Characterization and Mapping of Kimberlites and Related Diatremes

Characterization and Mapping of Kimberlites and Related
Diatremes Using Hyperspectral Remote Sensing
1
Fred A. Kruse and Joseph W. Boardman
Analytical Imaging and Geophysics LLC
4450 Arapahoe Ave, Suite 100
Boulder, Colorado, USA, 80303
303-604-2844
[email protected], [email protected]
Abstract—Airborne Visible/Infrared Imaging Spectrometer
(AVIRIS) and commercially-available HyMap hyperspectral
data were used to study the occurrence and mineralogical
characteristics of kimberlite diatremes in the State-Line
district of Colorado/Wyoming. A mosaic of five flightlines
of AVIRIS data acquired during 1996 with 20-m resolution
is being used to locate and characterize the kimberlite
diatremes. Higher spatial resolution data (1.6m AVIRIS and
4m HyMap acquired in 1998 and 1999, respectively) are
being used to map additional detail. Poor exposures,
vegetation cover, and weathering, however, make
identification of characteristic kimberlite minerals difficult
except where exposed by mining. Minerals identified in the
district using the hyperspectral data include calcite,
dolomite, illite/muscovite, and serpentine (principally
antigorite), however, most spectral signatures are dominated
by both green and dry vegetation. The goal of this work is
to determine methods for characterizing subtle mineralogic
changes associated with kimberlites as a guide to
exploration in a variety of geologic terrains.
TABLE OF CONTENTS
1.
2.
3.
4.
5.
6.
7.
INTRODUCTION
COLORADO AND WYOMING KIMBERLITES
AVIRIS PROCESSING AND ANALYSIS
HYMAP DATA ANALYSIS
FIELD RECONNAISSANCE AND LAB SPECTRA
PROSPECTS FOR ADDITIONAL WORK
CONCLUSIONS
1. INTRODUCTION
Kimberlites are the principal source of diamonds and thus of
high economic interest and importance. They originate as
the result of intraplate alkaline magma, apparently generated
at deeper levels in the mantle than most other magmas1.
Kimberlites consist of predominantly ultramafic matrix
material that has crystallized in situ, associated megacrysts
formed in the upper mantle from the kimberlite magma, and
mantle-derived xenoliths incorporated during magma
transport.
Common matrix minerals include olivine,
phologopite, perovskite, spinel, chromite, diopside,
1
0-7803-5846-5/00/$10.00 © 2000 IEEE
monticellite, apatite, calcite, and serpentine (commonly Ferich)1. Alteration of some of these minerals to serpentine
and calcite is common. Additionally, kimberlites usually
contain transported sedimentary and crystalline rocks.
Information from deep mining of kimberlites in South Africa
has illustrated that the diatremes commonly thought of as the
source of diamonds are in fact part of a larger magmatic
system including a hypabyssal root zone, the diatreme, and
eruptive rocks. Thus three genetic groups of rocks are
recognized; hypabyssal facies, diatreme facies, and crater
facies1, 2. Kimberlite diatremes are generally vertical or
steeply inclined cone-shaped intrusive bodies.
They
typically cross-cut host rocks, outcrop as approximately
circular or elliptical bodies, and decrease in diameter with
depth. Host rock contacts are sharply defined with little
associated structural and contact metasomatism or
metamorphism. The diatremes are typically exposed at the
surface as shallow depressions.
Hypabyssal facies
kimberlites represent the root zones of diatremes and may
also occur as dikes and sills. The hyperbyssal facies rocks
are characterized by irregular outcrop plan, as the root zone
is strongly influenced by the joint and fracture patterns of
the host rocks. There are only a few known locations of
crater facies rocks, which occur as lavas, pyroclastic rocks,
and epiclastic rocks where erosion has been limited2, 3, 4.
Imaging spectrometer data (also known as hyperspectral
data) are under consideration by several mining companies
for kimberlite exploration and characterization. This paper
describes the use of Airborne Visible/Infrared Imaging
Spectrometer (AVIRIS) and commercially available HyMap
data to study the occurrence and mineralogical
characteristics of kimberlite diatremes in the State-Line
district of Colorado/Wyoming. Hyperspectral sensors
measure reflected light in up to several hundred narrow
(approximately 10 nm) bands. Several of the minerals
associated with kimberlites, in particular the serpentine and
associated calcite are easily detected using the shortwave
infrared region of the spectrum.
