Regional mineral mapping of island arc terranes in southeastern Mongolia using multi-spectral remote sensing data

Journal Pre-proofs Regional mineral mapping of island arc terranes in southeastern Mongolia using multi-spectral remote sensing data Young-Sun Son, Kwang-Eun Kim, Wang-Jung Yoon, Seong-Jun Cho PII: DOI: Reference:

S0169-1368(18)30877-1 https://doi.org/10.1016/j.oregeorev.2019.103106 OREGEO 103106

To appear in:

Ore Geology Reviews

Received Date: Revised Date: Accepted Date:

20 October 2018 4 August 2019 29 August 2019

Please cite this article as: Y-S. Son, K-E. Kim, W-J. Yoon, S-J. Cho, Regional mineral mapping of island arc terranes in southeastern Mongolia using multi-spectral remote sensing data, Ore Geology Reviews (2019), doi: https:// doi.org/10.1016/j.oregeorev.2019.103106

This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

© 2019 Elsevier B.V. All rights reserved.

Regional mineral mapping of island arc terranes in southeastern Mongolia using multi-spectral remote sensing data

Young-Sun Sona, Kwang-Eun Kima*, Wang-Jung Yoonb, Seong-Jun Choa aKorea

Institute of Geoscience and Mineral Resources, Daejeon 34132, Republic of Korea

bDepartment

of Energy & Resources Engineering, Chonnam National

University, Gwangju 61186, Republic of Korea

*Corresponding author. E-mail address: [email protected] Abstract Over the last few decades, many porphyry Cu deposits have been discovered in southeastern (SE) Mongolia. In particular, the Gurvansayhan and Mandalovoo island arc terranes, have high potential for ore deposits. Regional mineral mapping of these terranes using data from the Landsat Enhanced Thematic Mapper Plus (ETM+) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) provided have new geological information on the metallogenic province, revealing potential mineral deposits for future explorations. Iron oxides/hydroxides with high ETM+ band 1/3 ratio values occur extensively in Quaternary deposits located at the boundary between the Gurvansayhan and Mandalovoo island arcs terranes and basins. The high average band

1

ratios (>1.35) registered for the porphyry Cu and Au deposits and their occurrences are associated with iron oxidation which originates from the erosion and weathering of ore zones. Regional mapping of the island arc terranes using the ASTER shortwave infrared (SWIR) logical operators showed circular or semicircular alteration patterns which usually cluster along faults. The mineral assemblages mapped by the ASTER SWIR analysis in five major porphyry Cu districts can be divided into two types. The first type includes argillic, phyllic, and propylitic mineral assemblages, as exemplified by the Shuteen, Ikh Shankhai, and Oyu Tolgoi deposits. The second type of assemblage includes phyllic and propylitic mineral assemblages, as exemplified by the Kharmagtai and Tsagaan Suvarga deposits. Within the deposits of the first type, quartz was also mapped using the ASTER thermal infrared (TIR) mineral index. The difference between the two types may be related to the presence of a lithocap. The results of a field survey including spectral reflectance measurements in the Ikh Shankhai porphyry Cu district, showed a good correlation with the image analysis results.

Keywords: ASTER, ETM+, Mineral mapping, Porphyry Cu deposit, Mongolia

1. Introduction Mongolia is located within the Central Asian Orogenic Belt (CAOB), one of the largest orogenic belts in the world. It is positioned between the Siberian craton to the north and the Tarim and North China cratons to the south (Fig. 1). Several models have been proposed for the evolution of the CAOB. Sengor et al. (1993) inferred that the

2

CAOB was formed by the oceanward growth of a huge subduction-accretion complex and arc segments by strike-slip stacking. It has also been suggested that it may have been formed by the subduction and accretion of multiple oceanic basins accompanied by the development of individual magmatic arcs (e.g., Badarch et al., 2002; Buchan et al., 2002; Khain et al., 2002; Xiao et al., 2008, 2009; Wainright et al., 2011). The marginal continental magmatic belt extends over the entire region of southern Mongolia, which features a former suite of differentiated calk-alkaline material with plutonic massifs, as well as a later suit of bimodal complexes with peralkaline granite massifs (Yarmolyuk et al., 2008). The processes of arc growth and accretion in southern Mongolia contributed to the formation of the southeast Gobi mineral belts which include many Au- and Morich porphyry Cu deposits (e.g., Oyu Tolgoi and Tsagaan Suvarga) and other intrusionrelated occurrences including skarns and epithermal veins (e.g., Ikh Shankhai and Uzuur Cun Khudag) (Blight et al., 2008, 2010; Fig. 2a). In particular, many porphyry Cu deposits mainly associated with Devonian to Carboniferous subduction-related magmatism (e.g., Tsagaan Suvarga, Kharmagtai, and Oyu Tolgoi deposits) have been discovered in the Gurvansayhan and Mandalovoo island arc terranes in southeastern (SE) Mongolia (Fig. 2b) and consequently these island arc terranes are now a major mineral exploration region (Lamb and Cox, 1998; Perello et al., 2001; Blight et al., 2008; Batkhishig et al., 2010). Porphyry Cu systems supply nearly three quarters of the world’s Cu, half of the Mo, and one-fifth of the Au. These deposits show a consistent, broad-scale alteration zoning pattern which is composed of sodic-calcic, potassic, chlorite-sericite, sericitic (phyllic), advanced argillic (or argillic), chloritic and propylitic alterations (Fig. 3; Sillitoe, 2010). These alteration minerals have diagnostic spectral characteristics in the visible-near

3

infrared (VNIR: 0.4 – 1.3 µm), shortwave infrared (SWIR: 1.3 – 2.5 µm), and thermal infrared (TIR: 8 – 14 µm) (Fig. 4). Remote sensing analysis in alteration mapping is generally focused on identifying advanced argillic (or argillic), phyllic and propylitic alterations (Ducart et al., 2006; Mars and Rowan, 2006; Rowan et al., 2006; Son et al., 2014a). The Landsat Enhanced Thematic Mapper Plus (ETM+) has a wide observation range (170 × 185 km) and consists of bands which are effective for mineral exploration. They include four VNIR bands, two SWIR bands (spatial resolution 30 m), and one TIR band (spatial resolution 60 m). The ETM+ also has a panchromatic band (0.52 – 0.90 µm), which has a 15-m spatial resolution (Table 1). The Landsat series of remote sensing satellites (e.g., Multispectral Scanner (MSS), Thematic Mapper (TM), and ETM+) are used to map hydrothermal altered rocks (Rowan et al., 1977; Sabins, 1999; Langford, 2015). The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) has three optical sensor subsystems (VNIR, SWIR, and TIR), with a total of 14 bands and a swath width of 60 km. It includes three bands in VNIR (0.52–0.86 µm), six bands in SWIR (1.6–2.43 µm), and five bands in TIR (8.12–11.65 µm), with spatial resolutions of 15, 30, and 90 m, respectively (Table 1; Yamaguchi et al., 1998). ASTER has been used successfully for geological remote sensing due to its narrow spectral bands, especially in the SWIR and TIR regions. These spectral bands are able to identify and discriminate hydrothermal alteration minerals, silicates, and carbonates (Rowan and Mars, 2003; Ninomiya et al., 2005; Mars and Rowan, 2006). Although the ASTER SWIR subsystem was discontinued in 2008, the ASTER TIR subsystem is still in operation, and 2.8 millions of global land surface images have been archived (Cudahy et al., 2016). The Landsat missions have also maintained data continuity through Landsat 8, which was

4

launched in February 2013. The time and cost of mineral exploration is increased in SE Mongolia due to its large surface area (160,000 km2) and very long and harsh winters (average temperature of −10 °C from November to April). Remote sensing techniques are effective in identifying surface anomalies (e.g., hydrothermal alterations, faults, lineaments), which are often associated with ore deposits, while reducing the cost and time of field surveys at regional scale (Hewson et al., 2005; Mars and Rowan, 2006; Ducart et al., 2006; Rowan et al., 2006; Di Tommaso and Rubinstein, 2007; Pour et al., 2013; Rajendran et al, 2013; Naghadehi et al., 2014; Liu et al., 2017). The aim of this study is to identify areas associated with mineral deposits within the Gurvansayhan and Mandalovoo island arc terranes (SE Mongolia). To achieve this, we used six Landsat ETM+ and thirty ASTER image datasets to map the distribution of minerals associated with iron oxide/hydroxide, argillic, phyllic, and propylitic alteration. Through this study, we identified the distribution of altered minerals on the surface of five well-known porphyry Cu deposits in the Gurvansayhan and Mandalovoo island arc terranes, and proposed four potential porphyry Cu districts by combining the multispectral remote sensing datasets and the mineralogical and structural properties in porphyry Cu system.

2. Geological setting The tectonic boundary of Mongolia is traditionally divided into a northern and southern domain by the Main Mongolian Lineament (MML), which is a regional topographic and structural boundary (Badarch et al., 2002; Fig. 1). During the Paleozoic, 5

the southern domain underwent accretionary events, which resulted in joining of a number of island and continental margin magmatic arcs, rifted and back-arc basins, accretionary wedges, and continental margins (Perello et al., 2001; Windley et al., 2007; Blight et al., 2008; Rippington et al., 2008; Wainlight et al., 2011; Fig.2a, b). The study area is located in the southern domain of the MML and is dominated by two OrdovicianCarboniferous island arc terranes (Mandalovoo and Gurvansayhan) which are enclosed within the Gobi Altai and Nuhetdavaa backarc/forearc, the Zoolen accretionary wedge, and the Zuunbayan Cenozoic alluvial basins (Fig. 2a). The island arc terranes contain fragments of dismembered ophiolites, melanges, and island arc volcanic and volcaniclastic rocks. These are generally interpreted as being derived from Middle to Late Paleozoic ocean basin deposits and island arc sequences (Lamb and Badarch, 1997; Badarch et al., 2002). These two terranes were emplaced as along-strike equivalents of a contiguous island arc, but a series of dextral strike-slip faults shunted the Gurvansayhan terrane southwest to its current location (Badarch et al., 2002; Blight et al., 2008). The Mandalovoo terrane is a long, narrow belt in the northern part of the southern domain of the MML (Fig 2a). It consists of a deformed stratigraphic succession of Ordovician to Carboniferous volcanic and sedimentary rocks (Lamb and Badarch, 1997; Badarch et al., 2002). The post-accretion assemblages of the terrane include Upper Carboniferous-Permian volcanic, sedimentary rocks, and granite plutons, as well as Jurassic-Cretaceous clastic rocks (Fig. 5). The Gurvansayhan terrane is located to the south of the Mandalovoo terrane (Fig. 2a). The structure of the Gurvansayhan terrane is complex and dominated by imbricate thrust sheets, dismembered blocks, melange, and high-strain fault zones. The terrane comprises Ordovician-Silurian sedimentary and

6

volcaniclastic rocks, as well as Upper Silurian-Lower Carboniferous sedimentary and volcanic rocks. Moreover, it is overlain by Carboniferous, Permian, Jurassic, and Cretaceous volcanic and sedimentary rocks (Badarch et al., 2002; Fig. 5). Granitoid magmatism comprises Devonian, Carboniferous, Permian, and Early Mesozoic plutons and volcanic-plutonic complexes (Fig. 2a). Lower Carboniferous post-tectonic syenite plutons are widely distributed within the Gurvansayhan terrane (Lamb and Cox, 1998; Perello et al., 2001; Badarch et al., 2002). The processes of arc growth and accretion in SE Mongolia were responsible for the formation of the SE Gobi mineral belts and Au-rich and Mo-rich porphyry Cu deposits (e.g., Oyu Tolgoi, Tsagaan Suvarga and Kharmagtai; Dejidmaa et al., 2005; Fig. 2). At Oyu Tolgoi, Cu-Au mineralization occurred from the late Silurian to the early Devonian producing the monzonitic feldspar-hornblende and feldspar porphyries that are thought to have been emplaced during the initial stages of arc evolution (Perello et al., 2001). The Tsagaan Suvarga Cu-Mo deposit is associated with small intrusions and dykes that consist of diorite, granodiorite and syenite (Lamb and Cox, 1998). The Kharmagtai Cu-Au mineralization is associated with the Lower Carboniferous Kharmagtai intrusive complex, which was emplaced into a Late Devonian volcano-sedimentary sequence (MA, 2015).

