Vol49_1_2006def 83 ANNALS OF GEOPHYSICS, VOL. 49, N. 1, February 2006 Key words hyperspectral imaging (HSI) – mineral mapping – AVIRIS – EO-1 Hyperion 1. Introduction Hyperspectral remote sensing, measuring hundreds of spectral bands from aircraft and satellite platforms, provides unique spatial/spec- tral datasets for analysis of surface mineralogy (Goetz et al., 1985; Kruse et al., 2003). These data allow mapping of key iron mineralogy such as hematite, goethite, and jarosite as well as alteration minerals such as kaolinite, dickite, alunite, and sericite (Clark et al., 1990). Their use for geologic applications is well established (Goetz et al., 1985; Kruse et al., 1999, 2003; Rowan and Mars, 2003). The Los Menucos, Rio Negro, Argentina, site (fig. 1) is a fossil analog of hot springs sim- ilar to modern systems in other locations around the world. This area has the largest significant concentration of advanced argillic, altered Per- mian ignimbrite and rhyolite assemblages in Ar- gentina (Franco et al., 2000). Alteration is relat- ed to the intrusion of Triassic-age (?) rhyolite dome complexes below thick Permian-age felsic volcanic rocks. Associated with dome fields are large areas of phreatic breccias and hematite- rich altered oxidized zones. Alteration is charac- District-level mineral survey using airborne hyperspectral data, Los Menucos, Argentina Fred A. Kruse (1), Sandra L. Perry (2) and Alejandro Caballero (3) (1) Horizon GeoImaging, LLC, Frisco, Colorado, U.S.A. (2) Perry Remote Sensing, LLC, Englewood, Colorado, U.S.A. (3) Rio Tinto Mining & Exploration Ltd., Santiago, Chile Abstract The Los Menucos District, Rio Negro, Argentina, provides an excellent case history of a complex epithermal gold system mapped and explored using a combination of field mapping and multispectral/hyperspectral remote sensing. The district offers a host of argillic and advanced argillic alteration minerals at the surface, many of which are difficult to identify visually. A strategy utilizing regional targeting with Landsat TM to optimize field mapping followed by district-level survey with hyperspectral imaging (HSI) data demonstrates the value added by high-spectral resolution aircraft data. Standardized analysis methods consisting of spatial and spectral data reduction to a few key endmember spectra provides a consistent way to map spectrally active minerals. Miner- als identified in the Los Menucos district using the JPL Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) include hematite, goethite, kaolinite, dickite, alunite, pyrophyllite, muscovite/sericite, montmoril- lonite, calcite, and zeolites. Hyperspectral maps show good correspondence with the results of field reconnais- sance verification and spectral measurements acquired using an ASD field spectrometer. Further analysis of Hy- perion (satellite-based) hyperspectral data indicates that similar mapping results can be achieved from satellite altitudes. These examples illustrate the high potential of hyperspectral remote sensing for geologic mapping and mineral exploration. Mailing address: Dr. Fred A. Kruse, Horizon GeoIma- ging, LLC, P.O. Box 4279, Frisco, Colorado 80443, U.S.A.; e-mail: kruse@hgimaging.com 84 Fred A. Kruse, Sandra L. Perry and Alejandro Caballero terized by vuggy silica, quartz stockwork, kaolin, and alunite. The Los Menucos gold dis- trict, with potential for low-sulfidation style gold mineralization, was discovered in 1998 by Arminex, S.A. using regional exploration meth- ods employing Landsat Thematic Mapper (TM) satellite imagery and field investigation (Gemuts and Perry, 2000; Perry and Gemuts, 2000). Over 100 sites were predicted as alteration anomalies resulting from digital enhancement of the Land- sat TM imagery analyzed by Perry Remote Sensing, LLC (PRS). These results were used to drive field exploration, and in less than one year, a field crew of six geologists systematically vis- ited and sampled all of these anomalies. Eighty percent of the areas visited exhibited epithermal- style alteration, and five percent were mineral- ized (Perry and Gemuts, 2000). The exploration effort led Arminex to assemble 80 000 ha near the village of Los Menucos and established the area as the first gold district in Rio Negro province. Early in 2000, Rio Tinto Mining & Exploration (RTZ) took an option on the Armi- nex property and agreed to continue drilling and testing at key prospect areas. Based on this work, the Los Menucos region was submitted and selected as a NASA E0-1 collection site dur- ing 2000 to evaluate Earth observation sensors, including hyperspectral (Airborne Visible/In- frared Imaging Spectrometer (AVIRIS) and sa- tellite EO-1 Hyperion) as well as multispectral data sets (Landsat 7 Enhanced Thematic Mapper and ASTER imagery). TM reconnaissance re- sults are published in Perry and Gemuts (2000). Fig. 1. Los Menucos, Argentina Site Location in Rio Negro province, Argentina. Black box marks approximate extent of AVIRIS survey conducted during February 2001. 