The Airborne Visible/Infrared Imaging Spectrometer
(AVIRIS) is a 224-channel imaging spectrometer with
approximately 10 nm spectral resolution covering the 0.4 –
2.5 µm spectral range at 20 m spatial resolution5. Several
AVIRIS scenes acquired in August 1996 covering sites in
Colorado/Wyoming were analyzed. Selected results were
previously reported in Kruse and Boardman (1997)6.
HyMap, the most advanced commercial hyperspectral sensor
available today, provides high accuracy, calibrated radiance
data over 126 channels covering the 0.4 – 2.5 µm spectral
range with approximately 15-20 nm spectral resolution and
3-10m spatial resolution7. The system provides precisely
geolocated data. Analysis of two 4m-resolution HyMap
flightlines acquired for some of the sites is in progress. We
expect that this improved spatial resolution may help resolve
some of the spectral mixing problems inherent in the larger
20m pixels.
The goal of using the combined
AVIRIS/HyMap data is to develop methods for
characterizing subtle mineralogic changes associated with
kimberlites and related diatremes, examining the effect of
scaling and spatial resolution on detection, characterization,
and mapping of these changes, and developing exploration
models valid for a variety of geologic terrains using both
airborne and spaceborne hyperspectral sensors.
in reflectance across scene boundaries. This, however,
introduces elevation-related atmospheric artifacts into some
of the data, but these are outside the spectral range used to
analyze these data.
2. COLORADO AND WYOMING KIMBERLITES
The State-Line kimberlite district of Colorado/Wyoming,
discovered in the early 1960s, contains a number of
Devonian-age diamondiferous kimberlitic diatremes that
penetrate the crystalline basement8, 9, 10. Prominent joint sets
and faults apparently helped control placement of the
diatremes, which occur on an approximately north-south
trend roughly paralleling the eastern edge of the Front Range
(Figure 1). Diatremes are emplaced in Precambrian igneous
and metamorophic rocks. Kimberlites occurring in the
State-Line district are similar mineralogically and
chemically to other known kimberlites world-wide; a breccia
of subrounded to angular clasts in a fine crystalline matrix
consisting of serpentine, calcite, dolomite, phologopite,
magnetite, perovskite, chlorite, talc, and hematite8. Stateline kimberlites also include blocks and fragments of
Paleozoic dolomite, congolomerate, and sandstone. The
kimberlites themselves are deeply weathered, and alteration
typically consists of serpentization and carbonitization.
Figure
1:
Location of the State Line District,
Colorado/Wyoming (From Coopersmith and
Schulze)10.
Kelsey Lake
N
3. AVIRIS PROCESSING AND ANALYSIS
Five flightlines of AVIRIS data consisting of approximately
50 scenes were acquired during 1996. Analysis of these
data (Figure 2) using standardized methods developed by
AIG11, 12 (Figures 3 and described below) is in progress.
The 50 Colorado/Wyoming AVIRIS scenes were processed
to apparent reflectance using the ATREM software13.
ATREM is an atmospheric model-based routine that
converts the calibrated radiance measured by the sensor to
apparent surface reflectance without requiring in-situ
measurements14. A common reference altitude was used for
all of the Colorado/Wyoming data to avoid obvious changes
Figure 2: AVIRIS True Color (0.66, 0.55, 0.45 µm, RGB)
composite image of two concatenated AVIRIS
scenes (12km x 20 km) showing approximate
location of the Kelsey Lake kimberlite pipe along
the left edge of the image.
Methods being used in the analysis (implemented in the
“ENVI” image analysis software) include spectral data
reduction using the Minimum Noise Fraction (MNF)
transformation15, spatial data reduction using the Pixel
Purity Index (PPI)16, an n-Dimensional Visualizer to
determine image endmembers16, 17, identification of
endmembers using their reflectance spectra18, 19 in the
Spectral Analyst, and mineral mapping using several
methods20, 21, 22, 23 and also outlined in Kruse (1997)12.
abundance. Brighter pixels in the images represent higher
mineral abundances. These can then be combined as colorcoded images to show the distribution of principal
mineralogies (Figures 6 and 7).
