## 2 Materials and Methods
### Single-Antenna versus Dual-Antenna GNSS/INS Heading Precision Experiment
Once the datum coordinates for the reference station were determined, the RTK baselines were used to produce 2-3 cm accurate datum coordinates for the GCPs. A localized transverse Mercator projection centered at the reference station with a height-derived scale factor was applied to the GCP horizontal datum coordinates to produce ground-referenced coordinates. Applanix POSPac UAV software (Applanix, Richmond Hill, Canada) was used to post-process the APX-18 GNSS/INS data with the static reference station GNSS data to produce two separate smoothed best estimate trajectories (SBETs) for each of the four missions. The horizontal and vertical datum parameters and reference station coordinates were input into POSPac. The first processing run had the GAMS functionality enabled. GAMS utilizes the GNSS observations from both antennas in order to leverage the GNSS compass observations within the resulting trajectory estimates. The second processing run had the GAMS functionality disabled with GNSS observations used from only the primary antenna. The SBET position and orientation estimates including the associated precisions were exported to an ASCII file after each processing run. The ASCII trajectory files and the collected lidar data were then processed with OpenMMS software (OpenMMS, Moose Jaw, Canada) to generate two true-color georeferenced point clouds for each mission. The same localized transverse Mercator projection applied to the GCPs was used to produce ground-referenced coordinates for the point clouds. A vertical accuracy assessment was performed on each georeferenced point cloud by comparing the RTK-surveyed GCPs with the nearest lidar point within the point cloud. The assessment followed the American Society for Photogrammetry and Remote Sensing (ASPRS) Positional Accuracy Standards for Digital Geospatial Data [28]. No obvious systematic errors were observed within the point clouds. The lever-arm offsets between the origin of the lidar sensor and the center of the GNSS/INS sensor were taken from the hardware dimensions within the OpenMMS documentation with a measurement precision of 0.1-0.2 cm [26]. The lever-arm offsets between both the primary and secondary GNSS antennas and the center of the GNSS/INS sensor were determined by a total station survey using angular intersections. This led to measurement precisions of less than 1 cm. The boresight rotations for both the lidar sensor and the camera with respect to the GNSS/INS sensor's navigation reference frame were estimated as part of the first mission (i.e., flight A). Specifically, the flight A trajectory file with GAMS enabled was used within the boresight calibration procedures. The estimated boresight rotations were then held constant and applied within the processing of the remaining flights. The lidar sensor boresight calibration utilized a parametric least-squares (PLS) optimization of the RMS errors for planar surfaces found in areas of the point cloud that were observed within overlapping flight lines. Similarly, the camera boresight calibration utilized a PLS optimization of the residuals between the camera's GNSS/INS-derived exterior orientation parameters (EOPs) and the EOPs resulting from a photogrammetric bundle adjustment. The details of the boresight calibration methods are beyond the scope of this study; see [26] for further information. The generated point clouds were not adjusted by using any additional alignment techniques (e.g., strip adjustment) as they were observed as being well-aligned.