Space Science Sampler 2/NASASpaceScienceSamplerV2.cdr/land/plds/plds.txt

Text File | 1987-04-08 | 10KB | 183 lines

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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.