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2003 News Archive

Use of Hyperspectral Data in Regolith Mapping

Dr A.J.Mauger
CRC LEME Mineral Mapping SA
Gawler Craton Team
Geological Survey Branch

Hyperspectral data approximate continuous reflectance/emittance spectral measurements over a selected interval of the electromagnetic spectrum. Data in the visible to short-wave infrared region can now be acquired from airborne and satellite platforms that provide a full spectrum recorded for every pixel in the spatial image. Spectra can be examined for individual absorption features caused by specific chemical bonds in any solid, liquid, or gas. All materials are formed by chemical bonds and therefore have the potential to be detected by spectroscopy. Actual detection is dependant on spectral coverage, spectral resolution, signal-to-noise characteristics of the spectrometer, the abundance of the target material, and the relative strength of the absorption features for that material in the wavelength region being measured. Spectroscopy can be used in laboratories on hand specimens, drill hole cuttings and core samples, in the field with portable field spectrometers, from aircraft, and from satellites. In remote sensing applications, the surface materials mapped must be exposed in the optical surface (eg. to map surface mineralogy it must not be covered with vegetation), and the diagnostic absorption features must be in regions of the spectrum that are reasonably transparent to the atmosphere (adapted from http://speclab.cr.usgs.gov/aboutimsp.html).

Spectral mineral logging and mapping provides the geologist analysing regolith with objective information on the spatial distribution of particular minerals generated and dispersed by regolith forming processes. The advent of hyperspectral scanners with high signal-to-noise characteristics over 100 or more bands in the visible to short-wave infrared part of the electromagnetic spectrum, now provides the opportunity for objective surface mineral mapping. The problem of atmospheric interference with the signal reflected from the target has been addressed by including specific bands to measure the atmospheric water column on a per pixel basis. With this information the effects of atmosphere can be modelled and removed from the signal at the pixel level. The spectral resolution of the scanners is such that minerals can be discriminated using laboratory determined diagnostic absorption features at a resolution of separation of around 20nm. Hyperspectral data acquisition has been developed to the stage where our limited ability to model all the natural processes in the system constitutes the primary impediment to the accurate delineation of mineral species in the environment.

Hyperspectral data can be classified according to the platform of acquisition which can also be linked to the scale of observation. Hyperion is the first hyperspectral instrument to be launched on a satellite platform. With 30m pixel size, 7.7km swath width, 40km image length and 220 channels, Hyperion has proved the technology for the next generation of remote sensing satellites.

HyMap is an Australian built airborne system with 128 channels between wavelengths 450 and 2500nm. Depending on the height flown, 3m pixels with 1.5km swaths in 25-30km runs are possible although a more usual configuration of 5m pixels with 2.5km swaths flying at 2 km and allowing a 500m overlap between runs produces a manageable dataset.

In order to ground truth air- and space-borne instruments a portable field spectrometer covering the same wavelengths is required. One such instrument, the ASD Field Spec, which covers the spectral ranges of Hyperion and HyMap, relies on external illumination. Another, the PIMA II SP (Portable Infrared Mineral Analyser), utilises an internal light source and calibration target allowing it to operate under a broader range of conditions than the ASD Field Spec. Although the PIMA only covers the wavelength range 1300-2500nm this portion of the spectrum includes diagnostic absorption features for many common minerals. The prototype CSIRO Core Logger provides continuous spectral information along core with a 450-2500nm spectrum recorded at 1 cm intervals. By arranging the mineralogical results in their relative 3D orientation, spatial relationships can be investigated and volumetric studies undertaken.

Mineral groups detectable with these systems include:

• Clays

• Amphiboles

• Phosphates

• Carbonates

• Hydroxides

• Borates

• Sulphates

• Evaporites

• Zeolites

Typical minerals include:

• Kaolin

• Alunite

• Actinolite

• Muscovite

• Jarosite

• Calcite

• Illite

• Chlorite

• Dolomite

• Pyrophyllite

• Talc

• Magnesite

• Smectites

• Epidote

• Gypsum

Within a particular mineral solid solution series geochemistry might also be identified based on subtle features of the reflectance spectra. For example the sodium-potassium content of white mica can be estimated by examining the position of the 2200nm absorption feature which shifts to lower wavelengths with increasing sodium substituting for potassium.