Figure 3 AIG Standardized Processing methods for
hyperspectral data analysis.
Operationally, last 60 AVIRIS bands (1.92 – 2.51 µm) were
linearly transformed using the MNF transformation, and the
top MNF bands, which contain most of the spectral
information, were used to determine the most likely
endmembers using the PPI procedure. These potential
endmember spectra were loaded into an n-dimensional
scatterplot and rotated in real time on the computer screen
until “points” or extremities on the scatterplot were exposed.
These projections were “painted” using Region-of-Interest
(ROI) definition procedures and then rotated again in 3 or
more dimensions (3 or more bands) to determine if their
signatures were unique in the AVIRIS MNF data. Once a
set of unique pixels were defined, then each separate
projection on the scatterplot (corresponding to a pure
endmember) was exported to a ROI in the image. (Note:
when trying to locate “rare” or sub-pixel targets (such as
kimberlites), selection of the signal vs noise cut-off in the
MNF is critical. Care must be taken not to eliminate too
many MNF bands or the targets of interest will not be
located). Mean spectra were then extracted for each ROI
from the apparent reflectance data to act as endmembers for
spectral mapping (Figure 4). These endmembers or a subset
of these endmembers were used for subsequent classification
and other processing. Three digital mapping methods, the
Spectral Angle Mapper (SAM)21, Linear Spectral
Unmixing16, 17, 22, 23, and Matched filtering24 were used to
produce mineral abundance maps (Figure 5). The results are
generally presented as gray-scale images with values from 0
to 1.0, which provide a means of estimating mineral
Figure
4:
AVIRIS endmember spectra.
Tentative
identifications are: EM#1 Serpentine 1, EM#2
Calcite, EM#3 Carbonate/Serpentine 2, EM#4
Antigorite (Serpentine 3), and EM#5 Dry
Grass.
EM 4
Detections
EM 1
Detections
Figure 5: Grayscale abundance images for the minerals
Serpentine 1 (EM#1) and Antigorite (EM#4).
Brighter pixels indicate higher abundances.
Kelsey Lake
Nix/Moen?
Figure 6: AVIRIS Mineral Map produced from the two AVIRIS scenes. EM#1 (Serpentine 1) Orange; EM#2 (Calcite)
Purple; EM#3 (Serpentine 2) Green; EM#4 (Antigorite [Serpentine 3]) Cyan; EM#5 (Dry Grass) Yellow.
Figure 7:
AVIRIS Mineral Map produced from the two AVIRIS scenes overlaid on a grayscale image. EM#1
(Serpentine 1) Orange; EM#2 (Calcite) Purple; EM#3 (Serpentine 2) Green; EM#4 (Antigorite [Serpentine
3]) Cyan; EM#5 (Dry Grass) Yellow.
There are several things to note when analyzing the
hyperspectral data of kimberlite occurrances. First, unless
the minerals are very well exposed (for example surface
outcrop in an arid terrain, or as here in mined areas), the
signatures will be very subdued when compared to the
spectral libraries (Figure 8). They may be so subdued in
fact that the spectra will appear very similar to those for dry
grass or other dry vegetation (Figure 9). In the case history
described here for the State Line district, the similarities to
dry grass has serious implications, as much of the area is
covered by dry grass anyway. Also, note that we have
differentiated several serpentines despite not being able to
clearly distinguish the exact mineral. EM#4 is clearly
identifiable as antigorite (there may be some mixed
phlogopite and or lizardite as well, see Figure 8), however,
the other serpentines, though clearly serpentine do not match
a specific mineral from the spectral library (and may in fact
be mixtures).
Figure 9:
AVIRIS EM#4 (Antigorite) and EM#1 (Dry
Grass) compared to Dry Grass spectrum from
the U.S. Geological Survey spectral library.
