Cotton crop condition was assessed from an analysis of multispectral aerial video imagery. Visible-near infrared imagery of two cotton fields
was collected towards the end of the 1990 crop. The digital analysis
was based on image classification, and the accuracies were assessed
using the Kappa coefficient of agreement.
The earliest of three images proved to be best for distinguishing
plant variety. Vegetation index images were better for estimating
potential yield than the original multispectral image; so too were
multi-channel images that were transformed using vegetation indices
or principal component analysis. The seedbed preparation rig used,
the nitrogen application rate and three plant varieties, a weed species
and two cotton cultivars, could all be discriminated from the imagery.
Accuracies were moderate for the discrimination of plant variety,
tillage treatment and nitrogen treatment, and low for the estimation of
potential yield.
| Identifer | oai:union.ndltd.org:ADTP/219025 |
| Date | January 1991 |
| Creators | Hodgson, Lucien Guy, n/a |
| Publisher | University of Canberra. Applied Science |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | ), Copyright Lucien Guy Hodgson |
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