3. Porphyry copper systems and their spectral characteristics Sillitoe (2010) defined porphyry Cu systems as large volumes (10–100 km3) of hydrothermally altered rock centered on porphyry Cu stocks, which may also contain skarn, carbonate-replacement, sediment-hosted, high- to intermediate-sulfidation 7

epithermal base, and precious metal mineralization (Fig. 3). The regional- and districtscale characteristics of porphyry Cu systems are as follows: (1) They show a tendency to occur in linear, typically orogen-parallel belts, which range from a few tens to thousands of kilometers in length. (2) They are generated mainly in favorable tectonic settings, such as volcanic and plutonic arcs (including back-arcs) in subduction environments and paleosubduction zones. (3) The intersection between continental scale transverse fault zones or lineaments and arc-parallel structures is an important factor for porphyry Cu formation. (4) At district scale, porphyry copper and other deposits occur as clusters or alignments which may reach 5 – 30 km in width or length, respectively (Pirajno, 1992; Tosdal and Richards, 2001; Sillitoe and Perello, 2005; Sillitoe, 2010). Porphyry Cu deposits are generated by hydrothermal fluid processes which accompany porphyry emplacement and alter the mineralogy and geochemistry of the host rocks. The alteration-mineralization zoning sequence typically affects several kilometers of rock; the volume of the alteration zone varies between deposits (Lowell and Guilbert, 1970; Guilbert and Park, 1986; Hedenquist et al., 1998; Sillitoe, 2000, 2010; Seedorff et al., 2005). The expected alteration zones expected in a porphyry system, associated mineral assemblages, and the spectral features of those assemblages are summarized in Table 2. Sodic-calcic alteration, which mainly bears magnetite, is uncommon and occurs in the central, deepest part of some porphyry Cu systems (e.g., in Koloula, Solomon Island and British Columbia; Chivas, 1978; Arancibia and Clark, 1996). This alteration zone can locally contain ore, although the economic potential is generally poor. Potassic alteration, in which biotite and K-feldspar predominate, is ubiquitous in the core zones of the

8

porphyry Cu deposits and constitutes the main ore zone. Chlorite-sericite alteration, which is dominated by illite and hematite, is common in the upper parts of some porphyry Cu core zones and overprints pre-existing potassic alteration zone. The alteration zone often carries ore grade metal endowments (Harris et al., 2005; Masterman et al., 2005). Sericitic alteration, which overprints the potassic and chlorite-sericite alteration zones, is universal in porphyry Cu deposits. This type of alteration has commonly a low economic potential, but it may contain constitute ore depending on the economics of the deposit. The top of porphyry Cu systems are characterized by lithocaps which generally have a well-developed advanced argillic alteration. The advanced argillic lithocaps, which contain mainly quartz, alunite, pyrophyllite, dickite, kaolinite, and, sometimes, local ore, may overprint the sericitic and chloritic alterations. Propylitic alteration including epidote, chlorite, albite, and carbonates occurs in the marginal parts of the systems, below the lithocaps, and is not an economically important part of the porphyry system unless it contains significant subepithermal veining (Sillitoe, 2010). Many of these mineral associates with these alteration zones have characteristic spectral features which allow for their identification by remote sensing data. Kaolinite, alunite (advanced argillic alteration), and sericite (sericitic alteration) have intense AlOH absorption features in the SWIR. The specific absorption positions of these minerals are 2.17, 2.18, 2.21, and 2.33 µm (Table 2; Fig. 4a). These spectral differences in terms of position and depth allow to distinguish between argillic and sericitic alterations using remote sensing data (Mars and Rowan, 2006, Rowan et al., 2006). Propylitic and chloritic alterations (e.g., epidote, chlorite and carbonates) display strong absorption at 2.22, 2.30,

9

and 2.35 µm, based on the vibrational overtones of Fe-OH and CO3 (Table 2; Fig. 4a). These spectral features contrast strongly with those of sericitic and argillic minerals. Many silicate minerals (e.g. quartz, K-feldspar) typically do not have characteristic spectral features in the VNIR and SWIR regions. In contrast, they display distinctive spectral features in the TIR region, as a result of the stretching and bending vibrations of the Si-O bond. Figure 4b illustrates the spectral features of a variety of silicate minerals in the TIR region (8 – 14 µm). The minimum emissivity for felsic minerals (quartz, Kfeldspar) occurs at relatively short wavelengths, while that for mafic minerals (olivine, hornblende) occurs at longer wavelengths of TIR domain (Salisbury and D'Aria, 1992; Clark, 1999; Hook et al., 1999; Ninomiya et al., 2005). Iron oxide (e.g., hematite, goethite) and sulfate (e.g., jarosite) minerals, which commonly occur in oxidized caps over ore deposits, show diagnostic spectral features in the VNIR range (0.4 – 1.3 µm) and result from electronic processes associated with Fe (e.g., crystal field and charge transfer effects by Fe2+ or Fe3+ ions; Hunt, 1977; Goetz and Rowan, 1981;

Fig. 6). Jarosite also has spectral features in the SWIR regions, due to

the vibrational overtones of Fe-OH.

4. Methods 4.1. ETM+ data analysis The six orthorectified Landsat ETM+ scenes used in this study were acquired between August – October 2000 (Fig. 7a). Orthorectified Landsat ETM+ data are corrected for erroneous image displacements caused by the interaction between terrain reliefs (or local 10

elevation changes) and variations in sensor orientation (Tucker et al., 2004). The orthorectified Landsat ETM+ scenes were calibrated from digital numbers (DN) to reflectance using FLAASH atmospheric correction software that incorporated the MODTRAN4 radiation transfer code (Adler-Golden et al., 1999). These reflectance scenes were used to make a mosaic image. The presence of vegetation, water, snow, and relief shadow in the pixels impacts the accuracy of image analysis for mineral mapping. To eliminate the effects of vegetation, water, snow, and relief shadow, a series of mask images were produced by applying a normalized difference vegetation index (NDVI; Rouse et al., 1974), normalized difference water index (NDWI; McFeeters, 1996), normalized difference snow index (NDSI; Hall et al., 1995), and a histogram thresholding for the dark pixels and were applied to the reflectance images. Band ratio analysis is widely used for mineral and lithology mapping because it can emphasize subtle spectral differences between the target and background materials (Rowan et al., 1977; Goetz and Rowan, 1981; Sultan et al., 1987). Secondary minerals associated with weathering or hydrothermal systems, such as iron oxide, iron hydroxide, and sulfates (e.g., hematite, goethite, jarosite), have high reflectance in ETM+ band 3 but low reflectance in ETM+ band 1 (Fig. 6; Sabins, 1999). The ETM+ band ratio 3/1 was used to distinguish iron-rich rocks from those that do not contain iron minerals.

4.2. ASTER data analysis 4.2.1 . Data and preprocessing In this study, 15 ASTER Level 1B (L1B) radiance-at-sensor images and 15 Level 2B04 (L2B04) TIR emissivity images were used. These images covered the five major

11

porphyry Cu deposits occurring within the island arc terranes of SE Mongolia (Fig. 7). The 6 SWIR bands of L1B data (30-m spatial resolution) and the 5 TIR bands of 2B04 data (90-m resolution) were resized to the VNIR 15-m spatial resolution by using a 2× and 6× pixel duplication of the SWIR and TIR data, respectively. Each of the 30 ASTER images used in this study were taken from four different viewing angles, ranging from 8.59 to 5.73 degrees off nadir, resulting misregistration (Rockwell and Hofstra, 2008; Mars and Rowan, 2010). Therefore, each ASTER image was geometrically registered at a 14.25-m resolution panchromatic band of the orthorectified Landsat ETM+. We selected 20 ground-control points for each image; their root mean square errors were < 0.1. The SWIR bands of ASTER are affected by a crosstalk phenomenon, which distorts radiance values in the SWIR bands (especially in band 4 and band 9), resulting in false reflectance spectra (Rowan and Mars, 2003; Iwasaki and Tonooka, 2005; Mars and Rowan, 2010; Son et al., 2014b). The crosstalk correction algorithm of Iwasaki and Tonooka (2005) and the radiometric correction factors of Biggar et al. (2010) were applied to each ASTER L1B SWIR radiance data set to obtain accurate surface reflectance data. Then, the crosstalk and radiometrically corrected 6 SWIR bands and 3 VNIR bands were combined. The 9 VNIR-SWIR bands were calibrated to reflectance using FLAASH atmospheric correction software that incorporated the MODTRAN4 radiation transfer code (Adler-Golden et al., 1999). The masking for removal of the effects of vegetation, water, snow, and relief shadow in the same method as Landsat ETM+ data was applied to the ASTER VNIR-SWIR reflectance data. To minimize the noise of the ASTER TIR bands, a minimum noise fraction (MNF) transform analysis was applied to each ASTER L2B04 image. The MNF transform produces decorrelated data, and organizes the transformed images in terms of decreasing 12

data variance (Green et al., 1988). The four high-order eigenvalue bands (MNF bands 1 – 4 and excluding the extremely noisy MNF band 5) were used to create inverted TIR bands (1 – 5). Consequently, noise and contrast were reduced and improved, respectively, in the inversed TIR bands (Son et al., 2014a).

4.2.2 . ASTER SWIR logical operators Mars and Rowan (2006) suggest the use of band ratio logical operator algorithms, based on ASTER SWIR bands, to map argillic and phyllic altered rocks. Each logical operator algorithm consists of a series of band ratios. If a pixel satisfies the conditions of all ratios in the algorithm, the output byte will be assigned a value of ‘1’ (true); otherwise, it will be assigned a value of ‘0’ (false). We used these logical operator algorithms for the regional scale mapping of hydrothermal altered rocks. All pixels extracted by the logical operator algorithms were median filtered for noise removal. The derived-ASTER alteration pixels were then converted to vector data and overlain on band 1 of Landsat ETM+. The argillic band ratio logical operator (ABRLO) algorithm (Mars and Rowan, 2006) considers the reflectance of an argillic altered rock, composed of kaolinite and alunite (Figs. 4a and 8a). It is defined by: 𝐴𝐵𝑅𝐿𝑂 = (𝐵𝑎𝑛𝑑4 > 2600) 𝑎𝑛𝑑

𝐵𝑎𝑛𝑑4 𝐵𝑎𝑛𝑑5 > 1.22 𝑎𝑛𝑑 1.05 𝑎𝑛𝑑 𝐵𝑎𝑛𝑑5 𝐵𝑎𝑛𝑑6 ≤

(

) (

(

𝐵𝑎𝑛𝑑7 > 1.03 (1) 𝐵𝑎𝑛𝑑6

)

13

)

Argillic minerals commonly display Al-OH absorption features near 2.17 and 2.20 µm (ASTER band 5 and band 6; Figs. 4a and 8a). The ASTER band ratios 4/5 and 7/6 are used in the ABRLO to extract the Al-OH absorption feature of argillic minerals. The ratio 5/6 is needed to distinguish argillic alteration from phyllic alteration because band 5 reflectance of phyllic mineral is much larger than band 6 reflectance, while band 5 reflectance of argillic mineral slightly larger or smaller than band 6 reflectance (Mars and Rowan, 2006). The phyllic band ratio logical operator (PBRLO) algorithm applies the spectral features of a phyllic altered rock, composed of muscovite and is nearly identical to the ABRLO algorithm (Figs. 4a and 8a). The PBRLO is defined as: 𝑃𝐵𝑅𝐿𝑂 = (𝐵𝑎𝑛𝑑4 > 2600) 𝑎𝑛𝑑

𝐵𝑎𝑛𝑑4 𝐵𝑎𝑛𝑑5 > 1.30 𝑎𝑛𝑑 > 1.15 𝑎𝑛𝑑 𝐵𝑎𝑛𝑑6 𝐵𝑎𝑛𝑑6

(

) (

)

𝐵𝑎𝑛𝑑7 > 1.03 (2) 𝐵𝑎𝑛𝑑6

(

)

Muscovite usually shows Al-OH absorption features only near 2.20 µm (ASTER Band 6), unlike argillic minerals (Figs. 4a and 8a). The ratios 4/6 and 7/6 in the PBRLO can be applied to extract the Al-OH absorption feature of muscovite, while the ratio 5/6 scan distinguishes phyllic alterations from argillic and propylitic alterations (Mars and Rowan, 2006). We applied to the ABRLO and PBRLO algorithms the same threshold ratio values proposed by Son et al. (2014a) who applied them to the Oyu Tolgoi region (Mongolia) after evaluating them in the Cuprite region (U.S.).

