Regional Mineral Mapping By Extending Hyperspectral Signatures Using Multispectral Data 1, 2
Fred A. Kruse Horizon GeoImaging, LLC P.O. Box 4279, Frisco, CO 80443 970-668-3607,
[email protected]
and
Abstract—Hyperspectral imaging (HSI) data in the 0.4 – 2.5 micrometer (VNIR/SWIR) spectral range allow direct identification of minerals using their fully resolved spectral signatures, however, spatial coverage is limited. Multispectral Imaging data (MSI) (e.g. data from the Advanced Spaceborne Emission and Reflection Radiometer, ASTER)) are spectrally undersampled and may not allow unique identification, but they do provide synoptic spatial coverage. Combining the two data types by modeling hyperspectral signatures to ASTER band passes allows extending HSI mapping results to regional scales and leads to improved mineral mapping over larger areas.
TABLE OF CONTENTS 1. INTRODUCTION ..................................................... 1 2. BACKGROUND ....................................................... 2 3. APPROACH AND METHODS ................................... 3 4. RESULTS ................................................................ 5 5. SUMMARY AND FURTHER WORK ....................... 11 6. ACKNOWLEDGEMENTS ....................................... 11 7. REFERENCES ....................................................... 11 BIOGRAPHIES .......................................................... 14
1. INTRODUCTION This research uses Advanced Spaceborne Thermal Emmission and Reflection Radiometer (ASTER) data to extend hyperspectral imaging (HSI) mapping results to regional scales for environmental monitoring and geologic mapping. Hyperspectral imaging is currently available from both airborne and satellite platforms. Its utility for detailed materials mapping has been demonstrated for a variety of scientific disciplines [1, 2, 3, 4]. Availability and regional coverage of HSI data continues to be problematic, however, and probably always will be because of the high data volumes generated by these sensors. Thus hyperspectral systems are best used as targeted sensors – looking at small specific regions-of-interest. Multispectral imagery (MSI) systems like ASTER on the other hand are able to provide synoptic coverage, albeit with fewer spectral bands. The spectral information from multispectral instruments is more limited than that from HSI systems because of lower spectral resolution and limited spectral ranges. We are using integration and spectral/spatial scaling of nested HSI/MSI data to model and predict ASTER multispectral signatures. The predicted signatures are then used to extend hyperspectral mapping results to the larger synoptic spatial coverage of ASTER, thus improving geologic mapping and monitoring for areas not covered by hyperspectral data. Concepts and methods are being developed in the context of NASA’s Earth Science Enterprise (ESE) mission and applied to geologic problems to produce case histories in the areas of geologic mapping and baselining, and environmental monitoring of mined areas. Field
We are using several geologic test sites to establish geologic background and characterize and map human-induced change in the form of mine excavations, mine tailings, mine waste, and acid runoff using HSI and ASTER data. The HSI data are atmospherically corrected using commercialoff-the-shelf (COTS) atmospheric correction software. Data are then analyzed to determine spectral endmembers and their spatial distribution, and validated using field spectral measurements. Spectral modeling is used to convert HSI spectral signatures to the ASTER spectral response. Reflectance-corrected ASTER data are then used to extend the hyperspectral mapping to the full ASTER spatial coverage. Field verification of ASTER mapping results is conducted and accuracy assessment performed. Additional geologic sites are also being assessed with ASTER using the modeling methodology based on sceneexternal HSI and/or field spectra (but without scene-specific a priori hyperspectral analysis or knowledge). These results are further compared to field measurements and subsequent hyperspectral analysis and mapping to validate the spectral modeling approach. Initial results show that the ASTER multispectral data can successfully map several minerals and/or mineral groups. While some specific minerals are ambiguous, the mineral maps produced using this method, identifying and mapping specific minerals based on their spectral signatures, are significant improvements over previous approaches that expressed simple spectral shape differences on color-composite images or as statistically different (but unidentified) classes. 1 1 2
Sandra L. Perry Perry Remote Sensing, LLC Englewood, CO 80113
1-4244-0525-4/07/$20.00 ©2007 IEEE. IEEEAC paper #1078, Version 4, Updated November 24, 2006
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reconnaissance and spectral measurements are being used to validate the ASTER modeling results.
variety of disciplines. The EO-1 Science Validation Team has evaluated and validated the instrument. Selected results have been presented at team meetings [10] and also published in various venues [11, 12, 13]. Also see [14] for a summary along with associated papers. The instrument remains healthy and additional data can be requested for specific sites. Table 1 shows a comparison of AVIRIS and Hyperion instrument characteristics.
2. BACKGROUND Imaging Spectrometers, or “Hyperspectral” sensors measuring hundreds of spectral bands provide a unique combination of both spatially contiguous spectra and spectrally contiguous images of the Earth's surface unavailable from other sources [5]. Current airborne sensors provide high-spatial resolution (2-20m), high-spectral resolution (10-20nm), and high SNR (>500:1) data for a variety of scientific disciplines. The two HSI sensors used for this effort are:
Table 1: AVIRIS/Hyperion Sensor Comparison. HSI Sensor AVIRIS Hyperion
Spectral Bands 224 242
Spectral Resolution 10 nm 10 nm
Spatial Resolution 20 m 30 m
Swath Width 12 km 7.5 km
SWIR SNR ~500:1 ~50:1
Multispectral Imaging (MSI) sensors usually have only a few spectral bands (
