DATA FUSION TECHNIQUES FOR COMBINING SPATIAL STATISTICAL AND REMOTELY SENSED DATA

An analytical method is presented for the fusion of spatial statistical data with traditional remotely sensed imagery. By utilizing data fusion techniques spatial statistical data can be fused with traditional remotely sensed imagery and DEM derived data bands to create new geologically relevant views of an area. This process facilitates a more robust, spatially-centered analytical mode of computational analysis than that presented by traditional visualization techniques and extends the usefulness of fused data sets well beyond that of conventional fused data sets.

Extensive spatial statistical data sets derived from frequency and orientation aggregation of semi-automated lineament extraction analyses are fused with DEM derived geomorphic data, ortho-photo imagery and SPOT and TM7 imagery to produce new data sets which then provide a basis for application of traditional clustering and classification techniques. The derived classes are hybrids between the spatial statistical data and remotely sensed data and represent new geologically relevant views of a particular area. Example analyses are presented for the Wallowa Mountains of northeast Oregon and the adjacent Hell's Canyon area of Washington, Idaho and Oregon.