4.2.3 . ASTER TIR mineralogical indices

14

We used a quartz index (QI) and mafic index (MI3), which are closely correlated to the bulk SiO2 content (felsic rock: SiO2 > roughly 63 %; intermediate – mafic rocks: SiO2 content < roughly 63 %; Le Maitre, 2002). The indices were calculated using the ASTER L1B TIR radiance data without atmospheric correction (Ninomiya et al., 2005), and based on the TIR emissivity characteristics of mafic vs. felsic minerals (Figs. 4b and 8b):

𝑄𝐼 =

𝑀𝐼3 =

(𝐵𝑎𝑛𝑑11 × 𝐵𝑎𝑛𝑑11) (3) (𝐵𝑎𝑛𝑑10 × 𝐵𝑎𝑛𝑑12)

(𝐵𝑎𝑛𝑑12 × 𝐵𝑎𝑛𝑑143) (𝐵𝑎𝑛𝑑134)

(4)

The emissivity spectrum of quartz commonly displays higher values at 8.60 µm (ASTER band 11) than at 8.50 µm (bands 10) and 8.95 µm (band 12) (Figs. 4b and 8b). The QI has been used effectively to map quartzite, as well as of siliceous and siliciclastic rocks (Ninomiya et al., 2005; Mitsuishi et al., 2012). On the other hand, the MI3 has been used to map mafic and ultramafic rocks such as basalt and gabbro (Ninomiya et al., 2005). The minerals that make up the intermediate mafic rocks usually have lower emissivity at 10.5 µm (ASTER band 13) than at 8.6 µm (ASTER band 11) (Fig. 8b), while felsic minerals show an opposite spectrum shape which has higher emissivity at 10.5 µm (ASTER band 13) than at 8.6 µm (ASTER band 11). The inverse QI, here named the Alkali Index (AI), is effective in mapping the spectral emissivity feature of alkali (K-) feldspars, such as orthoclase (Ninomiya et al., 2005; Di Tommaso and Rubinstein, 2007). In contrast to quartz, orthoclase has lower emissivity in band 11 than in band 10 and 12 (Fig. 8b). AI is defined as: 𝐴𝐼 =

(𝐵𝑎𝑛𝑑10 × 𝐵𝑎𝑛𝑑12) (5) (𝐵𝑎𝑛𝑑11 × 𝐵𝑎𝑛𝑑11)

15

The pixels derived from the mineralogical indices were converted to vector data and overlaid on band 1 of the Landsat ETM+.

4.2.4 . ASTER SWIR matched filter analysis Matched filter processing is a spectral detection mapping technique used to maximize the signal of the target spectrum of interest, while suppressing all background spectra (Mustard and Sunshine, 1999). Previous studies using ASTER data showed that matched filter processing is effective for identification and mapping of surface mineralogy (Rowan and Mars, 2003; Hubbard et al., 2003; Bedini 2011). However, it is first necessary to select the representative reflectance spectra of the mineral classes of interest, which will be referenced to during image analysis. These reference spectra (or endmembers) for matched filtering can be selected from laboratory or image spectra; however, it is more efficient to select image spectra, rather than laboratory spectra acquired under different measurement conditions (Bedini, 2011). In this study, the endmembers used to map the spatial distribution of alteration minerals in the three porphyry Cu deposits (Kharmagtai, Shuteen, and Tsagaan Suvarga) were selected from the ASTER SWIR reflectance images. In order to extract the endmembers, the dimensionality of the ASTER SWIR reflectance images was first determined; afterwards, the signal was separated from the noise using a minimum noise transform (MNF). The next step was to inspect the extreme pure pixels projected as points in n-dimensional scatter plots of the high-order MNF images (which had larger eigenvalue and reduced-noise). The pixels which were projected in extreme positions within the scatter plots were selected as endmembers and applied to the matched filter analysis (Green et al., 1988; Boardman, 1993).

16

4.3. Field spectroscopy To validate the mineral mapping results, field reflectance spectra was collected at the surface of more than fifty outcrops of the Budgat and Gashuun Khudag areas within the Ikh Shankhai porphyry Cu district (No. 12 and 14 in Fig. 5 and Appendix A). This district was chosen because it has been relatively less explored and studied compared to the other four porphyry Cu districts (Oyu Tolgoi, Tsagaan Suvarga, Shuteen and Kharmagtai). Reflectance spectra acquisition was conducted in regions which where ASTER-mapped as argillic and phyllic zones, using a portable ASD TerraSpec Halo mineral identifier which measure the VNIR and SWIR range (0.35 – 2.5 µm) and is equipped with GPS. The spectral analysis was carried out using spectral feature fitting (SFF) in ENVI to compare the fit of field spectra with the references provided from the USGS digital spectral library splib06a (Clark et al., 2007).

5. Results 5.1. Iron oxide/hydroxide content Figure 7b shows the regional scale iron oxide/hydroxide content map generated from the ETM+ 3/1 band ratio. High ratio values (>1.35) represented in red and yellow, correlate with the characteristic reflectance difference of iron oxide/hydroxide minerals in the 0.45 – 0.69 µm interval. Red and yellow regions in the map correspond to Quaternary covers, as well as to Cretaceous and Neogene rocks (Fig. 5, 7b). In particular, 17

the yellow occurred extensively in the Quaternary covers located at the terrane boundaries between the Gurvansayhan island arc and the Mandalovoo island arc and Cenozoic alluvial basin (Figs. 2a and 5; Qr and Qg in Fig. 7a and b).

On the other hand, the

western Quaternary deposits of the study area (Qb) showed low band ratio values, represented in green and blue, indicating a lower iron oxide content. The color of sedimentary rocks may provide an indication of the presence of iron bearing minerals. The Qr regions, (yellow in Fig. 7b), appear predominantly red, brown, and yellow in the true-color composite image (Fig. 7a). These regions are expected to be redbeds or red sandstones, rich in hematite and goethite. The Qg regions, represented in yellow in Fig. 7b, were predominantly beige, gray, and white in the true color image (Fig. 7a), implying the presence of iron rich-gray and white sandstones in the region. These observations are consistent with the published geologic map of gray sand and pebble from weathering rocks (Ooka et al., 1998). The Qb regions, corresponding to low band ratio values (green and blue colors in Fig. 7b) are dark gray and black in the true-color composite image (Fig. 7a), suggesting the existence of gray and black sandstones with low iron oxide content. In order to interrogate the relationship between 3/1 band ratio value and mineral deposits, we calculated the average 3/1 band ratio values from a total of 70 deposits and occurrences (Fig. 7b; Appendix A). Based on the idealized porphyry Cu deposit model, much of the ore occurs near the boundary between the potassic and phyllic zones (Lowell and Guilbert, 1970). In case of sulfide bearing ore zones exposed by weathering, iron minerals result from the oxidation of pyrite (Sabins, 1999). We calculated the average band ratio values of deposits and occurrences within a radius of 150m, assuming that the oxidation zone would not be far from the center of the deposit. The average band ratio

18

calculated from 58 deposits and occurrences related to Cu or Au was 1.33 (No. 1 – 58 in Fig. 7b; Appendix A); the average band ratio calculated from 32 deposits and occurrences located in the five major porphyry Cu districts (No. 1 – 32 in Fig. 9a – e; Appendix A) was 1.35. On the other hand, the average band ratio calculated from 12 REE occurrences, not associated with Cu or Au, was 1.27 (No. 59 – 70 in Fig. 7b; Appendix A).

5.2. Alteration anomaly mapping Phyllic- and argillic-altered rocks were mapped using ASTER logical operator algorithms from Mars and Rowan (2006) (Fig. 10). Most of spectral signature indicative of hydrothermal alteration minerals occur in Carboniferous to Permian volcanic and plutonic rocks, and in the faults zones (Figs. 5 and 10). Detrital clays (e.g., montmorillonite, illite, and kaolinite) in sedimentary rocks may be confused with hydrothermal alteration minerals (Mars and Rowan, 2006). The phyllic alteration units in the DC region (Fig. 10 and 11d) are expected to be detrital clays as this region is composed of Neogene to Permian sedimentary rocks (Fig. 5). However, mapped argillic +/- phyllic units in the five major porphyry Cu deposit districts (Figs. 10 and 11) are expected to be alteration minerals as this region is mainly composed of Carboniferous to Devonian volcanic and plutonic rocks (Fig. 5). The Kharmagtai district contains four high grade porphyry-hosted (monzodiorite) CuAu deposits (No. 1– 4 in Fig. 11a and Appendix A; Müller et al., 2010). The Kharmagtai complex covers approximately 5 – 6 km2 and at least 70% of the complex is concealed

19

by a shallow Quaternary cover (MA, 2015). Superimposing the image alteration anomalies and the geologic map (Figs. 5 and 10), it appears that a series of circular and linear phyllic alteration units (with no argillic alteration Fig. 11a) are distributed along faults in the Kharmagtai porphyry Cu district. The Shuteen porphyry Cu district consists of intermediate volcanic and plutonic rocks of the Middle Carboniferous Shuteen Complex which were emplaced over and into Lower Carboniferous sedimentary rocks, respectively (Fig. 11b; Batkhishig et al., 2010, 2014). The Shuteen Complex is characterized by a weakly developed porphyry-style Cu mineralization and has a ring structure of approximately 15 × 13 km (Batkhishig et al., 2014). This complex includes four Cu prospects: Shuteen Kahnbogd, Khar Tolgoi, Bayan Khoshuu and Dash Sum (No. 8–11 in Fig. 11b and Appendix A). The ASTER data analysis revealed the presence of a long and elliptic argillic alteration units on the western side of the Middle Carboniferous Shuteen Complex volcanic rocks: these units are associated with a 2-km wide and 8-km long, north-south trending Shuteen Kahnbogd lithocap (No. 8 in Fig. 11b). The linear phyllic alteration units are near the Khar Tolgoi and Bayan Khoshuu (No. 9 and 10 in Fig. 11b and Appendix A). On the other hand, argillic or phyllic alteration signature associated with Dash Sum is not detected. The Tsagaan Suvarga porphyry Cu-Mo district consists of a Late Devonian Tsagaan Suvarga intrusive complex and of Carboniferous sedimentary and volcanic rocks (Watanabe and Stein, 2000). This district has one deposit and eight occurrences (No. 18 – 26 in Fig. 11c and Appendix A). A semicircular phyllic alteration pattern was mapped in the vicinity of the Tsagaan Suvarga deposit (No. 18): this is the main ore body of the district in terms of both grade and tonnage (Watanabe and Stein, 2000). The phyllic

20

anomaly to the east of main ore body is also confirmed and weakly phyllic alteration anomalies are scattered within the Tsagaan Suvarga intrusive complex. The Ikh Shankhai porphyry Cu district is composed of Late Carboniferous volcanic and sedimentary rocks, intruded by Carboniferous-Permian granite, granodiorite, and granodiorite porphyry (Figs. 5 and 11d; Ooka et al., 1998). The argillic alteration units identified from the ASTER data exhibit semicircular to circular patterns, occur as cluster, and are associated with hydrothermally altered Carboniferous-Permian igneous intrusive rocks and subvolcanic bodies (Figs. 5 and 11d). Phyllic alteration units surrounds these argillic alteration units. These alteration patterns and distributions are in accord with the porphyry Cu system characteristics described in previous studies (Lowell and Guilbert, 1970; Pirajno, 1992; Mars and Rowan, 2006; Sillitoe, 2010). Some phyllic alteration units (e.g. DC) are due to the detrital clays (e.g., montmorillonite, illite) mentioned above. The Oyu Tolgoi porphyry Cu-Au district consists of Paleozoic volcanic and volcaniclastic rocks intruded by Devonian to Permian granitoid plutons. These rocks are unconformably overlain by poorly consolidated Cretaceous sediments (Wainright et al., 2011). The district comprises three deposit groups (Hugo Dummett, Oyu Tolgoi, Heruga), extending in a north-northeast trending zone (No. 27 – 32 in Fig. 11e and Appendix A). The groups and the deposits align almost perpendicularly to a Late Devonian arc axis (Khashgerel et al., 2008). The alteration units identified from the ASTER data analysis are distributed along faults and linear features. The observed semicircular argillic alteration pattern corresponds to a leached outcrop with supergene alunite in the Central Oyu Tolgoi deposit (No. 29 in Fig. 11e; Perello et al., 2001). A linear phyllic alteration pattern, showing some argillic alteration, corresponds to the South Oyu Tolgoi deposit (No. 30 in Fig. 11e). Some linear phyllic alteration patterns are also found on the west of

21

the Oyu Tolgoi deposits.

