Agricultural applications of high-resolution digital multispectral imagery: evaluating within-field spatial variability of canola (Brassica napus) in Western Australia.

摘要

This paper analyses the potential of a high-resolution, airborne remote sensing system, the Digital Multi-Spectral Imagery (DMSI), for detecting canola growth variability within a field to help farmers for future incorporation of the system into site-specific crop management approaches for agriculture. Transect sampling within a canola field of a broad acre agricultural property in the South West of Western Australia was conducted synchronous with the capture of one-metre spatial resolution DMSI. Four individual bands (blue, green, red and NIR) and five image transformations namely the normalized difference vegetation index (NDVI), normalized difference vegetation index-green (NDVI-green), soil adjusted vegetation index (SAVI), photosynthetic vigour ratio (PVR) and plant pigment ratio (PPR) of DMSI were investigated. Canola density was correlated with the 4 individual bands and 5 image transformations, while leaf area index (LAI) was correlated with the 4 individual bands. The NDVI-green, red and near-infrared bands of DMSI produced the best correlations with the density of canola, whereas the LAI had significant ( alpha =0.05) negative correlations with the blue (-0.93) and red (-0.89) DMSI bands, and a significant positive correlation were found with the near-infrared band (0.82).