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Please cite this dataset as follow:

Cunliffe, A., Myers-Smith, I., Kerby, J., Assmann, J., & Daskalova, G. (2020). Canopy height, spectral reflectance (NDVI), and aboveground biomass of Salix richardsonii across a wet graminoid-shrubland ecotone on Qikiqtaruk - Herschel Island, Yukon, Canada (2016) (Version 1.0) [Data set]. UK Polar Data Centre, Natural Environment Research Council, UK Research & Innovation. https://doi.org/10.5285/61C5097B-6717-4692-A8A4-D32CCA0E61A9

Methodology:

We have conducted our study at one of the key sites for ecological monitoring in the circumpolar Arctic. Tundra communities on Qikiqtaruk - Herschel Island in the Canadian Arctic range from graminoid- to shrub-dominated, and are underlain by organic soils and ice rich permafrost. This site has undergone marked ecological changes in community composition, increases in canopy height and vegetation abundance, decreases in bare ground, and an advance in leaf emergence and flowering over the 18 years of ecological monitoring to date (Myers-Smith et al., 2019). We established a ca. 2 ha-1 site across a graminoid-shrub ecotone at the edge of a willow shrub dominated alluvial plain (69.34N, 138.53W).

To constrain the photogrammetric modelling and locate the point clouds in a coordinate reference system, 26 ground control markers (265 mm x 265 mm) were deployed across the site and geolocated to a relative 3D accuracy of <0.015 m with RTK-GNSS equipment (Leica GS10). Coordinates were relative to a local benchmark, geolocated in absolute terms to ±0.003 m in X and Y. and ±0.008 m in Z (95% confidence interval), using the AUSPOS web service. The markers were situated so as to be visible from the air, and a high density of markers facilitated image alignment in the texturally complex scenes. We selected 36 square plots of 50 cm × 50 cm for harvesting. The plots were arranged in a twelve blocks of three replicates across the range of canopy heights to allow a detailed assessment of the form of the allometric relationships. The corners of each harvest plot were geolocated using the GNSS. To minimise sinkage of the GNSS survey staff into the often soft ground, we used a ca. 25 cm2 'foot' on the bottom of the staff to dissipate pressure.

Point Cloud dataset

To obtain aerial images for modelling canopy heights, we used a 24 megapixel camera (Sony alpha6000), equipped with a prime lens (Sony SEL 20 mm F2.8), carried on a Tarot hexacopter controlled with a PixHawk running open source ArduPilot (http://ardupilot.org) software. Two sets of survey flights were undertaken, the first obtaining nadir imagery and the second obtaining oblique (ca. 20 degrees from nadir) images with a spatial grain of ca. 4-6 mm at the canopy top (Cunliffe and Anderson, 2019). The camera was triggered by the flight controller based on distance travelled, with both sets of flights together capturing > 22 photos for every part of the study area yielding (equivalent to forward overlap of 75% and sidelap of 65% for each flight). We collected 673 RGB photographs over our survey area. Image data were originally recorded in lossless RAW format (Sony ARW), and were converted to uncompressed TIFF using Sony's Image Data Converter (v4).

These aerial images were processed using structure-from-motion photogrammetry, using a high performance workstation and a workflow based on Cunliffe et al. (2016). Geotagged image data and marker coordinates were imported into Agisoft PhotoScan (v1.2.4) and converted into a common coordinate reference system (WGS84 UTM 7N; EPSG:32607). Image sharpness was assessed using PhotoScan's image quality tool, which assesses the sharpness of the sharpest part of each photograph; all images had a sharpness of > 0.77. Photos were matched and cameras aligned, using the highest quality setting, key point limit of 100,000; unlimited tie points, generic and reference pair preselection enabled, and adaptive camera model fitting disabled. Reference parameters were set to: camera location accuracy was set to 25 m; marker location accuracy was set to 0.01 m; marker projection accuracy was set to 2 pixels; tie point accuracy was set to 1.

The sparse cloud was filtered and tie points with reprojection error above 0.55 were excluded from further analysis. An operator reviewed the estimated camera positions to verify their plausibility and remove an...(64)

Data collection:

Red-green-blue images collected on 25th of July, 2016. Coordinates collected between June and August 2016. Images for normalised difference vegetation index (NDVI) maps collected in July 2018. Biomass harvests conducted in July & August 2016.