5.3. Mineral composition mapping Figure 12 shows an ASTER TIR index image, which QI >1.02, AI >1.015, and MI >0.98. A threshold on QI (>1.02), red color in Fig. 13b and d, is effective for detecting siliceous lithocaps with high quartz content. This threshold thus used to detect quartz. Quartz-rich units with high QI (red color) also occur in Quaternary covers and Cretaceous sedimentary rocks (Fig. 5; QC in Fig. 12). They are distributed widely on both sides of the strike-slip Zuunbayan fault which underwent deformation during the Mesozoic, prior to the Late Cretaceous. The units with high QI may be linked to metamorphosed sediments and metamorphic rocks rich in quartz (Ninomiya and Fu, 2016). The DC part is expected to be quartz in sediments which was formed through weathering and erosion. Based on the alteration anomaly and geologic mapping, this region is likely composed of detrital and clay-rich sedimentary rocks (Figs. 5, 10 and 12). The average AI value for the 12 rare earth element (REE) occurrences (No. 59–70) located within the Khan Bogd granitic complex (Fig. 12) is 1.028. A threshold on AI (>1.015), cyan color in Fig. 12, is effective for detecting the Khan Bogd peralkaline granitic complex. The Khan Bogd peralkaline granitic complex contains up to 35 modal percent K-feldspar (Kynicky et al., 2011). The threshold AI (>1.015) thus used to detect alkali rock rich in K-feldspar. The alkali-rich units with high AI (cyan color) are correspond to Permian, Carboniferous, and Devonian granitic rocks, respectively, in Fig. 5 (Pg, Cg, and Dg in Fig. 12). A threshold on MI (>0.98), blue color in Fig. 12, is effective for detecting mafic

22

intrusions, such as gabbro and gabbronorite (Pgb in Fig. 12, and indicated as Permian in Fig. 5). This threshold used to detect Fe and Mg-rich rock. Fe and Mg-rich units with high MI (blue color) are correspond to Carboniferous and Devonian volcanic and sedimentary rocks (Fig. 5; e.g., Ca, Cb, and Cs in Fig. 12). High MI units are also mapped in the sedimentary rocks in the porphyry Cu districts (Fig. 13).

5.4. Mineral mapping at district scale Within the Kharmagtai porphyry Cu-Au district, the ASTER SWIR pixel purity index (PPI) endmember spectra exhibited Al-OH ± Fe and Mg-OH spectral absorption features (A and B in Fig. 14). The PPI spectrum B is similar to the ASTER-resampled laboratory muscovite spectrum, having a strong absorption feature at 2.2 µm (Fig. 8a); the PPI spectrum A resembles the mixed spectrum of muscovite and chlorite, having absorption features at 2.2 and 2.33 µm (Rowan et al., 2003, 2006). A matched filter classification, based on the PPI spectrum B, showed that the presence of muscovite in volcaniclastic siltstones, to the west of three Cu-Au deposits (i.e., Altan Tolgoi, Tsagaan Sudal and Zenden Uul; Fig. 15a, b). Mixtures of muscovite and chlorite sporadically occur in southern volcaniclastic siltstones and sandstones (Fig. 15b). Previous studies (Müller et al., 2010; MA, 2015) confirmed the occurrence of alteration zones, consisting of chlorite, epidote, and muscovite, within the Kharmagtai Cu-Au deposits. Five PPI endmembers were identified from the ASTER SWIR image of the Shuteen porphyry Cu district (C – G in Fig. 14). The PPI spectrum C shows a Fe and Mg-OH absorption feature at 2.33 µm, which can be attributed to chlorite (Fig. 8a). The PPI

23

endmember spectrum D has 2.2 and 2.33 µm absorption features, similar to those of the PPI spectrum A; its shape resembles that of the muscovite and chlorite mixed spectrum (Rowan et al., 2003, 2006). The PPI spectrum E has a strong Al-OH absorption feature at 2.2 µm, which can be attributed to by muscovite (Fig. 8a). The spectral characteristics of the PPI spectra F and G are similar to those of kaolinite and alunite, respectively (Fig. 8 a). The alunite spectrum differs from the kaolinite spectrum in the maximum absorption wavelength (2.17 versus 2.20 µm, respectively). The results mapped with the matched filter, show that the distributions of alunite and kaolinite are generally consistent with the advanced argillic alteration zones indicated in the geologic map (Fig. 16a, b). Alunite is the spectrally dominant mineral in the main alteration zone which forms a siliceous lithocap (MAZ, Fig. 16b). The muscovite, the chlorite, and the muscovite + chlorite are restricted to the outlying part of the MAZ (Fig. 16b), in correspondence of the potassic and propylitic alteration zones of plutonic rocks, andesite, and diorite porphyry (Batkhishig et al., 2014). Two PPI endmembers were extracted from the ASTER SWIR image of the Tsagaan Suvarga porphyry Cu-Mo district (H and I in Fig. 14). The PPI and the ASTER-resampled laboratory spectra were compared confirming similarity between the PPI spectra H and I, and the laboratory spectra of chlorite and muscovite, respectively (Fig. 8a). The shape of the PPI spectrum H, which has a 2.33 µm strong absorption feature, is also similar to the PPI spectrum C in the Shuteen porphyry Cu district (Fig. 14). Additionally, the PPI spectrum I resembles the PPI spectra B and E, having a strong absorption feature at 2.2 µm. Muscovite was mapped with the matched filter, using the PPI spectrum I: and is distributed along the fault boundaries between intrusive and volcanic-sedimentary rocks,

24

as well as in the main ore body (Fig. 17a, b). Based on a previous study, the mapped muscovite units may be related to coarse muscovite rather than to phyllic alteration (Tungalag et al., 2018). ). Muscovite in volcanic-sedimentary sequences may be linked to detrital clays (e.g., illite and montmorillonite) in the sedimentary units. Chlorite appeared widely distributed in a NW direction, in the northern part of the Tsagaan Suvarga complex (Fig. 17b) and may be related to strongly deformed volcanicsedimentary rocks (Tungalag et al., 2018).

5.5. Field validation Field study of the Budgat and Gashuun Khudag areas within the Ikh Shankhai porphyry Cu district confirmed the occurrence of silicious lithocaps and presence of oxidized, argillic and phyllic zones which are clearly exposed on the surface (Fig. 18). This supports our mapping results from Landsat VNIR and ASTER SWIR-TIR datasets (No. 12 and 14 in Fig. 9d, 11d, and 13d). Our field spectra measurements clearly identified the presence of alunite, dickite, kaolinite and pyrophyllite rich argillic zone, illite rich phyllic zone (Fig. 19), and hematite and goethite rich oxidized zone (Fig. 20).

6. Discussion We mapped the surface minerals in SE Mongolia using multi-spectral image data sets (ETM+ and ASTER). Our results do not only agree with geological mapping and the alteration mineralogy identified in previous studies (Watanabe and stein, 2000; Perello et

25

al., 2001; Batkhishig et al., 2005, 2014; Khashgerel et al., 2006; Tungalag et al., 2018), but also provide new information about the iron oxide content, the presence of previously unknown alteration anomalies, and the occurrence of quartz and feldspar. We mapped a quartz area along the strike-slip Zuunbayan fault zone, consisting of metamorphosed volcanic and sedimentary rocks, which can be the result of Mesozoic deformations antecedent to the Late Cretaceous (Fig. 12; Lamb et al., 1999; Webb and Johnson, 2006). Figure 20 shows the field reflectance spectra containing iron minerals (goethite and/or hematite) measured in the Ikh Shankhai porphyry Cu district (Fig. 18). The average 3/1 band ratio value of these spectra, resampled to ETM+ spectral resolution, was 1.58, while the average 3/1 band ratio of the ETM+ pixel spectra at the same locations was 1.4. The difference in average 3/1 band ratio values between the field and the ETM+ image spectra may be due to atmospheric attenuation effects in the ETM+ image and/or to the spatial resolution of single pixels (30m). We believe that ETM+ 3/1 band ratio of 1.35 can be useful a threshold value for the detection of iron oxide minerals associated the porphyry Cu deposit in SE Mongolia. In order to evaluate the usefulness of the ASTER-mapped hydrothermal alterations as auxiliary data for mineral exploration, we compared the ASTER-mapped alterations with the known mineral deposits and occurrences, including Cu or Au ores (No. 1 – 58 in Fig. 10; Appendix A). Thirty-four of the 58 deposits and occurrences have phyllic or argillic alterations within a 0.5-km radius from each site. Moreover, ten of these 34 deposits have both phyllic and argillic alteration anomalies and all of them occur within the five major porphyry Cu districts. This is a result of structural deformation, erosion, and deposition and a multiplicity of intrusions, which can conceal large portions of the

26

alteration zones. Some alteration mineral assemblages observed from ASTER dataset in this study do not reflect classic alteration zoning models of porphyry Cu deposits which are often described (Lowell and Guilbert, 1970; Guilbert and Park, 1986; Hedenquist et al., 1998; Sillitoe, 2000, 2010; Seedorff et al., 2005). Our ASTER SWIR analysis results show the existence of two types of alteration mineral assemblages in the porphyry Cu deposits of SE Mongolia. The first type (Karmagtai and Tsagaan Suvarga deposits) includes phyllic and propylitic minerals (no argillic minerals) (Figs. 11a, c, 15b, and 17b). Non argillic alteration may be due to deep erosion or denudation level. The high ETM+ 3/1 band ratio (average 1.43) indicating rich iron oxides for the first type of deposits support this (Appendix A). The second type (Shuteen, Ikh Shankhai, and Oyu Tolgoi deposits) includes argillic, phyllic and propylitic minerals (Figs. 11b, d, e, and 16b). The ASTER TIR analysis allowed the identification of quartz in the second type of deposits (Fig. 13b, d and e). The coexistence of quartz and argillic minerals is consistent with the typical lithocap found in high-level porphyry Cu districts (Perello et al., 2001; Khashgerel et al., 2006; Batkhishig et al., 2014). The average QI of the regions with quartz and argillic alteration in the second type of deposits is 1.02 (Appendix A). This implies that the second type of deposits has a relatively shallow erosion or denudation level with respect to the first type of deposits. The average ETM+ 3/1 band ratio for the second type of deposits is 1.28 (Appendix A), which suggests that the iron oxide content in the second type of deposits is the lower than the first type of deposits. Quartz was not mapped in the first type of deposits (Kharmagtai and Tassan Suvarga; Fig 13a, c). The average QI for the first type of deposits is 1.0 (Appendix A), which is lower than the average QI (1.02) of the regions with quartz and argillic alteration. This is perhaps due to the abundance of feldspar in the rocks. Previous studies confirmed that the QI index has a very low value