Finally, the AVIRIS data did detect minerals diagnostic of
kimberlites, however, these occurred principally where
exposed in mined areas. There are a few minor occurrences
that do not appear to be associated with the obvious mines
and prospects, but these will require additional work with
higher spatial resolution hyperspectral sensors and/or field
confirmation.
4. HYMAP DATA ANALYSIS
The AVIRIS analysis above produced enough information
that AIG elected to acquire higher spatial resolution
hyperspectral data over several of the serpentine areas. Two
flightlines of HyMap data were flown during September
1999 at approximately 4m spatial resolution. HyMap is a
state-of-the-art aircraft-mounted commercial hyperspectral
sensor developed by Integrated Spectronics, Sydney,
Australia, and operated by HyVista Corporation, Sydney,
Australia. The sensor provides unprecedented spatial,
spectral and radiometric excellence7. The system is a
whiskbroom scanner utilizing diffraction gratings and four
32-element detector arrays (1 Si, 3 liquid-nitrogen-cooled
InSb) to provide 126 spectral channels covering the 0.45 –
2.5 µm range over a 512-pixel swath. The Y-direction of
the imagery is provided by the aircraft motion. HyMap
provides high spatial resolution data (3 –5 m), however, has
slightly broader spectral bands than AVIRIS (~17nm for
HyMap vs ~10nm for AVIRIS in this wavelength range).
These are still adequate for identification of specific
kimberlite minerals (principally serpentine). The last 29
bands 2.0 – 2.48 µm) were used for this analysis.
Figure 8: Comparison of EM#4 (AVIRIS spectrum
identified as Antigorite) to spectra of minerals
from the U.S. Geological Survey spectral
library25.
Figure 10 shows a geocorrected false color-infrared
composite (CIR) image of the two flightlines acquired for
location purposes. The flightlines cross at their north-west
ends over the Kelsey Lake Mine.
Figure 10: Geocorrected False Color Infrared (CIR) composite of two HyMap flightlines covering the Kelsey Lake Mine
and other parts of the Colorado/Wyoming State Line District. North is to the left of the page.
One flightline has been analyzed using the standardized AIG
methodology (see Section 3 above and Kruse, 1997 for a
description of the methodology)12. Data were corrected to
apparent reflectance using ATREM. The spectral
dimensionality of the data was reduced using the MNF
transform, and the spatial dimensionality using the Pixel
Purity Index. Spectral endmember were selected from the
data using the n-Dimensional Visualizer and identified using
visual inspection and the ENVI Spectral Analyst (Figure
11).
Endmembers identified are typical for weathered
kimberlites. Two slightly different antigorite spectra were
extracted, along with two different illites. Calcite is present,
however, the spectrum marked as “Epidote?” is problematic.
It really doesn’t match anything in the library very well and
is likely a mixture of carbonate minerals and something else,
probably not epidote. The spectrum extracted for dry
vegetation is typical, and similar in some ways to the
mineral spectra of interest. The “green vegetation” spectrum
is typical for healthy vegetation in this spectral region, but
has no individual diagnostic spectral features.
Comparison of the HyMap “Antigorite#2” endmember
spectrum to a spectrum of Antigorite from the USGS
Spectral Library25 (Figure 12) demonstrates a close match,
however, there are some differences. The spectral feature
near 2.3 µm is somewhat subdued in the HyMap spectrum,
as are the secondary features. These are likely explained by
the fact that first, this is a spectral average for several
spectra from the n-D Visualizer. Additionally this spectrum
is a linear mixture of all materials occurring within the
approximately 4m HyMap pixel.
Figure 12: Comparison of HyMap Antigorite#2 endmember
spectrum to USGS Spectral Library Antigorite
spectrum.
The sharp fall-off at long
wavelengths in the HyMap spectrum is probably
caused the low energy levels available at these
wavelengths when using natural solar
illumination.
Figure 11: Endmembers extracted from the 1999 HyMap
data. Identifications are based on a combination
of visual inspection and comparison to plotted
endmember spectra combined with numerical
comparison of continuum-removed spectra using
the ENVI Spectral Analyst (spectral matching).
