INTEGRATION AND FORMAL FUSION OF REMOTE SENSING AND GEOPHYSICAL DATA TO OBTAIN SUBSURFACE STRUCTURE: SOME EXAMPLES

The ultimate goal of many studies that employ remote sensing and geoinformatics technologies is to characterize the 3-D structure of a region of interest in order to address key societal, scientific, and engineering questions. In this context, 3-D implies determining the properties of a volume and mapping subsurface features. This can be accomplished by using geophysical techniques and drilling data to measure seismic velocities, density, magnetic properties, electrical properties, anisotropy, seismic attenuation (Q), temperature, etc. and map their distribution via volume elements that can take several forms. In addition, interfaces that represent features such as stratigraphic boundaries, faults, magmatic bodies, etc. must also be mapped in order to properly characterize a region. These goals can only be achieved through a highly integrated approach that takes advantage of all of the geological and geophysical constraints available. Drill holes and geophysical surveys are relatively expensive, and thus, remote sensing data are very valuable to both measure properties of the exposed land surface and as a tool to extrapolate laterally from locations where drilling and geophysical data provide vertical control. We present examples of an integrated approach in which remote sensing data play an important role in both qualitative (overlay of data layers) and quantitative (data fusion) analyses. These applications include an analysis of the Taos trough region of northern New Mexico, a study to find a site for a brine disposal well for a large desalinization project, and a study of Quaternary faulting. The last of these studies involves formal data fusion via a Hue-Saturation-Values (HSV) transformation approach that accomplishes the fusion of surface roughness and shallow subsurface information from Airborne Synthetic Aperture Radar (AIRSAR) data with surface spectral reflectivity from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. The fused image contains new information and brings out new features that are not evident in the original images and also helps to identify many features that are not clear in the original images.