NJPL1I00PDS000000000 FILE_TYPE = TEXT RECORD_TYPE = STREAM END The Deadman Butte area of Wyoming is one of several locations in the Wind River and Bighorn Basins of Wyoming being studied for the NASA Code EEL Multispectral Analysis of Sedimentary Basins Project at JPL (Lang, 1985). The purpose of the study is to develop quantitative models of the formation and evolution of sedimentary basins through stratigraphic, structural, and tectonic analysis of conventional geologic/geophysical and remotely sensed multispectral data. The Deadman Butte area in each of the following scenes encompases approximately 15 x 15 kilometers on the Eastern edge of the Wind River Basin. The stratigraphic sequence exposed in this area ranges from Permian to Late Cretaceous in age and includes limestones, dolostones, siltstones, shales, sandstones, and conglomerates (Lang et al., 1986). The following coregistered, 512 x 512 pixel data sets (including Landsat Thematic Mapper [TM], Airborne Imaging Spectrometer [AIS], Thermal Infrared Multispectral Scanner [TIMS], Quad-pole synthetic aperature radar [SAR], and Digital Terrain Data) are examples of the remotely sensed types of data being used in the study. The TM, and NASA experimental aircraft instrumemts such as the AIS and TIMS are new sensor systems available since 1982. These sensors span a region of the electromagnetic spectrum (0.4 to 12 micrometers) which contains diagnostic spectral features for characterizing many geologic materials. The SAR is a NASA experimental system that actively senses the microwave region of the electromagnetic spectrum. These new sensors have high spatial and spectral resolutions for accurate photogeologic mapping. Used independently or in combination, data from these sensors not only allow delineation of geologic units and structures, but also determination of mineralogy based on spectral properties. The following discussion briefly describes TM, AIS, TIMS and SAR data in the context of geologic applications; examples of each type of data, and processing and analysis functions are provided in Evans et al. (1985), Lang et al. (1986) and Paylor et al. (1985). Thematic Mapper (see Paylor et al. 1985) The TM has six spectral bands in the visible and near infrared (0.4 - 2.5 un) and one band in the mid-infrared (10.4 - 12.5um) region of the electromagnetic spectrum. Bands 5 and 7 are particularly useful for geologic applications because they span a spectral region that is important for characterizing geologic surface materials such as clay and carbonate minerals. Limonitic (iron oxide) materials have diagnostic absorption features in the 0.45 to 0.85 um wavelength range. This interval is sampled by TM channels 1 thru 4. No other specific mineral identifications have been demonstrated using TM data alone. The system provides 30-m picture elements (pixels) in the visible and near infrared and 120-m pixels in the thermal infrared region of the spectrum. Thirty-meter pixels in the visible and near infrared allow for detection of small ground targets and thus accurate reconaissance photogeologic mapping of stratigraphic units and structures is possible. Image processing techniques useful for TM data can be found in Williams (1983), Abrams et al. (1985), and Lang et al. (1986). Photogeologic interpretation of TM images can also be used, in combination with topographic information, for detailed stratigraphic and structural studies (Lang et al., 1986; Paylor et al., 1985). The 30 meter spatial resolution and cartographic fidelity of TM data are sufficient to allow images to be enlarged to 1:24,000 scale to match 7 1/2' topographic maps without any rectification. Thus, standard photogeologic methods can be employed to calculate the attitudes of geologic units and determine stratigraphic thickness. Such information allows the construction of conventional geologic diagrams including stratigraphic columns, structural cross sections, down-plunge projections, stereographic projections, and panel diagrams. TM images are useful for discriminating among geologic structures and a variety of lithologic and stratigraphic units; however, the data lack specific spectral information for unambiguous identification of most minerals. This is due mainly to the relatively broad bandpasses of each TM channel. For example, carbonate minerals have a spectral feature at 2.33 um, within the range of TM channel 7. Thus, carbonate-bearing rocks are not likely to be separable from OH-bearing rocks in the TM images. Narrower bandpasses or some additional information are