Mineralogical remote sensing of surface expressions of deep-seated porphyry copper deposits at Safford mining district, Arizona
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Engineering topics
Publications and source records attributed to Abrams, M..
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Studies of the effects of spatial resolution on extraction of geologic information are woefully lacking but spatial resolution effects can be examined as they influence two general categories: detection of spatial features per se; and the effects of IFOV on the definition of spectral signatures and on general mapping abilities.
For a number of years Landsat data have been used to locate areas of iron oxide occurrences which might be associated with hydrothermal alteration zones. However, the usefulness of the Landsat data was restricted because of certain limitations of the spectral information provided by Landsat. A new generation multispectral scanner will, therefore, be carried by the fourth Landsat, which is to be launched in July, 1982. This instrument, called the Thematic Mapper (TM), will have seven channels and provide data with 30 m spatial resolution. Two of the spectral channels (1.6 micron and 2.2 micron) should allow detection of hydrous minerals. Possible applications of Landsat-D TM data for copper exploration were studied on the basis of a comparison of Landsat data with simulated TM data acquired using an aircraft scanner instrument. Three porphyr copper deposits in Arizona were selected for the study. It is concluded that the new Landsat-D TM scanner will provide Exploration geologists with a new improved tool for surveying mineral resources on a global basis.
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Results of a sedimentary rock type discrimination project using Seasat radar and Landsat multispectral image data of the San Rafael Swell, in eastern Utah, are presented, which has the goal of determining the potential contribution of radar image data to Landsat image data for rock type discrimination, particularly when the images are coregistered. The procedure employs several images processing techniques using the Landsat and Seasat data independently, and then both data sets are coregistered. The images are evaluated according to the ease with which contacts can be located and rock units (not just stratigraphically adjacent ones) separated. Results show that of the Landsat images evaluated, the image using a supervised classification scheme is the best for sedimentary rock type discrimination. Of less value, in decreasing order, are color ratio composites, principal components, and the standard color composite. In addition, for rock type discrimination, the black and white Seasat image is less useful than any of the Landsat color images by itself. However, it is found that the incorporation of the surface textural measures made from the Seasat image provides a considerable and worthwhile improvement in rock type discrimination.
Satellite synthetic aperture radar (SAR) images is evaluated in terms of its geologic applications. The benchmark to which the SAR images are compared is LANDSAT, used both for structural and lithologic interpretations.