27

when feldspar is abundant in granitic rocks (Aboelkhair et al., 2010; Guha and Kumar, 2016). The Kharmagtai and Tassan Suvarga igneous complexes consist of a series of intrusive bodies (e.g., quartz-monzodiorite and quartz-monzonite) rich in feldspars (Figs. 15a and 17a; MA, 2015; Tungalag et al., 2018). The selection of new exploration sites associated with porphyry Cu deposits using imaging spectroscopy should be performed with caution. The available geological information and the image analysis results regarding well-known porphyry Cu districts in from this and previous studies (Sabins, 1999; Ducart et al., 2006; Mars and Rowan, 2006; Rockwell and Hofstra, 2008; Sillitoe, 2010) show that potential porphyry Cu districts may be selected based on some criteria that follow. (1) The ASTER SWIR alteration anomaly must be present in the igneous rock. ASTER alteration anomaly mapped on the surface can be a valuable indicator of porphyry Cu prospect, but they are not always related to hydrothermal alteration associated with porphyry Cu deposits. They can be confused with minerals which form in sedimentary and metamorphic rocks. For example, the muscovite, chlorite, and epidote contained in metamorphic rocks, such as schist, can be confused with phyllic or propylitic minerals, and the weathered kaolinite in sedimentary rocks, such as shale and sandstone, can be confused with argillic minerals (Mars and Rowan, 2006). (2) At the district and regional scales, the presence of clusters and alignments of phyllic and/or argillic anomalies from ASTER SWIR data is a clue of porphyry Cu prospect. (3) ASTER phyllic and/or argillic anomalies showing semicircular – circular pattern near intersections (between transverse fault zones, or lineaments, and arc-parallel structures) are also favorable condition for porphyry Cu deposit. (4) ASTER TIR-mapped quartz with argillic alteration increases the potential for porphyry Cu deposit.

28

(5) The coexistence of high ETM+ 3/1 band ratio with ASTER TIR quartz and ASTER SWIR argillic alteration suggests the lithocap found in porphyry Cu deposit. Oxidized zones with high ETM+ 3/1 band ratio can be a useful indicator of underlying porphyry Cu deposit, but this may be a false anomaly associated with iron-rich volcanic rocks and sedimentary red beds. On the basis of above criteria, the study area contains four potential porphyry Cu districts (red circles in Fig. 10) which is may be associated with the processes of subduction erosion and terrane accretion in SE Mongolia where many porphyry Cu deposits associated with Devonian to Carboniferous subduction-related magmatism have been discovered.

7. Conclusions This study provides the surface lithological/mineralogical information of island arc terranes in SE Mongolia based on satellite data and existing geological maps of previous studies, some of which have been confirmed by field survey and sampling. The ETM+ VNIR data band ratio was utilized to map regional scale iron oxide/hydroxide content. The iron oxide/hydroxide minerals were extensively mapped in Quaternary covers located at the terrane boundary between the Gurvansayhan and Mandalovoo island arcs and basins. Oxidized zones with high ETM+ 3/1 band ratio can be a clue of underlying porphyry Cu deposit. ASTER SWIR logical operators and the matched filter analysis were applied to map the alteration minerals associated with porphyry Cu mineralization at the regional and district scales, respectively. The alteration zones derived from the ASTER analysis typically occurred as clusters along faults. In five major porphyry Cu districts, hydrothermal alterations occurred mainly in semicircular – circular and some 29

elongate patterns. The distribution of hydrothermal alteration anomalies in the Ikh Shankhai porphyry Cu district was in good agreement with that of the alteration zones identified by the field reflectance spectra collected at the surface of outcrops. In addition, we identified some alteration anomalies that might be associated with porphyry Cu deposits (e.g., Oyu Tolgoi and Shuteen; Fig. 10). The ASTER TIR mineral indices were used to create a map of quartz and k-feldspar, which typically do not exhibit specific spectral features in the VNIR and SWIR. In particular, the high QI index values obtained in correspondence of argillic alterations, might be associated with the silicic alteration of the lithocaps overlying porphyry Cu deposits. However, because of the low spectral and spatial resolutions of the ASTER TIR data, we could only identify lithocaps exposed over a large area.

Acknowledgments This study was supported by the Korea Institute of Geoscience and Mineral Resources (KIGAM) Basic Research Project “Development of mineral potential targeting and efficient mining technologies based on a 3D geological modeling platform (19-3211-1)” funded by the Ministry of Science and ICT of Korea. References Aboelkhair, H., Ninomiya, Y., Watanabe, Y., Sato, I., 2010. Processing and interpretation of ASTER TIR data for mapping of rare-metal-enriched albite granitoids in the Central Eastern Desert of Egypt. J. Afr. Earth Sci. 58, 141-151.

30

Adler-Golden, S.M., Matthew, M.W., Bernstein, L.S., Levine, R.Y., Berk, A., Richtsmeier, S.C., Acharya, P.K., Anderson, G.P., Felde, G., Gardner, J., Hike, M., Jeong, L.S., Pukall, B., Mello, J., Ratkowski, A., and Burke, H.-H., 1999. Atmospheric correction for short-wave spectral imagery based on MODTRAN4. Proc. SPIE 3753. Imaging Spectrometry, 61. Arancibia, O.N., Clark, A.H., 1996. Early magnetite-amphibole-plagioclase alterationmineralization in the Island Copper porphyry copper-gold-molybdenum deposit, British Columbia. Econ. Geol. 91, 402-438. Badarch, G., Cunningham, D., Windley, B.F., 2002. A new terrane subdivision for Mongolia: implications for the Phanerozoic crustal growth of Central Asia. J. Asian Earth Sci. 21, 87-110. Batkhishig, B., Bignall, G., Tsuchiya, N., 2005. Hydrothermal quartz vein formation, revealed by coupled SEM-CL imaging and fluid inclusion microthermometry: Shuteen complex, South Gobi, Mongolia. Resour. Geol. 55, 1-8. Batkhishig, B., Noriyoshi, T., Greg, B., 2010. Magmatism of the Shuteen Complex and Carboniferous subduction of the Gurvansaikhan terrane, South Mongolia. J. Asian Earth Sci. 37, 399-411. Batkhishig, B., Noriyoshi, T., Greg, B., 2014. Magmatic hydrothermal activity in the Shuteen area, South Mongolia. Econ. Geol. 109, 1929-1942. Bedini, E., 2011. Mineral mapping in the Kap Simpson complex, central East Greenland, Using HyMap and ASTER remote sensing data. Adv. in Space Res. 47, 60-73.

31

Biggar, S.F., Thome, K.T., MacCorkel, J.T., D’Amico, J.M., 2005. Vicarious calibration of the ASTER SWIR sensor including crosstalk correction. Proceedings of SPIE 5882. Earth observing Systems, 588217. Blight, J.H.S., Cunningham, D., Petterson, M.G., 2008. Crustal evolution of the Saykhandullan Inlier, Mongolia: Implication for Palezoic arc magmatism, polyphase deformation and terrane accretion in the Southeast Gobi Mineral Belt. J. Asian Earth Sci. 32, 142-164. Blight, J.H.S., Crowle, Q.C., Petterson, M.G., Cunningham, D., 2010. Granites of the Southern Mongolia Carboniferous Arc: New geochronological and geochemical constraints. Lithos 116, 35-52. Boardman, J.W., 1993. Automating spectral unmixing of AVIRIS data using convex geometry concepts. Summaries of the 14th Annual JPL Airborne Geoscience Workshop. JPL publication 93-26. Vol 1, 11-14. Buchan. C., Pfander. J., Kroner. A., Brewer. T.S., Tomurtogoo. O., Tomurhuu. D., Cunningham. D., Windley. B.F., 2002. Timing of accretion and collisional deformation in the Central Asian orogenic belt: implications of granite geochronology in the Bayankhongor ophiolite zone. Chem. Geol. 192, 23-45. Chivas, A.R., 1978. Porphyry copper mineralization at the Koloula igneous complex, Guadalcanal, Solomon Islands. Econ. Geol. 73, 645-677. Clark, R.N., 1999. Spectroscopy of rocks and minerals and principles of spectroscopy. In: Rencz, A.N. (Eds.), Remote Sensing for the Earth Sciences. John Wiley, New

32

York, pp. 3-58. Clark, R.N., Swaze, G.A., Wise, R., livo, E., Hoefen, T., Kokaly, R., Sutley, S.J., 2007. USGS spectral library splib06a. U.S. Geological Survey, Digital Data Series 231. Cox, D.P., Singer, D.A., 1986, Mineral deposit models. U.G. Geological Survey Bulletin 1693, pp. 145-167. Cudahy, T., Caccetta, M., Thomas, M., Hewson, R., Abrams, M., Kato, M., ... Collings, S., 2016. Satellite-derived mineral mapping and monitoring of weathering, deposition and erosion. Sci. Rep. 6, 23702. Dejidmaa, G., 2005. Mineral resources and metallogenic belts in southern Mongolia. In: Seltmann, R., Gerel, O., Kirwin, D. (Eds.), Geodynamics and metallogeny of Mongolia, with a special emphasis on copper and gold deposits. CERCAMS, London, p. 221. Dejidmaa, G., Buninlkham, B., Eviihuu, A., Emkhtuya, B., T, Ganbaatar, T., MoenkhErdene, N., Oyuntuya, N., 2001. Distribution map of deposits and occurrences in Mongolia, Geological Information Center, Geological Office, Mineral Resources Authority of Mongolia, scale 1:1,000,000. Di Tommaso, I.M., Rubinstein, N., 2007. Hydrothermal alteration mapping using ASTER data in the Infiernillo porphyry deposit, Argentina. Ore Geol. Rev. 32, 275-290. Ducart, D.F., Crosta, A.P., Filho, C.R.S., 2006. Alteration mineralogy at the Cerro La Mina epithermal prospect, Patagonia, Argentina: field mapping, short-wave infrared

33

spectroscopy, and ASTER Images. Econ. Geol. 101, 981-996. Gaffey, S.J., 1987. Spectral reflectance of carbonate minerals in the visible and near infrared (0.35–2.55 um): Anhydrous carbonate minerals. J. Geophys. Res. 92, 14291440. Goetz, A.F.H., Rowan, L., 1981. Geologic remote sensing. Science. 211, 781-791. Green, A.A., Berman, M., Switzer, P., Craig, M.D., 1988. A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Trans. Geosci. Remote Sensing 26, 65-74. Guha, A., Kumar, V., 2016. New ASTER derived thermal indices to delineate mineralogy of different granitoids of an Archaean Craton and analysis of their potentials with reference to Ninomiya's indices for delineating quartz and mafic minerals of granitoids-an analysis in Dharwar Craton, India. Ore Geol. Rev. 74, 76-87. Guilbert, J.M., Park, C.F., Jr., 1986. The geology of ore deposits. W.H. Freeman, New York. Hall, D.K., Riggs, G.A., Salomonso, V.V., 1995. Development of methods for mapping global snow cover using moderate resolution imaging spectroradiometer data, Remote Sens. Environ. 54, 127-140. Harris, A.C., Golding, S.D., White, N.C., 2005. Bajo de la Alumbrera copper-gold deposit: Stable isotope evidence for a porphyry-related hydrothermal system dominated by magmatic aqueous fluids. Econ. Geol. 100, 863-886.

