This document discusses the use of hyperspectral remote sensing for geological mapping and mineral exploration. It explains that hyperspectral sensors provide more detailed spectral information than multispectral sensors by collecting over 100 spectral bands. This allows for the identification of alteration minerals and lithologies by analyzing their diagnostic absorption features. Methods for processing hyperspectral data include linear and non-linear spectral unmixing to separate mixed pixel spectra into individual mineral components. Challenges include addressing atmospheric effects, topographic variations and developing representative spectral libraries for specific geological terrains.

2. Three-color composite of the Moon,
showing reflected near-infrared
radiation from the Sun. It illustrates
the extent to which different materials
are mapped across the side of the
Moon that faces Earth. This image
shows the distribution of water and
hydroxyl (blue) found at high latitudes
toward the poles.
Blue shows the signature of water and hydroxyl molecules as seen by a highly diagnostic
absorption of infrared light with a wavelength of three micrometers. Green shows the
brightness of the surface as measured by reflected infrared radiation from the sun with a
wavelength of 2.4 micrometers, and red shows an iron-bearing mineral called pyroxene,
detected by absorption of 2.0-micrometer infrared light

3. “Remote Sensing”
A term that was coined in the
1950’s by Evelyn Pruitt, US Office of
Naval Research

4. Remote Sensing
The term "remote sensing," now commonly used to describe the
science—and art—of
•identifying,
•observing, and
•measuring an object without coming into direct contact with it.
•This process involves the detection and measurement of radiation
of different wavelengths reflected or emitted from distant objects or
materials, by which they may be identified and categorized by
class/type, substance, and spatial distribution.
•Satellite or aircraft platform, UV to radar wavelength, passive and
active
•But generally NOT other forms of geophysics which might appear to
fit the definition e.g. radioactivity, magnetics and gravity
•Consider the term “Spectral Geology” – both narrows the field and
is more inclusive of proximal tools using same technology

5. Aerial Photography
•Coined the term in 1950s
•Balloon flight initiated in 1783
•First photograph from a balloon 1858
•World Wars saw great advances in photography from aeroplanes
•Geologists took advantage of the new technology
•Black and white stereo photography
•Interpretation
•Navigation
•Cartography

6. Space Race 1955-1972
•A race for supremacy in spaceflight between Cold War rivals – USA
and USSR
•Oct 4th 1957 Soviet launch of the Sputnik
•Artificial satellites
•Unmanned probes – Moon, Venus and Mars
•Human spaceflight in low earth orbit
•Travel to the Moon
•July 20th 1969 Man walks on the Moon
•A new view of the Earth

7. Earth Resource Technology Satellite - 1
(The LANDSAT Program of USA)
•ERTS-1 Launched July 23rd 1972
•ERTS spacecraft represented the first step in merging space and
remote-sensing technologies into a system for inventorying and
managing the Earth 's resources
•Continental scale geological structures became visible
•Continental Drift and eventually Plate Tectonics were gaining currency
in the geological fraternity
•The interrelationship between continental scaled and outcrop scaled
geological structures required research
•Empirical relationships were observed – mostly photointerpretation

8. Landsat images
• Landsat satellites that have acquired valuable remote sensing data
for mineral exploration and other applications.
• The first generation Landsats 1, 2, and operated from 1972 to 1985.
• The second generation Landsats 4, 5 and 7, which began in 1982
and continues to the present.
• Landsat 6 of the second generation was launched in 1993, but
failed to reach orbit.

9. Digital Data
•With 4 bands of data from Landsat Multi-Spectral Scanner (MSS)
digital enhancement and classification became possible
•Practical application of statistics
•Coping with band to band correlation
•Empirical relationships with geology
•Geological signal tantalisingly just out of reach
•Goal became to accurately, unambiguously and repeatedly map
the earth’s surface geology

10. Development streams
•Increase the number of bands (channels)
•Add channels with geological applications
•Increase the sensitivity of the detectors
•Reduce the footprint of the pixel
•Increase the signal to noise
•Improve the geometry
•Model the transmission properties of the atmosphere
•Digitally filter out vegetation interference
•Develop radar imaging to penetrate cloud and penetrate the
ground

