Abstract

Aerial drones enable detailed three-dimensional terrain and vegetation canopy reconstructions supporting a diverse set of environmental monitoring applications. Small drone-derived photogrammetric datasets (<5 km2) often extend field-scale observations and enable calibration and validation for satellite-based mapping. Applications usually require data over much larger areas or in remote areas such as the Arctic, yet large-area drone datasets are rare due to aviation regulations usually stipulating that missions adhere to within-visual-line-of-sight (VLOS) conditions. Terrain and vegetation canopy reconstruction based on longer-range drone missions requires evaluation to justify future beyond-visual-line-of-sight (BVLOS) data initiatives. This work analyzed BVLOS drone photogrammetric datasets for terrain and vegetation height applications along a forest-tundra ecotone (FTE) spanning 396 km in northern Canada. Specifically, we: 1) performed validation assessments of derived terrain models and canopy height models, and 2) investigated remote sensing applications supported by BVLOS data in a FTE experiencing the effects of climate change. The BVLOS data covered in excess of 550 km2, increasing conventional drone data coverage by two orders of magnitude. Elevation validation indicated that strong agreement with GNSS benchmarks, Airborne Laser Scanning (ALS) and VLOS drone data (0.15–0.19 m RMSE) is possible, and that vertical RMSEs <2x the image spatial resolution is achievable. To validate vegetation canopy height modelling capabilities, comparisons with NASA's Land, Vegetation, and Ice Sensor (LVIS) full-waveform ALS observations indicated satisfactory agreement for height metrics (R2 = 0.7 to 0.8, RMSEs <1.0 m). Canopies were reconstructed at fine spatial scales, which in turn supported a unique comparison of vegetation height distributions between six land-cover classes and ecoregions along the FTE, and identified discrepancies in how national and international canopy height models represented the FTE. Detected terrain subsidence, including retrogressive thaw slumping and ice-wedge degradation, illustrated how climate-driven permafrost thaw is modifying landscapes and placing infrastructure at increased risk, which requires intensive monitoring. These applications demonstrated how BVLOS-derived data enables broader scale assessments of regional vegetation structure and terrain changes across larger spatial extents than previously possible with VLOS drones. Mapping opportunities will arise in the environmental remote sensing discipline as drone systems are increasingly operated beyond visual range.

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