34

Hedenquist, J.W., Arribas, A., Jr., Reynolds, T.J., 1998. Evolution of an intrusioncentered hydrothermal system; Far southeast-Lepanto porphyry and epithermal CuAu deposits, Philippines. Econ. Geol. 93, 373-404. Hewson, R.D., Cudahy, T.J., Mizuhiko, S., Ueda, K., Mauger, A.J., 2005. Seamless geological map generation using ASTER in the Broken Hill-Curnamona province of Australia. Remote Sens. Environ. 99, 159-172. Hook, S.J., Abbott, E.A., Grove, C., Kahle, A.B., Palluconi, F.P., 1999. Use of multicpectral thermal infrared data in geological studies. In: Rencz, A.N. (Eds.), Remote Sensing for the Earth Sciences. John Wiley, New York, pp. 59-110. Hubbard, B.E., Crowley, J.K., Zimbelman, D.R., 2003. Comparative alteration mineral mapping using visible to shortwave infrared (0.4–.4 m) Hyperion, ALI, and ASTER imagery. IEEE Trans. Geosci. Remote Sensing 41, 1401–1410. Hunt, G.R., 1977. Spectral signatures of particulate minerals in the visible and near infrared. Geophysics 42, 501-513. Iwasaki, A., Tonooka, H., 2005. Validation of a crosstalk correction algorithm for ASTER/SWIR. IEEE Trans. Geosci. Remote Sensing 43, 2747-2751. Khashgerel, B-E., Rye, R.O., Hedenquist, J.W., Kavalieris, I., 2006. Geology and reconnaissance stable isotope study of the Oyu Tolgoi porphyry Cu-Au system, south Gobi, Mongolia. Econ. Geol. 101, 503-522. Khashgerel, B-E., Kavalieris, I., Hayashi, K-i., 2008. Mineralogy, textures, and whole-

35

rock geochemistry of advanced argillic alteration: Hugo Dummett porphyry Cu-Au deposit, Oyu Tolgoi mineral district, Mongolia. Miner. Deposita. 43, 913-932. Khain, E.V., Bibikova, E.V., Kröner, A., Zhuravlev, C.Z., Sklyarov, E.V., Fedotova, A.A., Kravchenko-Berezhnoy, I.R., 2002. The most ancient ophiolite of the Central Asian fold belt: U-Pb and Pb-Pb zircon ages for the Dunzhugur complex, eastern Sayan, Siberia, and geodynamic implications. Earth Planet. Sci. Lett. 199, 311–325. Kynicky, J., Chakhmouradian, A.R., Xu, C., Krmicek, L., Galiova, M., 2011. Distribution and evolution of zirconium mineralization in peralkaline granites and associated pegmatites of the Khan Bogd complex, southern Mongolia. Can. Mineral. 49, 947965. Langford, R.L., 2015. Temporal merging of remote sensing data to enhance spectral regolith, lithological and alteration patterns for regional mineral exploration. Ore Geol. Rev. 68, 14-29. Lamb, M.A., Badarch, G., 1997. Paleozoic sedimentary basins and volcanic-arc system of southern Mongolia: new stratigraphic and sedimentological constructions. Int. Geol. Rev. 39, 542-576. Lamb, M.A., Cox, D., 1998. New 40Ar/ 39Ar age data and implications for porphyry copper deposits of Mongolia. Econ. Geol. Bull. Soc. Econ. Geol. 93, 524-529. Le Maitre, R.W., 2002. Igneous rocks: A classification and glossary of terms. Cambridge, Cambridge University Press, 240 p.

36

Liu, L., Zhou, J., Han, L., Xu, X.L., 2017. Mineral mapping and ore prospecting using Landsat TM and Hyperion data, Wushitala, Xinjiang, northwestern China. Ore Geol. Rev. 81, 280-295. Lowell, J.D., Guilbert, J.M., 1970. Lateral and vertical alteration-mineralization zoning in porphyry ore deposits. Econ. Geol. 65, 373-408. Mars, J.C., Rowan, L.C., 2006. Regional mapping of phyllic-and argillic-altered rocks in the Zagros magmatic arc, Iran, using Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data and logical operator algorithms. Geosphere 2, 161-186. Mars, J.C., Rowan, L.C., 2010. Spectral assessment of new ASTER SWIR surface reflectance data products for spectroscopic mapping of rocks and minerals. Remote Sens. Environ. 114, 2011-2025. Mars, J.C., Rowan, L.C., 2011. ASTER spectral analysis and lithologic mapping of the Khanneshin carbonatite volcano, Afghanistan. Geosphere 7, 276-289. Masterman, G.J., Cooke, D.R., Berry, R.F., Walshe, J.L., Lee, A.W., Clark, A.H., 2005. Fluid chemistry, structural setting, and emplacement history of the Rosario Cu-Mo porphyry and Cu-Ag-Au epithermal veins, Collahuasi district, northern Chile. Econ. Geol. 100, 835-862. McFeeters, S.K., 1996. The use of normalized difference water index (NDWI) in the delineation of open water features. Int. J. Remote Sens. 17, 1425-1432.

37

Mining Associates Pty Ltd (MA), 2015. Independent technical report Kharmagtai copper gold project Mongolia. Mitsuishi, M., Wallis, S.R., Aoya, M., Lee, J., Wang, Y., 2012. E-W extension at 19Ma in the Kung Co area, S. Tibet: Evidence for contemporaneous E–W and N–S extension in the Himalayan orogen. Earth Planet. Sci. Lett. 325, 10-20. Müller, A., Herrington, R., Armstrong, R., Seltmann, R., Kirwin, D.J., Stenina, N.G., Kronz, A., 2010. Trace elements and cathodoluminescence of quartz in stockwork veins of Mongolian porphyry-style deposits, Miner. Deposita 45, 707-727. Mustard, J.F., Sunshine, J.M., 1999. Spectral analysis for earth science: Investigation using remote sensing data. In: Rencz, A.N. (Eds.), Remote Sensing for the Earth Sciences. John Wiley, New York, pp. 251-306. Naghadehi, K.M., Hezarkhani, A., Asadzadeh, S., 2014, Mapping the alteration footprint and structural control of Taknar IOCG deposit in east of Iran, using ASTER satellite data. Int. J. Appl. Earth Obs. Geoinf. 33, 57-66. Ninomiya, Y., Fu, B., Cudahy, T.J., 2005. Detecting lithology with Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) multispectral thermal infrared radiance-at-sensor data. Remote Sens. Environ. 99, 127-139. Ninomiya, Y., Fu, B., 2016. Regional Lithological mapping using ASTER-TIR data: Case study for the Tibetan Plateau and the surrounding area. Geosciences 6, 39. Ooka, T., Metsugi, H., Kaku, M., Adachi, K., 1998. Extraction of clay mineral alteration

38

zone in eastern Mongolia using JERS-1 data. Bull. Geol. Surv. Jpn. 49, 275-290. Perello, J., Cox, D., Garamjav, D., Sanjdori, S., Diakov, S., Schissel, D., Munkhbat, T.O., Oyun, G., 2001. Oyu Tolgoi, Mongolia; Siluro-Devonian porphyry Cu-Au-(Mo) and high-sulfidation Cu mineralization with a Cretaceous chalcocite blanket. Econ. Geol. 96, 1407-1428. Pirajno, F., 1992. Hydrothermal mineral deposits: Principal and fundamental concepts for the exploration geologist. Springer-Verlag, Berlin. Pour, A.M., Hashim, M., van Genderen, J., 2013. Detection of hydrothermal alteration zones in a tropical region using satellite remote sensing data: Bau gold field, Sarawak, Malaysia. Ore Geol. Rev. 94, 181-196. Rajendran, S., Nasir, S., Kusky, T.M., Ghulam, A., Gabr, S., El-Ghali, A.K.M., 2013. Detection of hydrothermal mineralized zones associated with listwaenites in Central Oman using ASTER data. Ore Geol. Rev. 53, 470-488. Rippington, S., Cunningham, D., England, R., 2008. Structure and petrology of the Altan Uul Ophiolite: new evidence for a Late Carboniferous suture in the Gobi Altai, southern Mongolia. J. Geol. Soc. 165, 711-723. Rockwell, B.W., Hofstra, A.H., 2008. Identification of quartz and carbonate minerals across northern Nevada using ASTER thermal infrared emissivity data—implications for geologic mapping and mineral resource investigations in well-studied and frontier areas. Geosphere 4, 218-246.

39

Rouse, J.W., Haas, R.H., Schell, J.A., Deering. D.W., 1974. Monitoring vegetation systems in the Great Plains with ERTS. 3rd ERTS-1 Symposium, 309-313. Rowan, L., Goetz, A.F.H., Ashley, R.P., 1977. Discrimination of hydrothermally altered and unaltered rocks in visible and near infrared multispectral images. Geophysics. 42, 522-535. Rowan, L.C., Mars, J.C., 2003. Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data. Remote Sens. Environ. 84, 350-366. Rowan, L.C., Schmidt, R.G., Mars, J.C., 2006. Distribution of hydrothermally altered rocks in the Reko Diq, Pakistan mineralized area based on spectral analysis of ASTER data. Remote Sens. Environ. 104, 74-87. Sabins, F.F., 1999. Remote sensing for mineral exploration. Ore Geol. Rev. 14, 157-183. Salisbury, J.W., D'Aria, D.M., 1992. Emissivity of Terrestrial Materials in the 8-14 ㎛ Atmospheric Window. Remote Sens. Environ. 42, 83-106. Seedorff, E., Dilles, J.H., Proffett, J.M., Jr., Einaudi, M.T., Zurcher, L., Stavast, W.J.A., Johnson, D.A., and Barton, M.D., 2005. Porphyry deposits: Characteristics and origin of hypogene features. Econ. Geol. 100th Anniversary, 251-298. Sengor, A.M.C., Natal’in, B.A., Burtman, V.S., 1993. Evolution of the Altaid tectonic collage and Paleozoic crustal growth in Eurasia. Nature 364, 299-307. Sillitoe, R.H., 2000. Geold-rich porphyry deposits: Descriptive and genetic models and 40

their role in exploration and discovery, Rev. in Econ. Geol. 13, 315-345. Sillitoe, R.H., 2010. Porphyry copper systems, Econ. Geol. 105, 3-41. Sillitoe, R.H., Perelló, J., 2005. Andean copper province: Tectonomagmatic settings, deposit types, metallogeny, exploration, and discovery. Econ. Geol. 100th Anniversary, 845-890. Son, Y.S., Kang, M.K., Yoon, Y.J., 2014. Lithological and mineralogical survey of the Oyu Tolgoi region, Southeastern Gobi, Mongolia using ASTER reflectance and emissivity data. Int. J. Appl. Earth Obs. Geoinf. 26, 205-216. Son, Y.S., Kang, M.K., Yoon, Y.J., 2014b. Pyrophyllite mapping in the Nohwa deposit, Korea, using ASTER remote sensing data. Geosci. J. 18, 295-305. Sultan, M., Arvidson, R.E., Sturchio, N.C., Guinness, E.A., 1987. Lithologic mapping in arid regions with Landsat thematic mapper data: Meatiq Dome, Egypt. Geol. Soc. Am. Bull. 99, 748-762. Tungalag, N., Jargalan, S., Khashgerel, BE., 2018. Characteristics of the Late Devonian Tsagaan Suvarga Cu–Mo deposit, Southern Mongolia. Miner Deposita. Tosdal, R.M., Richards, J.P., 2001. Magmatic and structural controls on the development of porphyry Cu ± Mo ± Au deposits. Rev. in Econ. Geol. 14, 157-181. Tucker, C.J., Grant D.M., Dykstra J.D., 2004. NASA’s global orthorectified Landsat data set. Photogramm. Eng. Remote Sens. 70, 313-322.