85 District-level mineral survey using airborne hyperspectral data, Los Menucos, Argentina Initial AVIRIS results are summarized in Kruse et al. (2002a). An overview of the results of the combined TM reconnaissance and AVIRIS analysis are presented in Kruse et al. (2002b). Preliminary Hyperion, ETM and ASTER results are presented in Kruse et al. (2002c). Additional Hyperion results are summarized in Kruse et al. (2002a,d). Additional details and results for the AVIRIS and Hyperion data analysis are dis- cussed here. The principal airborne hyperspectral remote sensing instrument used for this research was the Airborne Visible/Infrared Imaging Spec- trometer (AVIRIS), a 224-channel hyperspec- tral sensor with approximately 10 nm spectral resolution covering the 0.4-2.5 nm spectral range (Porter and Enmark, 1987; Green et al., 2003). AVIRIS was flown by NASA/Jet Propul- sion Laboratory (JPL) over the Los Menucos District on a Twin Otter aircraft at low altitude on 14-15 February 2001. An AVIRIS dataset was collected consisting of 6 overlapping flight- lines (98 «scene» equivalents), covering an area approximately 11 km × 30 km at 3.5 m spatial resolution. These data are used to illustrate hy- perspectral analysis methods and specific analy- sis results for the Los Menucos District. 2. Methods A «standardized» hyperspectral data analy- sis methodology (fig. 2) has been tested for a variety of data (Boardman et al., 1995; Kruse et al., 1999, 2003). This approach is imple- mented and documented within the «Environ- ment for Visualizing Images» (ENVI) software system originally developed by AIG scientists (now a Research Systems (RSI) Commercial- Off-The-Shelf (COTS) product) (RSI, 2001). This is not the only way to analyze these data, but we have found that it provides a consistent way to extract spectral information from hyper- spectral data without a priori knowledge or re- quiring ground observations. Additional details are available in Kruse et al. (2003). The analy- sis approach consists of the following steps: – Correction for atmospheric effects using an atmospheric model «ACORN» (AIG, 2001) (fig. 3). – Spectral compression, noise suppression, and dimensionality reduction using the Mini- mum Noise Fraction (MNF) transformation (Green et al., 1988; Boardman, 1993). – Determination of endmembers using ge- ometric methods (Pixel Purity Index – «PPI») (Boardman and Kruse, 1994; Boardman et al., 1995). – Extraction of endmember spectra using n- dimensional scatter plotting (Boardman et al., 1995). – Identification of endmember spectra using visual inspection, automated identification, and spectral library comparisons (Kruse and Lefkoff, 1993; Kruse et al., 1993). Fig. 2. AIG «hourglass» hyperspectral data pro- cessing scheme. Large HSI datasets are reduced to a few key spectra (at the neck of the hourglass) that ex- plain the data using spatial and spectral data reduc- tion techniques (Boardman et al., 1995). Pixel-based spectral mapping methods are then applied to the full HSI dataset. 86 Fred A. Kruse, Sandra L. Perry and Alejandro Caballero – Production of mineral maps using a variety of mapping methods. «Mixture-Tuned-Matched- Filtering» (MTMF) used for this work is basical- ly a partial linear spectral unmixing procedure (Boardman, 1998). – Geometric correction of analysis results using sensor models and aircraft or satellite navigation information (Boardman, 1999). 3. Results 3.1. General Each of the six AVIRIS flightlines was processed using the above procedures and ana- lyzed separately in reconnaissance mode (opti- mized for the complete dataset, not individual Fig. 3. Comparison of selected AVIRIS radiance spectra (top) and corresponding ACORN reflectance spectra (bottom). Spectrum A is a kaolinite-bearing rock, spectrum B a clay-bearing rock, and spectrum C is green veg- etation. 