Rule-based classification models: flexible integration of satellite imagery and thematic spatial data

A framework for automated land-cover classification based on a concept of a classification model was developed and tested. The framework employs a user-specified rule base to describe a classification model, defined as the series of spatial data operations and decisions used in landcover classification. Both evidential and hierarchical inference are supported utilizing a set of spatial data operators. The concept was tested through the development and application of a set of computer programs which support classification models. A rule base, thematic spatial data, and satellite image data were then used to define a classification model. The classification model approach resulted in statistically significant, 15% improvements in classification accuracy when averaged across different analysts, geographic areas, and years. -from Authors