates of forest canopy attributes. The consistency and quality of data and information produced are important issues for the forest industry and forest research. This paper reviews seven case studies from 13 Canadian projects, clearly demonstrating differences in the ways data were acquired and processed by software, as well as in the measurements obtained and the models developed. The paper calls for standards and guidelines to promote more consistent acquisition, processing, and analyses of ALS data for forestry applications. Such standards would be particularly relevant to determining relationships between ALS data and forest attributes based on field plots and stand-level data, and to studies assessing disturbance or monitoring growth and the productivity of ecosystems. This paper also suggests creating a national ALS institute to serve as a clearing-house for lessons learned and to support the national community by fostering collaboration, knowledge transfer, training, and outreach.