87 District-level mineral survey using airborne hyperspectral data, Los Menucos, Argentina sites), then combined as a spatial mosaic to pro- duce mineral maps of the entire coverage. Two spectral ranges were analyzed; 1) 0.4-1.3 nm (iron oxides), and 2) 2.0-2.5 nm (clays, carbon- ates, etc). The results were map-corrected and combined into an image mosaic covering an ap- proximately 10 km × 30 km area covering sever- al key mineral prospects. While the complete dataset was analyzed, only Los Menucos AVIRIS flightline #2, covering several of the Fig. 4a,b. a) AVIRIS endmember spectra and mapping results for Los Menucos AVIRIS flightline #2. b) An example of an image-map produced using MTMF for the Los Menucos AVIRIS flightline #2 SWIR data. MTMF mineral mapping was performed using the endmembers selected and identified using the n-dimensional visual- ization and spectral identification procedures described above and shown in a). MTMF scatterplotting was used to select the spectrally predominant mineral for each pixel at abundances greater than 10% and to color-code the selected pixels in colors matching the endmember spectra. a b 88 Fred A. Kruse, Sandra L. Perry and Alejandro Caballero RTZ prospects is shown here as an example of typical AVIRIS processing results using the above methods. Minerals identified as above for the Los Menucos AVIRIS flightline #2 SWIR data in- clude several common alteration minerals such as kaolinite, muscovite, alunite, silica, pyrophylite, calcite, montmorillonite, chlorite-epidote, and ze- olites (fig. 4a,b). Additionally, because of the high SNR of the AVIRIS data, we were able to discriminate different within-species spectral dif- ferences. Thus several varieties of kaolinite and muscovite were also identified (fig. 4a,b). Field reconnaissance was conducted during April 2001 to validate areas delineated by the AVIRIS analysis. AVIRIS mineral maps were used along with Landsat TM mapping as base maps for field verification. Several prospects and other mineralogically interesting areas were vis- ited, the rocks and alteration were examined, and samples were collected. These samples were an- alyzed utilizing an Analytical Spectral Devices (ASD) «FieldSpec Full Range» field spectrome- ter (see http://www.asdi.com) provided by Jet Propulsion Laboratory. The ASD spectrometer covers the 0.35-2.5 nm range with approximate- ly 3 nm (VNIR) and 10 nm (SWIR) spectral res- olution and 1 nm spectral sampling. A «wand» attachment containing a halogen light source was used to illuminate the samples. This results in a high-quality spectrum with 2151 spectral bands, allowing identification of specific minerals. Over 160 spectral measurements were made of various rocks and soils from the Los Menucos area. Spectral libraries were used to validate and refine AVIRIS results, and to apply to EO-1 Hyperion and Landsat/ASTER multispectral evaluation. 3.2. AVIRIS Pyrophyllite Discovery The AVIRIS data pointed out several miner- als and mineral assemblages that were not readi- ly apparent utilizing conventional field mapping methods. In particular, several previously un- known pyrophyllite occurrences cross-cutting predominant structural trends were detected and mapped using the SWIR data (Kruse et al., 2002a,b). These have generated some interest for further exploration. Northwest-trending struc- tures apparently controlled the distribution of both well-crystalline and poorly crystalline kaoli- nite (fig. 5a,b). Both dickite and pyrophyllite, geochemical indicators of higher temperatures appear to terminate and/or crosscut the kaolinite occurrences (fig. 5b,c). On-the-ground field checking of the pyrophyllite areas showed noth- ing obvious at these locations. The ground sur- face was flat, no outcrop was exposed, and it con- sisted principally of soil with small rock frag- ments. Map positioning was double checked us- ing GPS and ASD field spectral measurements showed that indeed the principal soil mineral was pyrophyllite (fig. 5d). The spectral signatures, image patterns, and surface exposure indicate that these areas are highly weathered surface ex- posures of altered rock. Further investigation is required to determine their economic potential. 3.3. Los Menucos, Argentina Hyperion example Hyperion data for the Los Menucos, Ar- gentina, site were first acquired on 25 February 2001, close to the 14-15 February AVIRIS ac- quisition date. Hyperion is a satellite hyperspec- tral sensor covering the 0.4 to 2.5 nm spectral range with 242 spectral bands at approximately 10 nm spectral resolution and 30 m spatial res- olution from a 705 km orbit (Pearlman et al., 1999). Unfortunately, the Hyperion data were predominantly cloudy and because of low solar zenith angle, Signal-to-Noise Ratios (SNR) cal- culated for this scene were in the 20:1 range, marginal for successful mineral identification and mapping (Kruse et al., 2003). This exam- ple, does, however, serve to demonstrate the po- tential of satellite hyperspectral data for miner- al mapping. The «Cuya» and «Kaolinite Hills» sites shown in fig. 6a-d were mostly clear on the 25 February Hyperion acquisition date. These data were processed to geologic products using the approaches described above for extraction of mineralogic and geologic