Geologists depend on aerial photographs for regional mapping. Much of their work involves interpreting the photos for lithological units and geological structure. Detailed field mapping typically involves both transects across strike and the delineation of lithological boundaries by following contacts. If a surface material is not distinctive in the photography a geologist risks errors of omission because it is often not feasible to examine every outcrop on foot. Hyperspectral imagery provides a synoptic overview with the additional perspective of mineralogical information. Now it is possible to interpret and map mineral alteration that cuts across lithological boundaries and to recognise variation in weathering intensity by the appearance or absence of particular minerals and their relative abundance.

Issues with mapping regolith include the omission of unrecognised saprolite outcrop and the discrimination of transported deposits from in-situ regolith. Hyperspectral imagery offers the opportunity to map previously unrecognised saprolite and to map alteration mineral distribution patterns visible at the surface. Mineralogical variation may be significant in mapping regolith where unit boundaries are often less distinct and low angled deposits tend to coalesce.

To the geologist studying the regolith the issue becomes one of modelling the mineral systems under consideration and then using the appropriate tool on the appropriate platform to provide the necessary information.

Spectral logging is proving to be an effective technique for logging regolith units. In documenting the regolith profile it is important to log those minerals that survive the weathering process with an indication of the point in the profile where they disappear and what new minerals form during weathering. The 3D element dispersal train is also valuable to ascertain. The strength of the CSIRO Automated Core Logger lies in the capacity to measure large volumes of contiguous material in a short space of time. Using core gathered over a recognised deposit, element dispersion models can be linked to mineralogical changes identified as marking different stages in the development of the regolith.

Developments in hyperspectral data acquisition and analysis are advancing rapidly. The regolith geologist has the opportunity to avail themselves of these developments thus adding another dimension to their understanding of regolith forming processes.

In order to maximise utilisation of this tool CRC LEME offers annual workshops for CRC LEME participants. The next workshop is scheduled for 21-25 July 2003 at the University of Adelaide, South Australia. For details contact Alan Mauger, Geological Survey Branch, Minerals Petroleum & Energy, Primary Industries and Resources SA, p: +61-8-84633062, f: +61-8-82263200, e: mauger.alan@saugov.sa.gov.au or Pat James, University of Adelaide, p (dir): 61 (0)8 8303 5254 p (mob.):0403028004 p (sec): 61 (0)8 8303 5376 f: 61 (0)8 8303 4347 e: patrick.james@adelaide.edu.au.

A 2.5km wide strip of HyMap imagery from the Willouran ranges in South Australia

 

Spectral plot of selected pixels from HyMap imageryA 2.5km wide strip of HyMap imagery from the Willouran ranges in South Australia. Carbonate materials are shown in blues and purples while siliclastic materials appear as oranges and reds. Vegetation is displayed as green. One can very clearly identify and determine the source of the dominant mineral class in the stream sediments and outwash plains.

The accompanying spectral plot of selected pixels from this image demonstrates the ability of an airborne hyperspectral scanner to acquire high quality mineral spectra. A mesa of residual Tertiary material overlying the steeply dipping Proterozoic sediments is apparent in the lower left of the image.

(Click on images to enlarge them)

For further information see: J.L. Keeling and A.J. Mauger, 2000: "Application of Airborne Hyperspectral (HYMAP) Data to Map Variation in Carbonate Facies in Proterozoic Skillogalee Dolomite, Willouran Ranges, South Australia." 10th Australasian Remote Sensing and Photogrammetry Conference, Adelaide, 2000.

A 2.5km wide strip of HyMap imagery from the Willouran ranges in South Australia. Carbonate materials are shown in blues and purples while siliclastic materials appear as oranges and reds. Vegetation is displayed as green. One can very clearly identify and determine the source of the dominant mineral class in the stream sediments and outwash plains.

The accompanying spectral plot of selected pixels from this image demonstrates the ability of an airborne hyperspectral scanner to acquire high quality mineral spectra. A mesa of residual Tertiary material overlying the steeply dipping Proterozoic sediments is apparent in the lower left of the image.

(Click on images to enlarge them)

For further information see: J.L. Keeling and A.J. Mauger, 2000: "Application of Airborne Hyperspectral (HYMAP) Data to Map Variation in Carbonate Facies in Proterozoic Skillogalee Dolomite, Willouran Ranges, South Australia." 10th Australasian Remote Sensing and Photogrammetry Conference, Adelaide, 2000.

 

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