Site-Specific Nutrient, Lime and Seed Management 3
Drummond Centre (3)
Tue, Jun 26, 2018
3:30 PM to 5:00 PM
Conventional techniques (e.g., intensive soil sampling) for site-specific management zones (MZ) delineation are often laborious and time-consuming. Using drones equipped with hyperspectral system can overcome some of the disadvantages of these techniques. The present work aimed to develop a drone-based hyperspectral imagery method to characterize the spatial variability of soil physical properties in order to delineate site-specific MZ. Canonical correlation analysis (CCA) was used to extract the most related wavelengths to the soil physical properties based on hyperspectral imagery. The selected spectral bands were 540, 704 and 816 nm. These bands were processed using an object-based image analysis (OBIA) technique to delineate two homogenous zones. A Student’s t-test at the 5% significance level showed that these zones are statistically different in the physical soil properties. Also, a comparison between the extracted zones with the MZ obtained from the apparent soil electrical conductivity stratification yield very similar results. The results of this study suggested that MZ delineation using drone-based hyperspectral data can be a promising alternative to conventional techniques such as intensive soil sampling grid and soil proximal sensors.