# UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health
## 2 Methods
### UAV Imagery  
The UAV dataset used in this study was originally described in [12]. A co-axial quad-copter UAV was used for all data collection. The craft was a modified version of the Aeronavics (Aeronavics, Ragland, New Zealand www.aeronavics.co.nz) Skylib heavy-lift airframe. This craft had a flying time of around 15 min. with a payload of approximately 5 kg and provided a stable platform even in strong, turbulent winds. A single flight plan was used for all data collections to minimise variance associated with campaign settings. The flight plan used 18 flight lines to cover the area of interest and ensured that all craft manoeuvres and altitude adjustments occurred outside of the study area to minimise flight-related artefacts in the data collected. The original intent was to collect imagery on a weekly basis as the weather conditions permitted. In the end, data collection was significantly sparser due to technical difficulties and poor weather resulting in nine separate acquisitions between 30 October 2015 and 3 March 2016.  
A series of nine ground control points (GCPs) were established around the study area and fixed using a Trimble Geo7X GNSS receiver (Trimble Navigation Ltd., Sunnyvale, CA, USA). Positions were differentially corrected using a network of local continuously operating reference stations maintained by Land Information New Zealand (LINZ). The targets established at the ground control points were easily manually identified in the multispectral imagery. The GCPs were used to accurately georectify all UAV imagery [12].  
Narrowband multispectral imagery was collected using a MicaSense RedEdge 3 camera (Micasense, WA, USA). The camera provides imagery in five narrow bands (blue = 455-495 nm, green = 540-580 nm, red = 658-678 nm, red edge = 707-727 nm and near-infrared = 800-880 nm) (Figure 1) via five separate imaging units that operate nearly simultaneously. The camera has a lens focal length of 5.5 mm and field of view of 87.4\({}^{\circ}\). The camera was housed in a gimbal to ensure nadir orientation of the camera during data collection. The flight plan ensured cross-track and along-track overlap of 85 % and a calibrated reflectance panel was imaged directly before and after each flight and used for reflectance calibration using the empirical line method [53]. The UAV imagery was collected from a flying altitude of approximately 90 m above the local terrain and resulted in a ground sample distance (GSD) of 6 cm. Imagery acquisition was limited to within two hours either side of local solar noon to minimise shadows.  
The imagery was exported from the MicaSense RedEdge 3 in 12-bit RAW format. These images were mosaicked into a single, multi-band image covering the entire study area. The raw digital numbers (DNs) were converted into reflectance values using the calibrated reflectance panel. The relationship between DNs and the natural logarithm of the image surface reflectance is linear and the y-intercept can be interpreted as the minimum surface reflectance that can be detected for each wavelength band [53]. This can then be used to develop a regression equation to convert DNs to reflectance values using a calibration equation [54]. Images were georectified using the GCPs recorded within the study site and visible in the imagery [12].