Comparison of Orthomosaic Images and Flight-Line Transects for Crop Monitoring By Fixed-Wing Unmanned Aircraft.

The typical workflow for data acquired by unmanned aircraft systems (UAS) is to create structure-from-motion (SfM) point clouds using numerous overlapping images. The SfM point clouds are used to create surface elevation models that are required for generating orthomosaic images. However, the flight duration of UAS is short, so acquisition of overlapping images severely limits the total area covered during a UAS flight. An alternative is flying transects over fields and use each image as a sample point for crop monitoring. In June and July 2014, an InSitu ScanEagle UAS was flown at 450 and 600 m above ground level over six 50-ha fields near Boardman, Oregon, with a Tetracam Mini Multi Camera Array (mini-MCA) with five multispectral bands and an up-looking sensor to correct for changes in solar irradiance. The seasonal progressions of the normalized difference vegetation index (NDVI) for the six fields were similar to the progression of Landsat 8 Operational Line Imager data, showing that corrections using the up-looking sensor worked well for changes of solar irradiance. There were small but noticeable differences in reflectances and NDVI for adjacent transects when the flights were heading in opposite directions (150º versus 330º). The differences in NDVI were averaged in the orthomosaics; therefore, the point transect spectral data may be more accurate. However, the surface elevation models from the SfM point clouds may be used to determine plant heights for estimating crop growth and yield.