11. Comparison of technology

14. So what sort of geologically interesting things
are found in imagery?
•Major faults and other geological structures
•Palaeodrainage systems in night time thermal data
•Alterations signatures – hydrothermal minerals
•Vegetation stress related to metals and hydrocarbon seepage
•Ocean oil seeps using radar
•Surface structural geology below jungle canopies
•Concealed structure beneath dry sand dunes
•Regolith materials
•Mineralogy (1981 Using Collins GER profiler proved that spectroscopy could be done from
10,000 ft (Mt Turner, Mt Isa, Mary Kathleen and Kambalda – (Gabel, Fraser, Huntington, CSIRO))

15. Extracting Geological Information from
Remotely Sensed data
•The early Landsat series designed for agriculture
•Landsat 4 TM for the first time had Band 7 (2.08-2.35 um)
•Why was Band 7 so important to geologists?
•Band 7 records the presence of clay, carbonate, chlorite, gypsum –
but not individually
•Combined with Band 1 which detected iron oxides there is potential
to identify alteration which is an indicator towards mineralisation.
•Every pixel is a mixture. The mineral is only one component. How to
extract the mineral component?

16. Geological remote sensing is performed through
atmospheric windows where electromagnetic
radiation (EMR) is allowed to pass without
significant attenuation.
The five atmospheric windows available for remote mineral
mapping include:
• The visible to near infrared (VNIR),
• The shortwave infrared (SWIR),
• The mid-infrared (MIR),
• The thermal infrared (TIR) and
• The microwave wavelength regions

18. Of these five atmospheric windows, the VNIR, SWIR and TIR regions
are most useful for mapping surface mineralogy because these
wavelengths are sensitive to a wide range of diagnostic EMR-
material interactions. In particular:
1. The mineral-spectral features in the VNIR are largely related to
the transfer of electrons between energy levels of constituent
elements, especially the transition metals Fe, Mn and Cr.
2. The mineral-spectral features in the SWIR are largely related to
the overtones and combination tones of vibrations of octahedrally
coordinated cations (typically Al, Fe, Mg) bonded with OH groups
3. The mineral-spectral features in the TIR are largely related to
fundamental vibrations (bends and stretches) of Si-O bonds in
various structural environments .

19. As a consequence:
• The VNIR wavelength region is useful for mapping iron oxides and
oxyhydroxides (hematite and goethite)
• The SWIR for dioctahedral and trioctahedral silicates (kaolin, white
micas, smectite, chlorite, amphiboles, talc, serpentine)
• The TIR for framework silicates (quartz, feldspars, garnets,
pyroxenes and olivines).
• Carbonates and sulphates produce diagnostic spectral features at
both SWIR and TIR wavelengths.

20. Combined use of the VNIR, SWIR and TIR
1. The VNIR wavelength region is potentially useful for mapping gossans, rich in
iron oxides and associated with weathered sulphide occurrences, as well as
regolith characterisation
2. The SWIR wavelength region is potentially useful for mapping alteration haloes
that comprise minerals like chlorites and white micas in epithermal/porphyry
styles of Cu-Au mineralisation as well as regolith characterisation.
3. The TIR wavelength region is potentially useful for mapping a range of
exploration targets:
In more weathered environments, mapping silicification associated with
epithermal/porphyry alteration may be useful.
Mn-rich garnets associated with Broken Hill style Pb-Zn-Ag mineralisation
or Fe-rich garnets in Cu-Zn skarn systems can be targeted.
In less weathered terrains, pyroxene composition can potentially be used
as an indicator for skarn deposits whereas feldspars could be important in
mapping granite host rocks or granite-associated mineralising fluids. For example,
the Proterozoic Cu-Au-U mineralisation at Olympic Dam, rare earth mineralisation
and Archaean lode Au deposits are all associated with specific types of granites.