41

Wainwright, A.J., Tosdal, R.M., Forster, C.N., Kirwin, D.J., Lewis, P.D., Wooden, J.L., 2011. Devonian and Carboniferous arcs of the Oyu Tolgoi porphyry Cu-Au district, south Gobi region, Mongolia. Geol. Soc. Am. Bull. 123, 306-328. Watanabe, Y., Stein, H.J., 2000. Re-Os ages for the Erdenet and Tsagaan Suvarga porphyry Cu-Mo deposits, Mongolia, and tectonic implications. Econ. Geol. 95, 1537-1542. Webb, L.E., Johnson, C.L., 2006. Tertiary strike-slip faulting in southeastern Mongolia and implications for Asian tectonics. Earth Planet. Sci. Lett. 241 p. 363-335. Windley, B.F., Alexeiev, D., Xiao, W., Kröner, A., Badarch, G., 2007. Tectonic models for accretion of the Central Asian Orogenic Belt. J. Geol. Soc. 164, 31-47. Xiao, W., Han, C., Yuan, C., Sumn, M., Lin, S., Chen, H., Li, Z., Li, J., Sun, S., 2008. Middle Cambrian to Permian subduction-related accretionary orogenesis of northern Xinjiang, NW China: Implications for tectonic evolution of central Asia. J. Asian Earth Sci. 32, 102-117. Xiao, W.J., Windley, B.F., Han, C.M., Yuan, C., Sun, M., Li, J.L., Sun, S., 2009. End Permian to mid-Triassic termination of the southern Central Asian orogenic belt. Int. J. Earth Sci. 98, 1189-1217. Yamaguchi, Y., Khale, A.B., Tsu, H., Kawakami, T., Pniel, M., 1998. Overview of Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER). IEEE Trans. Geosci. Remote Sensing 36, 1062-1071.

42

Yarmolyuk, V.V., Kovalenko, V.I., Salnikova, E.B., Kovach, V.P., Kozlovsky, A.M., Kotov, A.B., Lebedev, V.I., 2008. Geochronology of igneous rocks and formation of the late Paleozoic south Mongolian active margin of the Siberian continent. Stratigr. Geol. Correl. 16, 162-181.

43

Figures

Fig. 1. Tectonic map of the Central Asian Orogenic Belt (CAOB) (modified from Wainlight et al., 2011a). It shows the location of Mongolia and of the surrounding Precambrian cratons. The Main Mongolian Lineament (MML) is an approximate regional topographic structural boundary separating the northern and southern domains. The red dashed line is SE Mongolia defines the study area, which is shown enlarged in Fig. 2a.

Fig. 2. (a) Tectonostratigraphic terrane map of SE Mongolia showing the locations of the major porphyry Cu deposits and of the alkaline complex (modified from Badarch et al., 2002). The red dashed line defines the study area, whose geological map is shown in Fig. 5. (b) Schematic sections of SE Mongolia summarizing the tectonic growth process from the Late Ordovician to the Permian (A-A’ in Fig. 2a) (modified from Windley et al., 2007; Wainlight et al., 2011).

Fig. 3. Generalized geological section model of the porphyry Cu system, illustrating the spatial relationships between the porphyry Cu deposit in a multiphase porphyry stock, the immediate host rocks, and the alteration-mineralization zoning pattern (modified from Sillitoe, 2010).

44

Fig. 4. (a) Laboratory VNIR-SWIR reflectance spectra of representative alteration minerals associated with the vibrational processes of OH, Metal-OH, H2O and CO3 molecules from the USGS spectral library splib06a (Clark et al., 2007). (b) Laboratory TIR emissivity spectra of representative rock-forming silicate minerals caused by Si-OSi stretching (Salisbury and D'Aria, 1992).

Fig. 5. Geological map of the study area including locations of 70 mineral deposits and occurrences (modified from Badarch et al, 1999; Dejidmaa et al., 2001). Numbers 1 – 58 relate to Cu or Au and numbers 59 – 70 relate to REE. Major porphyry Cu deposit districts are outlined with red dashed boxes.

Fig. 6. Laboratory reflectance spectra of representative iron oxide and sulfate minerals associated with the crystal field transitions and field absorptions of Fe3+ cations, obtained from the “splib06a” USGS spectral library (Clark et al., 2007). The upper spectrum of each spectral pair was resampled to ETM+ bandpass wavelengths.

Fig. 7. (a) Orthorectified Landsat ETM+ mosaic true-color image of SE Mongolia. The blue line is an outline of the ASTER scenes and the red line is the study area, which includes major porphyry Cu deposits (yellow-red circles). The white dashed line is the terrane boundaries between the Gurvansayhan island arc and the Mandalovoo island arc and Cenozoic alluvial basin. Qr, Qg, and Qb indicate the locations of Quaternary deposits

45

discussed in section 5.1. (b) Regional scale iron oxide/hydroxide content map of the study area, which uses the color assignment generated from the ETM+ 3/1 band ratio. The white dashed lines indicate the location of the main porphyry Cu deposit districts (a) – (e). The white numbers are the same as the numbers of the 70 deposits and occurrences in Appendix A and show their locations.

Fig. 8. (a) Laboratory SWIR reflectance spectra of the representative alteration minerals shown in Fig. 4a, resampled to ASTER SWIR bandpasses. (b) Laboratory TIR emissivity spectra of the representative rock-forming silicate minerals shown in Fig. 5b resampled to ASTER TIR bandpasses.

Fig. 9. Subsets of Fig. 7(b) showing iron oxide/hydroxide content in the main porphyry Cu deposit districts (a)–(e): (a) Kharmagtai, (b) Shuteen, (c) Tsagaan Suvarga, (d) Ikh Shankhai, and (e) Oyu Tolgoi. The white numbers correspond to those of the 70 deposits and occurrences listed in Appendix A.

Fig. 10. Alteration anomaly map of the study area in SE Mongolia, using the ASTER SWIR data: the alteration anomaly units are overlaid on the ETM+ band 1 image. The white dashed lines indicate the location of the main porphyry Cu deposit districts (a) – (e): (a) Kharmagtai, (b) Shuteen, (c) Tsagaan Suvarga, (d) Ikh Shankhai, and (e) Oyu Tolgoi. The white numbers correspond to those of the 70 deposits and occurrences listed

46

in Appendix A. The blue dashed lines indicate the expected occurrence of detrital clays (DC).

Fig. 11. Subsets of Fig. 10 showing alteration anomaly in the main porphyry Cu deposit districts (a)–(e): (a) Kharmagtai, (b) Shuteen, (c) Tsagaan Suvarga, (d) Ikh Shankhai, and (e) Oyu Tolgoi. The white numbers correspond to those of the 70 deposits and occurrences listed in Appendix A.

Fig. 12. Mineral composition map of the study area using the ASTER TIR data: mineral composition units are overlaid on the ETM band 1 image. The white dashed lines indicate the location of the main porphyry Cu deposit districts (a) – (e): (a) Kharmagtai, (b) Shuteen, (c) Tsagaan Suvarga, (d) Ikh Shankhai, and (e) Oyu Tolgoi. The white numbers correspond to those of the 70 deposits and occurrences listed in Appendix A. Abbreviated names: Quaternary and Cretaceous sedimentary deposits (QC), Permian, Carboniferous, and Devonian granitic rocks (Pg, Cg, and Dg), Carboniferous andesite (Ca), basalt (Cb) and sandstone (Cs), Permian gabbro and gabbronorite (Pgb), detrital clays (DC).

Fig. 13. Subsets of Fig. 12 showing mineral composition in the main porphyry Cu deposit districts (a)–(e): (a) Kharmagtai, (b) Shuteen, (c) Tsagaan Suvarga, (d) Ikh Shankhai, and (e) Oyu Tolgoi. The white numbers correspond to those of the 70 deposits and occurrences listed in Appendix A.

47

Fig. 14. ASTER PPI endmember spectra used for the mineral mapping of the three porphyry Cu deposit districts (Kharmagtai, Shuteen, and Tsagaan Suvarga). The PPI spectra A and D have weak (2.20) µm and strong (2.33) µm absorption features, attributed to chlorite and muscovite. The PPI spectra B, E, and I have 2.20 µm absorption features, attributed to muscovite. The PPI spectra C and H have 2.33 µm absorption features, attributed to chlorite. The PPI spectrum F has a maximum absorption feature at 2.20 µm, attributed to alunite, while the PPI spectrum G has a maximum absorption feature at 2.17 µm, attributed to kaolinite.

Fig. 15. (a) Geologic map of the Khrmagtai porphyry Cu district. The red line is the outlines of deep-seated gravity anomalies, indicating the extent of a magma chamber (http://www.xanadumines.com/irm/content/geology-mineralisation.aspx?RID=454). The yellow circles indicate the main Cu-Au deposits. (b) Matched filter classification image, showing the distribution of two classes of hydrothermally altered minerals on top of the ETM+ band 1 image.

Fig. 16. (a) Geologic map of the Shuteen porphyry Cu district. The blue, white, and yellow lines indicate the distributions of surface geochemical anomalies (modified from Batkhishig et al., 2014), while the red line indicates the main alteration zone (MAZ). (b) Matched filter classification image showing the distribution of five classes of hydrothermally altered minerals on top of the ETM+ band 1 image.

48

Fig. 17. (a) Geologic map of the Tsagaan Suvarga district (modified from Watanabe and Stein, 2000; Tungalag et al., 2018). The black box indicates the main ore body (MOB) of the Tsagaan Suvarga complex (b) Matched filter classification image showing the distribution of two classes of minerals on top of the ETM+ band 1 image.

Fig. 18. Field photographs. (a) Area No. 12 in the Ikh Shankhai porphyry Cu district (Fig. 10d) showing intense bleaching. (b) Outcrop in area No. 12, containing iron oxide (hm: hematite), silicic (qtz: quartz), argillic (aln: alunite, dck: dickite, kln: kaolinite), and phyllic (il: illite) minerals. (c) Area No. 14 in the Ikh Shankhai porphyry Cu district (Fig. 10d) showing intense bleaching. (d) Outcrop in area No. 14 containing iron oxide (hm: hematite), silicic (qtz: quartz), argillic (aln: alunite, dck: dickite, kln: kaolinite), and phyllic (il: illite) minerals.

Fig. 19. Field reflectance spectra of the altered rocks in the Ikh Shankhai porphyry Cu district, measured using a portable ASD TerraSpec Halo mineral identifier. (a) Representative reflectance spectra of altered rocks in area No. 12 (Figs. 10d and 17a, b). (b) Representative reflectance spectra of altered rocks in area No. 14 in (Figs. 10d and 17c, d).

Fig. 20. Field reflectance spectra of the altered rocks, containing goethite and/or hematite, in the Ikh Shankhai porphyry Cu district (solid lines), and ETM+ pixel spectra at the same

49

locations (dotted lines). The vertical dashed lines indicate the positions of ETM bands 1 and 3.

Fig. 1

50

Fig. 2 51

Fig. 3

52

Fig. 4

53

Fig. 5

54

Fig. 6.

55

Fig. 7

56

Fig. 8

57

Fig. 9

58

Fig. 10 59

Fig. 11

60

Fig. 12 61

Fig. 13

62

Fig. 14

63

Fig. 15

64

Fig. 16

65

Fig. 17

66

Fig. 18

67

Fig. 19

68

Fig. 20

69

Table 1. Performance parameters for ASTER and Landsat ETM+. ETM+

ASTER Subsystem Band no. (spatial

Spectral

Band no.