needed in order to accomplish this separation. Airborne Imaging Spectrometer (see Vane et al., 1983) The AIS was designed to make remote identification of surface materials possible. The 32 AIS channels are contiguous, and are each approximately 9 nm wide (compared to several hundred nm for TM channels). This sampling of the 1.9 to 2.4 um wavelength region resolves most diagnostic absorption features associated with rock forming minerals. This is especially true for materials containing OH (clays), CO3 (carbonates), SO4 (evaporites), and H2O ions and molecules. Standard image processing techniques are not useful for analysis of AIS data. One of the most effective means of data analysis is to sample individual picture elements (pixels) and construct spectral reflectance curves. Thus, direct identification of surface materials is possible by comparing image spectra to laboratory or field spectra of well characterized materials. AIS data have a ground swath of only 320 meters which makes regional studies impossible using AIS data alone. Thermal Infrared Multispectral Scanner (see Kahle and Goetz, 1983) The TIMS sensor measures spectral radiance or brightness temperature of the Earth's surface in the 8 to 12 um wavelength region, in six channels. Spectral emittance information derived from these measurements contain diagnostic spectral features for many Earth materials. These features are particularly useful for detecting the abundance of silica in rocks. Bulk thermal properties, such as thermal inertia, thermal conductivity, thermal diffusivity, and density may also be derived from ground temperatures acquired from TIMS. TIMS data are very high correlated from one channel to the next because of a dominance of ground temperature (Kahle and Goetz, 1983). For this reason TIMS data have been processed using a modified principal components technique called "decorrelation stretching" (Kahle and Goetz, 1983), which displays spectral emittance information as image color, and temperature information as intensities. Silica-rich rocks are portrayed in red to red-orange image colors, clay-rich rocks in bluish-red to purple, carbonate rocks in blue to blue- green, and sulfate materials (mainly evaporites) in yellow. Synthetic Aperature Radar (see Evans et al., 1985) The SAR instrument collects information about surface features at 24.6 cm (L-band) simultaneously in four polarizations (HH - Horizontal transmit, Horizontal receive; HV - Horizontal transmit, Vertical receive; VH; and VV). The sensor measures backscatter intensity which is controlled by surface roughness, topography, and dialectric constant. Each channel (polarization) may be used independantly or in combination to form a color composite image for photogeologic mapping. REFERENCES Abrams, M.J., Conel, J.E., and Lang, H.R., 1985, The Joint NASA/Geosat Test Case Project Final Report: American Association of Petroleum Geologists Special Publication, Tulsa Oklahoma, 2 volumes. Evans, D. E., Farr, T.G., Ford, J.P., Thompson, T.W., and Werner, C.L., 1985, Multipolarization Radar Images for Geologic Mapping and Vegetation Discrimination: IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-24, no. 2, p. 246-257. Kahle, A.B., and Goetz, A.F.H., 1983, Mineralogic Information From a New Airborne Thermal Infrared Multispectral Scanner: Science, Vol. 222, no. 4619, p. 24-27. Lang, H. R.(ed.), 1985, Report of the Workshop on Geologic Applications of Remote Sensing Data to the Study of Sedimentary Basins: Jet Propulsion Laboratory Publication 85-44, 89p. Lang, H.R., Adams, S.A., Conel, J.E., McGuffie, B.A., Paylor, E.D., and Walker, R.E., 1986, Multispectral Remote Sensing as a Stratigraphic and Structural tool, Wind River/Bighorn Basin Area, Wyoming: American Association of Petroleum Geologists Bulletin in press. Paylor, E.D., Lang, H.R., Abrams, M.J., Conel, J.E., and Kahle, 1985, Performance Evaluation and Geologic Utility of Landsat-4 Thematic Mapper Data: Jet Propulsion Laboratory Publication, 85- 66, 68p. Paylor, E. D., 1987, Remote Sensing, in, McGraw-Hill 1987 Yearbook of Science and Technology: McGraw-Hill Book Company, New York, New York, p. 400-403. Vane, G, Goetz, A.F.H., and Wellman, J.B., 1983, Airborne Imaging Spectrometer: A New Tool For Remote Sensing: Proc. 1983 International Geoscience and Remote Sensing Symposiumm, IEEE Catalog #83CH1837-4. Williams, Jr., R.S. (ed.), 1983, Geological Applications, in, Manual of Remote Sensing, Second Edition (Colwell, R.N, ed.): American Society of Photogrammetry, Falls Church, Virginia, 2 Volumes, 2440 p.