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1 November 2004 Using landscape characteristics as prior information for Bayesian classification of yellow starthistle
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Yellow starthistle is an invasive plant of canyon grasslands in north-central Idaho. The distribution of yellow starthistle is associated with general landscape characteristics that include land use and specific terrain-related features such as elevation, slope, and aspect. Slope and aspect can be considered as indicators of plant community composition and distribution. Hence, these variables may be incorporated into prediction models to estimate the likelihood of yellow starthistle occurrence because plant communities differ in susceptibility to invasion. An empirically derived nonlinear model based on landscape characteristics has previously been developed to predict the likelihood of yellow starthistle occurrence in north-central Idaho. Although the model was used to predict the invasion potential of yellow starthistle into new areas, it could also be used as auxiliary data for classifying this weed species in remotely sensed imagery. To accomplish this, the predicted values from the model are regarded as prior information on the presence of yellow starthistle. A Bayesian image classification algorithm using this prior information is then applied to a corresponding set of remotely sensed data. This results in a map indicating the posterior probabilities of yellow starthistle occurrence given the landscape characteristics. This technique is demonstrated and is shown to reduce omissional error rates by 50% when the landscape characteristics are incorporated into the classification process.

Nomenclature: Yellow starthistle, Centaurea solstitialis L. CENSO.

Bahman Shafii, William J. Price, Timothy S. Prather, Lawrence W. Lass, and Donald C. Thill "Using landscape characteristics as prior information for Bayesian classification of yellow starthistle," Weed Science 52(6), 948-953, (1 November 2004).
Received: 24 February 2004; Accepted: 1 July 2004; Published: 1 November 2004

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