Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring

Abstract

Forest inventories are constrained by resource-intensive fieldwork, while unmanned aerial systems (UASs) offer rapid, reliable, and replicable data collection and processing. This research leverages advancements in photogrammetry and market sensors and platforms to incorporate a UAS-based approach into existing forestry monitoring schemes. Digital imagery from a UAS was collected, photogrammetrically processed, and compared to in situ and aerial laser scanning (ALS)-derived plot tree counts and heights on a subsample of national forest plots in Oregon. UAS- and ALS-estimated tree counts agreed with each other (r2 = 0.96) and with field data (ALS r2 = 0.93, UAS r2 = 0.84). UAS photogrammetry also reasonably approximated mean plot tree height achieved by the field inventory (r2 = 0.82, RMSE = 2.92 m) and by ALS (r2 = 0.97, RMSE = 1.04 m). The use of both nadir-oriented and oblique UAS imagery as well as the availability of ALS-derived terrain descriptions likely sustain a robust performance of our approach across classes of canopy cover and tree height. It is possible to draw similar conclusions from any of the methods, suggesting that the efficient and responsive UAS method can enhance field measurement and ALS in longitudinal inventories. Additionally, advancing UAS technology and photogrammetry allows diverse users access to forest data and integrates updated methodologies with traditional forest monitoring.

Multi-Scale Remote Sensing-Assisted Forest Inventory: A Glimpse of the State-of-the-Art and Future Prospects

“…Motivated by the recent trends and global interest, the Remote Sensing special issue "Remote Sensing-Based Forest Inventories from Landscape to Global Scale" hosted nine peer-reviewed papers adopting various modern applications of passive and active remote sensing data for multi-scale forest inventory applications. This special issue is enriched with a series of independent, though contextually related, recent studies from diverse geographical domains of the globe, including the near-Arctic Canada [10], Northern United States [11,12], Northern Japan [13], Southern Spain [14,15], Central Italy [16], Southern Poland [17] and Western Germany [18].…”

“…In terms of forest attributes under focus, again, the published papers within this special issue covered a range of essential forest entities for inventory as well as for monitoring. Allometric tree and stand attributes were given considerable attention, with the aboveground biomass (AGB) being modelled in three of the nine studies [13][14][15], followed by growing stock [18], basal area [10] and tree height [10,11,13]. A remarkable insight was especially given by [15], who applied metrics from ALS for simultaneous estimation of soil organic carbon and the AGB, pertaining these together as essential stand characteristics that can be largely affected by thinning.…”

“…A remarkable insight was especially given by [15], who applied metrics from ALS for simultaneous estimation of soil organic carbon and the AGB, pertaining these together as essential stand characteristics that can be largely affected by thinning. Moreover, high-resolution canopy-related spectral and ALS-derived attributes were also leveraged by [11] to estimate tree count across canopy cover classes (with r 2 reaching 0.93 when using ALS metrics), whereas medium-resolution but multi-temporal classifications of forest and tree species types by [17] returned promising performances of accuracies >80% by incorporating refinements like topography and stratification. Spectral information from multi-temporal, optical Landsat imagery was also shown by [16] to enable good approximations for forest recovery via the use of multiple vegetation indices, highlighting the tremendous information content within the time series of medium-resolution satellite imagery for monitoring forest stand dynamics on a regional scale and beyond.…”

“…Last but not least, the studies published within this special issue addressed the use of data from various sensor types, both from passive and active as well as from mono-and multi-temporal domains. A major emphasis was put on sole or combined use of ALS point clouds [11,[13][14][15]18], which is a prudent choice when dealing with the inventory of forest structural variables on landscape to regional scales. Moreover, very high resolution, often mono-temporal satellite imagery (UAV and aerial photogrammetry, WorldView-3 data), was employed by [10,11,13], which mainly aimed at quantifying local forest structural details at high geometric resolutions.…”

“…A major emphasis was put on sole or combined use of ALS point clouds [11,[13][14][15]18], which is a prudent choice when dealing with the inventory of forest structural variables on landscape to regional scales. Moreover, very high resolution, often mono-temporal satellite imagery (UAV and aerial photogrammetry, WorldView-3 data), was employed by [10,11,13], which mainly aimed at quantifying local forest structural details at high geometric resolutions. High-resolution optical data, including RapidEye and SPOT with geometric resolutions <10 m, were applied by [18], whereas medium-resolution (Landsat and Sentinel-2 series) [12,16,17] and low-resolution [14] data were also represented, mainly due to their proven ability for monitoring forest dynamics over timespans.…”