Although the complete HyMap flightline was analyzed using
the above methodology, and there appear to be several areas
of serpentine occurrences, this HyMap analysis work is in
progress. Therefore, only a small area within the Kelsey
Lake Mine itself is used here for illustrative purposes.
Figure 13 is a HyMap image subset around the Kelsey Lake
Mine and workings. Figure 14 is the HyMap mineral map
for the same image subset.
Figure 13: HyMap CIR composite of the Kelsey Lake Mine.
Figure 14: HyMap Mineral map of the Kelsey Lake Mine.
5. RECONNAISSANCE AND LAB SPECTRA
Field reconnaissance was conducted following image
processing and analysis in conjunction with a GSA field trip
to the Kelsey Lake Mine on 24 October 1999. Access was
granted by Diamond Company N.L., the current owner of
Kelsey Lake Mine, and several grab samples were selected
based on hyperspectral-mapped mineralogy and returned for
laboratory spectral measurements.
Figure 15 shows one of the areas mapped as Antigorite #2
using the HyMap data (area “A” marked on Figure 13 and a
semi-circular yellow ring opening to the west shown on
Figure 14 at the same location). Field reconnaissance and
information from the property owner show this area to be a
holding pile for oversize material from the mine. A wide
There is also a significant amount of fine-grained sand to
gravel matrix material supporting the larger material and
covering the flat tops of the piles. These flat areas map as
“Antigorite #1” in the HyMap data, corresponding to the
magenta center to the yellow semi-circular area on Figure
14. There doesn’t appear to be any obvious compositional
difference between the two antigorites, only that one occurs
as finer grained material and possibly slightly more
weathered. This affects the shape and depth of the principal
spectral band for antigorite near 2.3 µm.
Samples returned from the mine were measured in the
laboratory using an Analytical Spectral Devices FieldSpec
FR visible/infrared spectrometer. The FieldSpec covers the
range 0.4 – 2.5 µm at high spectral resolution. Figure 17
compares the Hymap-measured antigorite spectrum to the
FieldSpec-measured antigorite spectrum. Note that HyMap,
though lower resolution, resolves the key spectral features.
Figure 15: Oversize materials piles at Kelsey Lake
Mine. Ore from KL-2 pit and currently
located at site “A” seen in Figure 13.
Figure 17:
variety of materials were observed, most appearing to
correspond to relatively fresh kimberlite cobbles, boulders,
and rock fragments on the order of about 15cm across
(Figure 16) occurring on the sloped sides of the piles.
HyMap spectrum of the Antigorite #2 area
compared to a laboratory-measured FieldSpec
FR spectrum (left), and the FieldSpec spectrum
compared to a spectrum of Antigorite from the
USGS Spectral Library (right).
6. PROSPECTS FOR ADDITIONAL WORK
Figure 16: Sample of “Antigorite #2” from the Kelsey Lake
Mine.
Known occurrences of undisturbed/developed kimberlites in
the State Line District are also being studied using AVIRIS
and HyMap. The nature of kimberlites, and in particular the
kimberlites of this district, however, makes practical use of
hyperspectral technology for exploration extremely difficult.
This is principally because of the nature of the exposures.
Kimberlite at the surface typically is heavily weathered. In
the State Line district, its presence can be diagnosed by an
experienced geologist based on its geomorphic expression as
small depressions (often between granite outcrops), the
general absence of trees, the presence of specific grass
associations, and fragments of kimberlite brought to the
surface by biological activity. There is typically no outcrop,
and if any material occurs at the surface at all, the
distribution of diagnostic kimberlite materials is quite small
(Figure 18).
Kimberlite
Granite
Figure 18: Typical kimberlite exposures at KL-1, undeveloped occurrences approximately 1 km northeast of current Kelsey
Lake Mine. Left: Grassy area in the foreground is slight depression corresponding to part of the KL-1
kimberlite pipe. Right: Narrow extension of KL-1 in the grass-covered area between the trees in the center of
the photo, surrounded on both sides by granite covered with ponderosa pine.
Even so, there is some potential for mapping undisturbed
kimberlites, or even locating unknown ones in the State Line
district using hyperspectral data.
Distinct vegetation
associations merit further study and could lead to
vegetation-based mapping methods.
