(a) (b) (c)
Figure 1. Schematic of UAS imaging and processing: (a) setup for field
mapping based on flight waypoints and signal communication, (b)
conventional gridding by image rotation, and (c) adaptive gridding by
grid rotation.
The orthomosaic image is processed for plot-level metrics extraction on
a large number of plots by defining a grid that is spaced by rows and
columns of the total number of plots and by processing sub-ROIs in the
grid. Conventional gridding offered by commercial software (e.g.,
FIELDimageR) requires image rotation to achieve an upright rectangular
field so that the grid is aligned with the field and computed by row
(i ) and column (j ) of image coordinates (Fig. 2a).
Adaptive gridding algorithm is to eliminate the image rotation and
instead simply rotate the grid (Fig. 2b) that is aligned with the
rotated field and extract metrics from the rotated sub-ROIs.
2.1 Grid rotation
A rotated grid is drawn by rotating an outer ROI over the field boundary
and adding internal horizontal and vertical lines at the rotation angle
within the outer ROI. The grid rotation is implemented by applying a
geometric property of a rectangle
in a circle that keeps right angles at four corners when the inner
rectangle is rotated and reshaped within a circle by pivoting two
diagonal corners. When two diagonal cornersA (i 1, j 1) andC (i 2, j 2) are
known, therefore, the other two diagonal cornersB (i 3, j 3) andD (i 4, j 4) are
uniquely defined with an arbitrary i along the circumference
(Fig. 2a) by using Eqs. (1) and (2).