Spectral range

range (µm)

(spatial

(µm)

resolution)

resolution)

VNIR

SWIR

1 (30 m)

0.45 – 0.52

1 (15 m)

0.52 – 0.60

2 (30 m)

0.52 – 0.60

2 (15 m)

0.63 – 0.69

3 (30 m)

0.63 – 0.69

3N (15 m)

0.78 – 0.86

4 (30 m)

0.78 – 0.86

3B (15 m)

0.78 – 0.86

Pan (15 m)

0.52 – 0.90

4 (30 m)

1.60 – 1.70

5 (30 m)

1.55 – 1.75

5 (30 m)

2.145 – 2.185

7 (30 m)

2.08 – 2.35

6 (30 m)

2.185 – 2.225

7 (30 m)

2.235 – 2.285

70

TIR

8 (30 m)

2.295 – 2.365

9 (30 m)

2.360 – 2.430

10 (90 m)

8.125 – 8.457

11 (90 m)

8.475 – 8.825

12 (90 m)

8.925 – 9.275

13 (90 m)

10.25 – 10.95

14 (90 m)

10.95 – 11.65

71

6 (60 m)

10.4 – 12.5

Table 2. Characteristics of principal alteration-mineralization types in porphyry Cu systems (from Sillitoe, 2010) and spectral feature range for identification of alteration minerals by remote sensing. Alteration Position in system type (abundance)

Key minerals

Spectral feature range for remote sensing detection

Possible ancillary minerals

Principal sulfide assemblages

Sodiccalcic

Deepest (uncommon)

Albite

8.6, 9.6, 9.9 µm (TIR)

Diopside, epidote, garnet

Typically absent

Magnetite

No spectral features

Potassic

Core zone of porphyry Cu deposits (ubiquitous)

Biotite

2.34 µm (weak) (SWIR),

K-feldspar

8.68, 9.46 µm (TIR)

Actinolite, epidote, sericite, andalusite, albite, carbonate, tourmaline, magnetite

Pyrite-chalcopyrite, chalcopyrite ± bornite, bornite ± digenite ± chalcocite

Marginal parts of systems, below lithocaps (ubiquitous)

Chlorite Epidote

2.25, 2.33 µm (SWIR) Actinolite, hematite, magnetite 2.26, 2.34 µm (SWIR)

Albite

8.6, 9.6, 9.9 µm (TIR)

Carbonate

2.32 or 2.34 µm (SWIR)

Propylitic

(dolomite, limestone) Chloritesericite

Upper parts of porphyry Cu core

Chlorite Sericite/illite

Pyrite

11.2 or 11.32 µm (TIR) 2.25, 2.33 µm (SWIR) Carbonate, epidote, smectite 2.2/2.22 µm (SWIR)

72

Pyrite-chalcopyrite,

Sericitic (phyllic)

zones (common)

Hematite

0.66, 0.87 µm (VNIR)

Upper parts of porphyry Cu deposits (ubiquitous)

Quartz

8.47, 8.9 µm (TIR)

Sericite

2.2,

Advanced Above porphyry Quartz argillic Cu deposits, Alunite constitutes lithocap (common) Pyrophyllite

µm (SWIR)

8.47, 8.9 µm (TIR)

Pyrophyllite, carbonate, tourmaline, specularite

Diaspore, andalusite, zunyite, corundum, 2.18, 2.33 µm (SWIR) dumortierite, topaz, 2.17, 2.32 µm (SWIR) specularite

Dickite

2.18, 2.21 µm (SWIR)

Kaolinite

2.17, 2.21 µm (SWIR)

73

Pyrite ± chalcopyrite

Pyrite-enargite, Pyritechalcocite, Pyritecovellite

Appendix A. Mineral deposits and occurrences of southeastern Mongolia. No.

Name

Dep. or Occur.

Location Latitute

Major mineral resource (minor)

Longtitute

Deposit type

Image

Argil

Kharmagtai porphyry Cu district 1

Altan Tolgoi

Dep.

44°02’52”

106°09’12”

Cu (Au, Ag)

Porphyry Cu

No

2

Tsagan Sudal

Dep.

44°02’27”

106°08’29”

Cu (Au, Ag)

Porphyry Cu

No

3

Zesen Uul

Dep.

44°02’30”

106°08’39”

Cu (Au, Ag)

Porphyry Cu

No

4

Chun

Dep.

44°01’20”

106°11’59”

Cu (Au, Ag)

Porphyry Cu

No

5

Burgit

Occur.

44°01’39”

105°59’19”

Cu (Au, Mo)

Porphyry Cu

No

6

Central OV

Occur.

44°02’11”

106°00’11”

Cu (Au)

Porphyry Cu

No

7

Hartsaga

Occur

44°03’17”

106°02’48”

Cu (Au)

Porphyry Cu

No

Shuteen porphyry Cu distict 8

Shuteen Khan Bogd

Occur

43°57’40”

107°38’20”

Alunite (Cu, Mo, Au, Ag)

Volcanogenicmetasomatic alunite

Yes

9

Khar Tolgoi

Occur.

43°58’51”

107°43’47”

Cu (Mo, Zn)

Porphyry Cu

No

10

Bayan Khoshuu

Occur.

43°54’20”

107°38’56”

Cu (Mo, Au, Zn, Pb)

Porphyry Cu

Yes

11

Dash Sum

Occur.

43°55’10”

107°45’09”

Cu (Pb, Zn)

Porphyry Cu

No

Ikh-Shankhai porphyry Cu district 12

Budagt

Occur.

43°37’20”

105°58’20”

Alunite (Cu)

Volcanogenicmetasomatic alunite

Yes

13

Ikh-Shankhai

Dep.

43°40’30”

105°56’00”

Pyrophyllite (Cu)

Volcanogenicmetasomatic pyrophyllite

Yes

14

Gashuun Khudag

Occur.

43°39’33”

106°05’17”

Fluorite (Cu)

Epithermal vein/replacement fluorite

Yes

15

Shivee Khudag

Occur.

43°40’20”

105°49’00”

Cu (Au. Mo, Ag)

Granitoid related AuAg-Cu

No

16

Nergui

Occur.

43°42’00”

105°54’00”

Au

Granitoid related AuAg-Cu

No

17

Nergui

Occur.

43°39’30”

106°06’15”

Au (Cu, Ag)

Granitoid related

Yes

74

Tsagaan Suvarga porphyry Cu-Mo district 18

Tsagaan Suvarga

Dep.

43°51’56”

108°20’47”

Cu-Mo

Porphyry Cu-Mo

Yes

19

Baruun

Occur.

43°51’56”

108°18’47”

Cu-Mo

Porphyry Cu-Mo

No

20

Unnamed

Occur.

43°53’45”

108°20’08”

Cu-Mo (Au, Ag) Porphyry Cu-Mo

No

21

Khoomor Khudag

Occur.

43°53’36”

108°24’26”

Cu-Mo

Porphyry Cu-Mo

No

22

Olgii Ovoo

Occur.

43°49’31”

108°19’56”

Cu-Mo

Porphyry Cu-Mo

No

23

Unnamed

Occur.

43°51’18”

108°19’43”

Cu-Mo

Porphyry Cu-Mo

No

24

Unnamed

Occur.

43°51’00”

108°21’29”

Cu-Mo

Porphyry Cu-Mo

No

25

Unnamed

Occur.

43°50’43”

108°18’34”

Cu-Mo

Porphyry Cu-Mo

No

26

Tsagaan Suvarga

Occur.

43°49’30”

108°18’52”

Fluorite (Cu)

Epithermal vein/replacement fluorite

No

Oyu Tolgoi porphyry Cu district 27

North Hugo Dummett

Dep.

43°02’37”

106°51’33”

Cu-Au

Porphyry

No

28

South Hugo Dummett

Dep.

43°01’52”

106°51’33”

Cu-Au

Porphyry

Yes

29

Central Oyu Tolgoi

Dep.

43°00’46”

106°51’17”

Cu-Au (Ag, Mo) Porphyry

Yes

30

South Oyu Tolgoi

Dep.

43°00’06”

106°51’30”

Cu-Au (Ag, Mo) Porphyry

Yes

31

Southwest Oyu Tolgoi

Dep.

43°00’26”

106°50’49”

Cu-Au (Ag, Mo) Porphyry

Yes

32

Heruga

Dep.

42°58’17”

106°48’41”

Cu-Au (Ag, Mo) Porphyry

Yes

Other deposits and occurrences related Cu or Au 33

Dochin Khural-2

Occur.

44°05’04”

106°22’00”

Cu

Porphyry

No

34

Dochin Khural-1

Occur.

44°03’57”

106°17’07”

Cu (Ag)

Porphyry

No

35

Gun Sain Khudag-1

Occur.

44°12’30”

107°56’30”

Cu (Mo)

Porphyry

No

75

36

Bunkhan Khudag

Occur.

44°12’00”

107°53’00”

Cu

Porphyry

No

37

Ulaan Tolgoi Bulag

Occur.

44°10’00”

107°56’00”

Cu (Mo)

Porphyry

No

38

Khongoot

Occur.

44°03’37”

107°50’05”

Cu (Mo, Au, Ag)

Porphyry

No

39

Mogoit Khudag

Occur.

44°35’00”

108°01’45”

Cu

Porphyry

No

40

Buyant Uul

Occur.

44°27’10”

108°17’50”

Cu (Mo)

Porphyry

No

41

Ulaan Tolgoi

Occur.

44°24’00”

108°06’00”

Cu (Mo)

Porphyry

Yes

42

Mandah

Occur.

44°23’30”

108°15’00”

Cu

Porphyry

No

43

Manhan Chuluu

Occur.

44°22’35”

108°27’35”

Cu

Porphyry

No

44

Khairhan

Occur.

44°19’00”

108°11’40”

Cu

Porphyry

No

45

Tsagaan Ovoo

Occur.

44°16’45”

108°11’40”

Cu

Porphyry

No

46

Nariin Khudag

Dep.

44°14’30”

108°02’30”

Cu (Mo)

Porphyry

No

47

Tsokhiotiin group

Occur.

43°40’00”

107°10’00”

Cu (Zn, Ag)

Porphyry

No

48

Alagbayan

Occur.

43°24’30”

107°43’00”

Cu

Porphyry

No

49

Zaeaagiin

Occur.

43°25’00”

106°30’00”

Cu (Pb, Zn)

Porphyry

No

50

Yamaat

Occur.

42°54’35”

106°34’49”

Cu-Mo (Au, Ag) Porphyry

No

51

Olgii Khiid

Occur.

43°36’00”

108°09’00”

Cu-Mo (Au, Ag) Porphyry

No

52

Nergui

Occur.

43°59’05”

105°30’55”

Au-Cu

Granitoid related

No

53

Gashuun Khudag

Occur.

43°09’30”

106°08’00”

Cu

Granitoid related

No

54

Atsat Huren Tolgoi

Occur.

42°43’28”

107°48’15”

Au (Cu, Ag, Pb, Zn, Sb)

Granitoid related

No

55

Occur. 34-30

Occur.

44°11’25”

106°41’05”

Au-Ag

Granitoid related

Yes

56

Zagoit

Occur.

44°06’00”

107°42’00”

Cu (Ag, AS, Sb)

Granitoid related

No

57

Tumen Khudag

Occur.

44°01’00”

108°10’00”

Au (Cu, Mn)

Granitoid related

No

76

58

Noyon Khudag

Occur.

44°14’22”

106°50’30”

Au

Placer

No

Khan Bogd alkali granite pluton 59

Hoit

Occur.

43°10’10”

107°10’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

60

Zamyn

Occur.

43°10’40”

107°07’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

61

Khiidiin

Occur.

43°08’50”

107°05’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

62

Khondiin

Occur.

43°07’50”

107°00’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

63

Argal

Occur.

43°05’00”

106°57’30”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

64

Lageriin

Occur.

43°00’40”

107°02’50”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

65

Brauun

Occur.

42°59’20”

107°00’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

66

Armstrong

Occur.

42°57’50”

107°02’10”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

67

Omnot

Occur.

42°57’00”

107°03’30”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

68

Tovin

Occur.

42°59’00”

107°08’40”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

69

Arfvedsonit

Occur.

42°57’00”

107°12’40”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

70

ZuunOmnood

Occur.

43°00’45”

107°16’00”

Ta, Nb, TR

Ta-Nb-(REE) pegmatite

No

Highlights Gurvansayhan and Mandalovoo island arc terranes in southeastern Mongolia, have high potential for porphyry Cu deposit. Regional mapping using the ASTER shortwave infrared (SWIR) logical operators showed semicircular – circular phyllic and/or argillic anomalies which usually clustered along faults or their intersections. The coexistence of high ETM+ 3/1 band ratio with ASTER TIR quartz and ASTER SWIR argillic alteration suggests the lithocap found in porphyry Cu deposit. We proposed four potential porphyry Cu districts by combining the multispectral remote sensing datasets and the mineralogical and structural properties in porphyry Cu system.

77