Many upland pastures and forest meadows in the western United States contain significant infestations of yellow hawkweed and oxeye daisy. Documentation of infestations is necessary in order to plan and assess control tactics. Previous work with an airborne charge coupled device (CCD) with spectral filters indicated that flowering yellow hawkweed with at least 30% cover was detectable at 1 m resolution. A single image of a large area may not capture all plants in the flowering phase and multiple images are costly. The objective of this paper was to assess the accuracy of images recorded at different phenological stages. We compared three methods of classification: unsupervised classification of a three principal component analysis image, supervised classification of a three principal component analysis image, and supervised classification of a composited image consisting of four bands and normalized difference near infrared (NIR)/red band. Regardless of the classification method, images of yellow hawkweed and oxeye daisy in full bloom had lower classification error than at early bloom or post bloom. The percent error for yellow hawkweed classification was about twice as high at post bloom as at full bloom, but varied slightly depending on the method of classification and cover class. The ability to detect discrete colonies of yellow hawkweed was not affected by phenological stage, but the ability to measure the area of each cluster differed among stages. Less than one-third fo the pixels classified as yellow hawkweed or oxeye daisy in the early bloom image remained in the same class in the full bloom image. About half the pixels in the full bloom image remained in the 90 to 100% cover class at the post bloom image. Seasonal growth of the grasses masked some yellow hawkweed and oxeye daisy plants, and accounted for differences in classification among phenological stages.