Updating residual stem volume estimates using ALS- and UAV-acquired stereo-photogrammetric point clouds

ABSTRACT

To improve precision management and the cost effectiveness of forest practices, we investigate a pre-harvest airborne laser scanning (ALS) forest inventory with an unmanned aerial vehicle (UAV) acquired post-harvest digital aerial photogrammetry (DAP) inventory to identify the location and residual volume of stands following selection harvesting. ALS data and field measurements collected pre-harvest in 2013 (T₁) and UAV imagery collected post-harvest in 2015 (T₂) were processed to produce analogous point clouds of the study area near Williams Lake, British Columbia, Canada. Tree height, diameter at breast height (DBH), and species were recorded from systematically located variable radius plots subsequent to ALS and DAP collection. Point cloud metrics and field measurements from each data set were used to create T₁ ALS and T₂ DAP predictive volume models. Direct and indirect volume change estimates were created from the difference between T₁ ALS and T₂ DAP model results. The estimated root mean square error (RMSE) for volume was 17.34% and 18.50% for the 2013 ALS and 2015 DAP models, respectively. The indirect and direct models predicting volume change produced errors of 16.65% and 86.56%, respectively. Results achieved from ALS and DAP models indicate strong potential for inventories generated using UAV-acquired DAP to estimate the quantity and location of residual volume after harvest operations, and could be applied in tandem to act as a semi-automated inventory cycling method to improve operational efficiency and cost effectiveness in Canadian forest management.

Acknowledgements

We thank an anonymous foundation for providing the funding for this research. We thank Spire Aerobotics for acquiring and pre-processing the DAP data. We thank AFRF staff Cathy Koot as well as Tesera Systems staff Dwight Crouse and Ian Moss for providing technical information and ALS data for the study. We thank Jacquelyn Bortolussi for graphical assistance.

Disclosure statement

No potential conflict of interest was reported by the authors.