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Percent ground cover of vegetation is an important parameter for crop management. An innovational method based on features of objects was presented to automatically estimate percent ground cover of winter wheat from digital image analyses. Based on the features of wheat and its background components, an algorithm was designed to extract the percent ground cover, and the corresponding program was developed. This method was simple, labor–and time–saving with high classification accuracy about 90', and the method combined the advantages of ISODATA method and maximum likelihood method. Finally the error source of automatic classification and scope of application were analyzed, and some approaches of improving accuracy of classification were discussed.

Automated Digital Image Analyses For Estimating Percent Ground Cover of Winter Wheat Based on Object Features