24. Recognition of hydrothermally altered rocks that may be
associated with mineral deposits.
• The spectral bands of Landsat TM are well-suited for
recognizing assemblages of alteration minerals iron
oxides, clay, and alunite that occur in hydrothermally
altered rocks.
• The best exploration results are obtained by combining
geologic and fracture mapping with the recognition of
hydrothermally altered rocks.

25. Alunite and clay minerals on
5/7 ratio images
Table 2

26. Iron minerals on 3/1 ratio images
shows spectra of the iron minerals which have low blue reflectance TM band 1
and high red reflectance TM band 3.

28. ASTER – Band Ratio FCC
•Extracting mineral
information from
multispectral
ASTER
•Quartz (y)
•Al(OH) (g)
•CO3 (r)

30. Emissivity Spectra of Common Rocks
showing shift in emissivity low from 8.6
um (ASTER Band 11) for granite to
10.7 um (ASTER Band 13) for dunite.
This shift forms the basis for using the
thermal bands of ASTER to map
lithology

31. Band Ratio 4/7-3/4-2/1
composite distinguishes
Ocean Island Basalt
(OIB)
from mid-Ocean Ridge
(MORB) Basalt

33. Break away from Bands
•The term “Hyperspectral” joins the lexicon circa 1998
•Usually means more than 100 channels
•Closely approximating the analogue signal as a spectrum
•Every pixel is still a mixture of several pure substances
•How to de-convolve the spectra in order to identify the components?
•“Hour Glass” approach – image dependant, signatures not
transferable
•Alternatively pursue feature extraction using polynomial
interpolation, band differences, ratios and thresholds

34. Spectral bands recorded by remote sensing systems. Spectral reflectance curves
are for vegetation and sedimentary rocks.

35. Hyperspectral Imaging

36. Multispectral Vs Hyperspectral Resolution

37. Spectral Variability will result in the shift in
position and shape of absorption bands as well as
suppress spectra
• Chemical variability (calcite -dolomite and solid solution series)
• Grain size (smaller grain size = higher reflectance)
• Illumination conditions / topography
• Atmosphere (lab measurements vs. in situ or airborne
measurements)
• Weathering – hyperspectral sensors only see what is on the
surface – no penetration!

38. Alteration Minerals Identifiable by Short Wave
Infrared Spectrometry
• Clays: Kaolinite, Dickite, Halloysite, Pyrophyllite, Illite-Smectite,
Montmorillionite
• Micas: White mica (Sericite), Illite, Phengite, Muscovite,
Paragonite, Biotite, Phlogopite, Pyrophyllite, etc.
• Chlorites: Variations in Fe, Mg content
• Other Phyllosilicates: Serpentines (Lizardite, Antigorite),
Fuchsite, Talc, Nontronite
• Amphiboles: Tremolite, Hornblende, Actinolite, Anthophyllite
• Carbonates: Calcite, Dolomite, Ankerite, Siderite
• Sulphates: Alunite, Jarosite, Gypsum
• Tourmaline: Fe-tourmaline, TourmalineMajor
Absorptions:Al-OH: clays, micas
Fe-OH: chlorites, serpentines
Mg-OH: serpentines, chlorites, micas, epidote, some
amphiboles

39. Hydrothermal Alteration Mapping: Orogenic
Gold Quartz-Carbonate Veins
(after Chris Ash)

40. Hyperspectral data does contain lithologic information that can
be used to produce a first pass spectral (lithologic) map to guide
(and focus) field mapping activities
• Amount of exposure is key - vegetation and lichen obscure
important spectral features
• Hyperspectral satellites are coming
• Thermal infrared for silicates

41. This is airborne data and is expensive …more appropriate at this time for
specific mineralization/ alteration studies as opposed to regional
mapping….until we have hyperspectral satellites similar to LANDSAT….we have
Hyperion but only 7 km swath
Hyperspectral data requires fairly complex processing (atmospheric effects)
Effects of topography on spectra
What spatial resolution is really needed?…research issue
What spectral resolution is really needed?….another research issue
What are the best methods to identify end members in areas of mixed rocks?
Traditional linear unmixing, matched filtering etc?
Non-linear unmixing
Derivative analysis
Spectral libraries for specific environment are required