Unmanned aerial systems for precision forest inventory purposes: A review and case study

Unmanned Aerial Systems (UAS) are capable of improving the efficiency of acquisition and providing fine spatial scale data for sustainable resource management. In this paper we begin by describing differences between UAS airframes, their successes and limitations, and list contemporary research applications. UAS compatible sensor technologies are discussed, including passive and active sensors. Finally, we detail a case study where UAS updated an Enhanced Forest Inventory (EFI) for a study area in interior British Columbia. Airborne Laser Scanning (ALS) from 2013 and Digital Aerial Photogrammetric (DAP) point clouds acquired using a UAS from 2015 were used to estimate individual tree height and volume increments. A total of 246 trees were detected using Canopy Height Models (CHMs) with 70% of these trees being matched in the ALS and DAP data sets. Mean tree growth between 2013 and 2015 from the CHM and 95th percentile of height (P95) was estimated at 0.68 +/- 0.05 and 0.50 m +/- 0.05 m, respectively. Similarly, mean gross tree volume increments (m(3)) were computed as 0.05 m(3) +/- 0.005 m(3) and 0.03 m(3) +/- 0.005 m3 for the CHM and P95, respectively. The results indicate that information from UAS-DAP point clouds can generate spatially and temporally accurate inventories and have potential to inform a number of sustainable forest management activities.