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.