GSA Annual Meeting, November 5-8, 2001

Paper No. 0
Presentation Time: 5:00 PM

GEOLOGICALLY MOTIVATED EXAMPLES OF REMOTE SENSING DATA PROCESSING AND FUSION


KELLER, G. Randy1, XIE, Hongjie2, LANGFORD, Richard2, QUEZADA, Oscar2 and ANDRONICOS, Christopher3, (1)Department of Geological Sciences/ PACES, Univ of Texas at El Paso, El Paso, TX 79968, (2)Department of Geological Sciences, Univ of Texas at El Paso, 500 W. University Ave, El Paso, TX 79968, (3)Geological Sciences, Univ of Texas at El Paso, El Paso, TX 79968, keller@geo.utep.edu

Recent years have seen an explosion in geospatial data that contains a wealth of valuable information for geologic studies. At the same time, the complexity of the questions geologists are addressing is also increasing due to many factors. This coincidence is both fortuitous and challenging and requires that we employ all the data and tools at our disposal. An example of a new tool is JPL/NASA’s AIRSAR/TOPSAR, a multipolarimetric, multiwavelength, and interferometric airborne synthetic aperture radar capable of imaging in C, L, and P- bands (5.7, 24.5, and 68 cm). However, these data need extra processing before being of maximum geologic utility. We have worked to find the optimal speckle removal, and for banding removal, we derived a new method that we call combined principal components analysis (CPCA) that was very effective with our data. We have investigated signature differences between radar and optical (ETM+) images in west Texas. Data fusion (integration) based on the color transform technique was employed to integrate Landsat 7 (30 m ETM+ data and accompanying 15 m panchromatic data) and TOPSAR data after speckle and banding removal. The resulting fused image brought out new features that were not evident in the original images and helped identify many features whose origin was not clear in the original images. We are using these results to investigate earthquake hazards and water resources in this region. In northern New Mexico, we have addressed a problem that requires the fusion of imagery and geophysical (seismic reflection and gravity) data to address a long-standing question about basement structure. A new approach to the reduction of the strong signature of vegetation facilitated the location of key outcrops of Precambrian rocks in the Sangre de Cristo Mountains in any area that contains a puzzling gravity low. Our combined analysis of the geologic, remote sensing, and geophysical data then revealed that a Precambrian batholith was the best geologic explanation for the observed geophysical signatures.