Kyle Loggenberg

This study proposes a new method of creating precision input data for precision viticulture and autonomous farming applications using remote sensing.

The research presented in Part 2 aims to derive a two-band optimised vegetation index using hyperspectral data captured across the visible near-infrared (VNIR) region of the electromagnetic (EM) spectrum.

This study presents a novel hyperspectral-machine learning methodology for the non-destructive identification of water-stressed vines in a Shiraz vineyard.