Automated GIS integration in landcover classification

This paper describes a system which allows the integration of traditional spectral-based classifiers with geographic information system technologies, but which greatly reduces analyst input. Spectral data, non-spectral spatial data, tabular, descriptive, and declarative data can be flexibly integrated in a landcover classification. A "classification model' is described via a rule-base, which may be modified incrementally. Spatial data operators are provided, such as class restriction based on thematic data and spectral likelihood classification. A test of this system in northeastern Wisconsin resulted in a significant improvement in classification accuracies when compared to a traditional maximum likelihood classification. -from Authors