information. Several characteristic mineral spectra (silica, kaolinite, muscovite) were extracted from the Los Menu- cos Hyperion data (fig. 6a-d). Mineral maps were produced and compared to those derived from the AVIRIS data above (fig. 6a-d). Com- 89 District-level mineral survey using airborne hyperspectral data, Los Menucos, Argentina parison of the two datasets shows that Hyperi- on identifies similar minerals and produces grossly similar mineral mapping results as AVIRIS, however, it does not produce the level of detail available from the AVIRIS data. Some minerals are missed, and others are confused (dickite/kaolinite). The kaolinite doublet shown for AVIRIS data (fig. 6c) is not fully resolved Fig. 5a-d. Geocorrected Pyophyllite Discovery AVIRIS results. a) False Color Infrared composite (CIR) image of bands 31, 19, 9 (0.66, 0.55, 0.45 nm) as RGB. b) SWIR mineral mapping results. Note pyrophyllite occur- rence in center of image crosscutting northwest-trending kaolinite distributions. c) AVIRIS endmember spectra: red is well crystalline kaolinite, green is poorly crystalline kaolinite, blue is dickite, and orchid is pyrophyllite. d) ASD field spectra for mineral occurrences mapped using AVIRIS. Colors are the same as for the AVIRIS end- members. a b c d 90 Fred A. Kruse, Sandra L. Perry and Alejandro Caballero Fig. 6a-d. a) Image-map of selected endmembers from geocorrected AVIRIS SWIR data. Dark green is Cuya area with hydrothermal silica ± clay signature. Red is Kaolinite Hills area with kaolinite signature. Bright Green area is poorly crystalline kaolinite (spectrum not shown). Magenta shows areas with muscovite signatures. b) Hyperion grayscale image with MTMF mineral map overlay for the same approximate area: colors are the same as for AVIRIS. White areas are clouds and dark areas are cloud shadows. c,d) Hyperion endmember spectra. by Hyperion (fig. 6d). This is largely the effect of reduced Hyperion signal-to-noise-perform- ance compared to the AVIRIS (∼ 20:1 and less for these Hyperion data, compared to > 500:1 for AVIRIS) (Kruse et al., 2003). The Hyperion data, however, illustrate the potential for world- wide hyperspectral mapping using satellite HSI systems. Suggestions are, that based on im- proved detector performance and more sophis- ticated design, that future sensor systems will a b c d 91 District-level mineral survey using airborne hyperspectral data, Los Menucos, Argentina likely approach current AVIRIS mapping per- formance (R. Green, 2003, pers. comm.). 4. Discussion and conclusions The Los Menucos district AVIRIS case histo- ry presented here illustrates the use of hyper- spectral data to perform a district-level mineral survey. Initially discovered using Landsat TM multispectral imagery, the district was further mapped and explored using hyperspectral imag- ing systems (AVIRIS and Hyperion). High-qual- ity, high spatial resolution (3.5 m) AVIRIS data were the key to rapid assessment of the detailed mineralogy of this area, pointing out minerals and mineral assemblages that were not readily apparent utilizing conventional field mapping methods. Nearly 100 AVIRIS scenes covering an approximately 10 × 30 km area were analyzed using standardized HSI analysis methods con- sisting of spatial and spectral reduction of the hy- perspectral data to just a few key endmember spectra. Partial unmixing using Mixture-Tuned- Matched-Filtering (MTMF) provided a consis- tent way to process the multiple AVIRIS flight- lines allowing identification and mapping of VNIR- and SWIR-active minerals. Common al- teration minerals such as hematite, goethite, kaolinite, dickite, alunite, pyrophyllite, mus- covite/sericite, montmorillonite, calcite, and zeo- lites were mapped. Distinguishing between sim- ilar minerals such as kaolinite and dickite and mapping of muscovite variability related to cation substitution was possible because of the high SNR of the AVIRIS sensor. AVIRIS map- ping results closely agree with field reconnais- sance and ground spectral measurements. Analy- sis of a Hyperion dataset generally validates in- orbit mineral mapping and sets the standard for future satellite hyperspectral system perform- ance. These examples illustrate the high poten- tial of hyperspectral remote sensing for geologic mapping and mineral exploration. Acknowledgements This research was partially funded by NASA under grant NCC5-495. Additional fi- nancial support was provided by Analytical Imaging and Geophysics, LLC and Perry Re- mote Sensing, LLC internal research and devel- opment funds. The Argentina test site was sug- gested by Sandra Perry, Perry Remote Sensing LLC, Englewood, Colorado, U.S.A. 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