LUT.(m)
posit Scale
5-8
-8
10-20
10-20
10-20
5-8
r types.
JLUT.(m)
posit Scale
5-8
5-8
10-20
:r deposits,
ork to
appropriate instruments and imagery for an effective evalu-
ation.
5.0 CONCLUSIONS
The successful application of remote sensing to mineral
exploration and mineral district mapping is complicated by
many factors, including the par ‘he mineral system
exposed, amount of exposure, character of plant cover,
elevation, relief, climate, and instrument design. Effective
remote sensing techniques are constrained by geologic
models, since the detectability and mapability of the key
geologic features of models are crucial to the success of the
remote sensing survey. The need to assess detection and
mapping parameters prior to selection of instruments and
imagery will increase dramatically with the deployment of
a new generation of remote sensing instruments with
greatly improved spatial and spectral resolution that is
planned by several agencies in the near-future. Effective
decisions depend heavily on the three characteristics of
remote sensing instruments most important for practical
applications: spatial resolution, spectral resolution, and the
positions of bandpasses within the electromagnetic spec-
trum. The exploration geologist will be faced with numer-
ous spectral and spatial resolution options. Well designed
strategies will depend on understanding the geologic ter-
rain, physiography, climate, and ore deposit models. Of
these, deposit model is the most fundamental.
Alteration character, both hypogene and supergene, is one
ofthe most important physical features of hydrothermal ore
deposits pertinent to remote sensing. Pyrite is a common
component of precious metal systems, and hyperspectral
scanners are capable of discriminating individual iron
oxide species. These instruments hold important potential
for mapping iron oxides that relate spatially to ore. The high
resolution hyperspectral scanners are capable of discrimi-
nating individual minerals, including kaolinite, montmo-
rillonite, illite (sericite), alunite, pyrophyllite, calcite, epi-
dote, chlorite, opal, chalcedony, and buddingtonite.
Hyperspectral scanners have been applied to sediment-
hosted gold deposits to differentiate ore-proximal illite
from more distal kaolinite. At hot-springs and high-
sulfidation gold systems, scanners have been used to dis-
criminate kaolinite, alunite and buddingtonite and inner-
differentiate individual mineral species on the basis of Na/
K and Fe/Mg. Instruments that measure in the TIR part of
the electromagnetic spectrum hold great promise for litho-
logic mapping, and when used in conjunction with sensors
that measure in the VNIR and SWIR at high spatial
resolution, the application potential of remote sensing
Increases significantly. Perhaps the most important appli-
cation of the TIR to mineral deposits is direct detection of
silicification. Differentiation of compositional trends within
Intrusive complexes can be relate spatially to ore potential
With this remote sensing interval.
In order to detect narrow quartz veins, small exposures of
647
hydrothermal alteration, or other aerially restricted ore-
related features, spatial resolutions of 5 meters may be
required, even though the width of the exposure need not
equal the spatial resolving power of the instrument. The
exposure only needs to provide a measurable contrast with
surrounding lithologies or adjacent pixels on the image.
High spectral and spatial resolutions offer potential 1) for
mapping alteration where intensity is weak, 2) within
aerially restricted belts or trends, 3) over covered areas
with limited exposure, 4) at sites of intermediate scale
exploration, and 5) at large scale pre-feasibility or mine
expansion phases of mineral development.
6.0 ACKNOWLEDGMENTS
The advise of James V. Taranik has been indispensable,
and the support of BHP Minerals is greatly appreciated.
This paper, largely a synthesis, draws heavily on the
published works of others many of whom are referenced
here and to all of whom I am beholden.
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International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996