Surface outcrop,
though small, has been observed at some locations (Figure
19) and there are indications from preliminary image
analysis that serpentine minerals occur at the surface in
some areas where there is no obvious mining or prospecting.
Kimberlite
Outcrop
kimberlite-related minerals. Several AVIRIS scenes have
been analyzed using a standardized procedure consisting of
atmospheric removal, selection and identification of spectral
endmembers, and spatial mapping of endmember occurrence
and abundance. Regional mineral mapping using a total of
50 AVIRIS scenes to produce maps showing the distribution
of minerals associated with kimberlites and surrounding
host-rocks is underway. Several prospects identified from
the AVIRIS mapping have been flown using higher spatial
resolution HyMap data and detailed mineral studies are also
in progress. The hyperspectral remote sensing data provides
the advantage of being able to cover large segments of
ground, providing a synoptic view and simultaneously
obtaining high-quality reflectance spectra of diagnostic
minerals. The goal of this research is to determine methods
for characterizing subtle mineralogic changes associated
with kimberlites and developing exploration models valid
for a variety of geologic terrains. The methods described
here may or may-not lead to improved understanding of
State Line District kimberlites or new kimberlite discoveries
in this district, but as a minimum, these approaches, based
on first principals, can be used as part of an integrated
exploration strategy.
8. ACKNOWLEDGMENTS
Figure 19: Small outcrop exposure of kimberlite materials
at the Sloan#1 pipe in another part of the State
Line district.
7. CONCLUSIONS
A hyperspectral study of selected diatremes in the
Colorado/Wyoming State Line District has established the
viability of hyperspectral data for mapping diagnostic
This research was supported by Analytical Imaging and
Geophysics IR&D funds. AVIRIS data were provided by
JPL. HyMap data were acquired under a cooperative
agreement between HyVista Corporation, Sydney, Australia
and AIG. Access to the Kelsey Lake property was courtesy
of Diamond Company N. L., and particular thanks are due to
Howard Coopersmith for his assistance and discussions
during the GSA field trip.
Laboratory spectral
measurements were performed at the University of Colorado
with the assistance of Bruce Kindel.
HyMap is a trademark of HyVista Corporation. ENVI is a
registered trademark of BSCLLC, Lafayette, Colorado.
Pixel Purity Index (PPI), n-Dimensional Visualizer, Spectral
Analyst, and Mixture-Tuned Matched Filter (MTMF) are all
trademarks of BSCLLC. FieldSpec is a trademark of
Analytical Spectral Devices, Boulder, Colorado.
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Development and geology of the Kelsey Lake diamond
mine, Colorado: In Diamonds to Gold, I. State Line
Kimberlite District, Colorado: Society of Economic
Geologist guidebook Series, V. 26, p. 1-19.
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AUTHOR BIOGRAPHIES
Dr. Fred A. Kruse received the Ph.
D. in Geology from the Colorado
School of Mines, Golden, Colorado
(1987). He has been involved in
multispectral, hyperspectral, and
SAR remote sensing research and
applications for over 18 years in
positions with the U. S. Geological
Survey, the University of Colorado,
and private industry. His primary
scientific interests are in the application of remote sensing
technology to exploration and understanding of ore deposits
and the development of knowledge-based techniques for
spectral identification and mapping of geology, man-made
materials, vegetation, and near-shore marine environments.
Dr. Kruse is also co-founder of BSC, the company that
developed the remote sensing analysis software package
ENVI, “The Environment for Visualizing Images.”
Dr. Joseph W. Boardman received the Ph. D. degree in
Geophysics from the University of Colorado in 1991,
followed by a 2 year Postdoctoral research fellowship with
the CSIRO, Sydney, Australia. From 1993 to 1995 he was a
Research Associate at CSES, University of Colorado,
Boulder. His current research as Senior Geophysicist,
Analytical Imaging and Geophysics LLC, Boulder,
Colorado, applies convex geometry and n-dimensional
methods to automatically determine endmembers for subpixel analysis (spectral unmixing). Dr. Boardman is also
co-founder of BSC, the company that developed the remote
sensing analysis software package ENVI, “The Environment
for Visualizing Images”.