Canadian Forest Service Publications

Developing a forest inventory approach using airborne single photon lidar data:from ground plot selection to forest attribute prediction

Year: 2021

Issued by: Pacific Forestry Centre

Catalog ID: 40639

Language: English

Availability: PDF (request by e-mail)

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Abstract

An increasing number of jurisdictions are integrating airborne laser scanning (ALS) into forest inventory programs to produce spatially explicit and accurate inventories of forest resources. However, wall-to-wall ALS coverage relative to the total area of managed forest remains limited in large forest nations such as Canada, where in logistics, cost and acquisition capacity can be limiting factors. Technologies such as single photon light detection and ranging (SPL) have emerged commercially, which have the capacity to provide efficient ALS acquisitions over large areas and with a greater point density than conventional linear-mode ALS. However, the large-scale operational application of SPL in a forest inventory still needs to be effectively demonstrated. In this study, we used wall-to-wall SPL data (collected with a Leica SPL100) across a 630 000 ha boreal forest in Ontario, Canada to develop a forest inventory. Specifically, we used a structurally guided sampling approach enabled via a principal component analysis of the SPL100 data to establish a network of 250 ground plots. Random forest models were then used to produce area-based estimates of forest attributes of interest. Results demonstrated that the sampling approach enabled the optimization and enhancement of the existing plot network by extending the range of sampled structural types and reducing the number of plots in oversampled forest types. Moreover, Lorey’s height, basal area, quadratic mean diameter at breast height, stem density, gross and merchantable volume and above-ground biomass were estimated with a relative root mean square error of 8.5, 19.76, 13.97, 30.82, 21.53, 23.79 and 22.87 percent, respectively, and relative bias