# Inter-Annual Variability of Peatland Vegetation Captured Using Phenocam- and UAV Imagery
## 2 Materials and Methods
### UAV Data  
#### 2.2.1 Data Collection  
UAV surveys were conducted over the 2018, 2019 and 2021 growing seasons (April to October) using a custom-built hexacopter developed by the Airborne Research and Innovation facility (University of Edinburgh), based around the Tarot T680 Pro airframe (WenzhouTarot Aviation Technology Co., Wenzhou, China) and a 3 DR Pixhawk flight controller running ArduPilot firmware ([[http://www.ardupilot.org](http://www.ardupilot.org)]([http://www.ardupilot.org](http://www.ardupilot.org)), accessed on 15 October 2017). Due to the global pandemic, no sampling was conducted during 2020. Repeat surveys were flown over a 0.05 km\({}^{2}\) area (see Figure 1), following a fixed flight path with 80% front- and side-lap, programmed using the Mission Planner software (v1.3.5, ArduPilot). Analysis of historical data identified this as the dominant source area for CO\({}_{2}\) fluxes measured at the site, allowing for a comparison of greenness and flux data.  
Surveying was limited to days with specific meteorological conditions in an attempt to collect the best-quality imagery [68; 69]. These were days with: (i) low wind-speeds (<10 m s\({}^{-1}\)) to reduce blur and limit movement of the vegetation canopy; and (ii) stable meteorological conditions (e.g., consistent clear skies or overcast conditions) to reduce effects of variable scene illumination. Furthermore, all UAV surveys were conducted within 2 h of solar noon to limit the impact of shadow on the collected imagery.  
Multispectral data were collected using a Parrot Sequoia camera (Parrot Drones SAS, Paris, France) mounted on the UAV to acquire images in the green, red, red-edge, and near infra-red (NIR) bands (see Table 1). This camera consists of two components: (i) a downward-facing lens, which captures imagery of the surveyed scene; and (ii) a skyward-facing incident light sensor (Parrot Sequoia Sunshine Sensor), which automatically corrects measured reflectance by recording changes in incoming irradiance. Before and after each flight, spectral calibration data were collected by taking an image over a panel of known reflectance (50%, SphereOptics GmbH,  
Figure 1: Study site overview. Panel **(a)** shows an aerial image of Auchencorth Moss alongside the UAV survey area (yellow box), with the location of the meteorological measurement mast (star), flux measurement tower and phenocam (circle) as well as its field of view (dotted lines) shown for reference. Panel **(b)** shows the employed species-level classification of the UAV survey area (see [70]). Map tile **(a)** by the Microsoft® BingTM Maps Platform API (Microsoft Corporation, Redmond, WA, USA), under General Rights and Restrictions for Prints. Data by OpenStreetMap, under ODbL.  
Prior to conducting the first survey in 2018, a series of permanent markers were placed within the chosen survey area. These consisted of 10 Ground Control Points (GCPs) to allow captured imagery to be geo-referenced, and five Check Points (CPs) to calculate the geolocation accuracy of produced maps. The exact location of each marker was measured using a high-precision Global Navigation Satellite System (GNSS; GPS500, Leica Geosystems AG, St. Gallen, Switzerland) to an accuracy of <2 cm. All markers were regularly monitored throughout the growing season and cleared of overgrowing vegetation.