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Abstract and Figures

Enhanced digital outcrop models attributed with hyperspectral reflectance data, or hyperclouds, provide a flexible, three-dimensional medium for data-driven mapping of geological exposures, mine faces or cliffs. This approach allows the collection of spatially contiguous information on exposed mineralogy and so provides key information for understanding mineralising processes, interpreting 1-D drillhole data, and optimising mineral extraction. In this contribution we present an open-source python workflow, hylite, for creating hyperclouds by seamlessly fusing geometric information with data from a variety of hyperspectral imaging sensors and applying necessary atmospheric and illumination corrections. These rich datasets can be analysed using a variety of techniques, including minimum wavelength mapping and spectral indices to accurately map geological objects from a distance. Reference spectra from spectral libraries, ground or laboratory measurements can also be included to derive supervised classifications using machine learning techniques. We demonstrate the potential of the hypercloud approach by integrating hyperspectral data from laboratory, tripod and unmanned aerial vehicle acquisitions to automatically map relevant lithologies and alterations associated with volcanic hosted massive sulphide (VHMS) mineralisation in the Corta Atalaya open-pit, Spain. These analyses allow quantitative and objective mineral mapping at the outcrop and open-pit scale, facilitating quantitative research and smart-mining approaches. Our results highlight the seamless sensor integration made possible with hylite and the power of data-driven mapping approaches applied to hyperclouds. Significantly, we also show that random forests (RF) trained only on laboratory data from labelled hand-samples can be used to map outcrop scale data.
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5Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Str. 40, 09599 Freiberg, Germany
6TheiaX, HZDR Innovation, Bautzner Landstraße 400, 01328 Dresden, Germany
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1. Introduc tion
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2. Geological setting
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,I@]89 A=B9F5@=G5H=CB C77IFG 5G DMF=H=7 5B8 7IDF=:9FCIG GHC7?KC F?
7CBG=89F98 HC 69 :9989F NCB9G HC H<9 A5GG=J9 GI@]89G K=H<=B H<9 65G=7
HC :9@G=7 JC@75B=7G 5B8 5G 8=GA9A69F98 @9BG9G C: GHF5H56CIB8 A5GG=J9
GI@D<=89G K=H<=B H<9 IDD9FACGH :9@G=7 JC@75B=7G 5H  &5 FH=B"N5F8 9H
5@  @@ FC7?G C: H<9 +=C -=BHC 5F95 5F9 =BH9BG9@M 5@H9F98 8I9 HC
@CK ;F589 F9;=CB5@ A9H5ACFD<=GA 5B8 <M8FCH<9FA5@ 57 H=J=HM 5GGC7=
5H98 K=H< A=B9F5@=N5H=CB -<9 G<5@9 A5]7 JC@75B=7G 5B8 GHC7?KCF?
;9B9F5@@M 9L<=6=H 5 7<@CF=H=7 5@H9F5H=CB H<5H =B7F95G9G =B =BH9BG=HM HC
K5F8G H<9 A=B9F5@=N5H=CB =9N&CBH9G 9H 5@  K<9F95G H<9 :9@G=7
JC@75B=7 FC7?G G<CK 5 NCB98 5@H9F5H =CB K=H< D9FJ5G=J9 G9F=7=H=N5H=CB
7FCGG7IH 6M 5 @5H9F 7<@CF=H9F=7< 5@H9F5H=CB DFCL=A5@ HC A=B9F5@=N5H=CB
&5FH=B"N5F8 9H 5@  "B B95F GIF:579 5F 95G 5B8 58>5 79BH HC :5 I@HG
5 @C75@@M G=;B=:=75BH G=@=75 HC 7<@CF=H9F=7< 5@H9F5H=CB =G 5@GC DF9G9BH
-<9 9BH=F9 7CAD@9L =G 7FCGG7IH 6M 5 G9F=9G C: 0 GHF=?=B; /5F=G75B
H<FIGHG 5B8 @C75@@M C::G9H 6M 5 7CB>I;5H9 G9H C: @5H9 GHF=?9G@=D :5I@HG
K=H< '0, HF9B8=B; 89LHF5@ 5B8 ',0 HF9B8=B; G=B=GHF5@ ?=B9A5H=7G
88=H=CB5@@M 5B 9LH9BG=CB5@ 89H57<A9BH <5G 699B A5DD98 5H H<9 =BH9F
:579 69HK99B H<9 JC@75B=7 FC7?G 5B8 H<9 I@A C:H9B =B GD5H=5@ DFCL=A
=HM C: A5GG=J9 GI@]89 CF9 6C8=9G *I9G585 
3. Photogrammetric survey
D<CHC;F5AA9HF=7 GIFJ9M C: H<9  CD9BD=H K5 G 7CB8I7H98 HC
;9B9F5H9 5 <=;<F9GC@IH=CB 8=;=H5@ CIH7FCD AC89@ '=?CB  , %+
75A9F5 5B8 '=??CF  AA : @9BG K5 G IG98 HC 57 EI=F9  + 
D<CHC;F5D<G :FCA AI@H=D@9 J=9KDC=BHG 5FCIB8 5B8 K=H<=B H<9 D=H ;
=GC:H &9H5G<5D9 )FC:9GG=CB5@ J K5 G H<9B IG98 HC ;9B9F5H9 5 D<C
HC;F5AA9HF=7 F97CBGHFI7H=CB G99 DD9B8=L :C F 89H5=@G 5B8 H<9 F9
GI@H=B; DC=BH 7@CI8 ;9CF9:9F9B798 6M A95BG C: 7CF9;=GHF5H=CB HC A
F9GC@IH=CB 5=F6CFB9 %=+ 85H5 )'(%=+ :FCA H<9 ,D5B=G< ;CJ
9FBA9BH IG=B; H<9 =H9F5H=J9 7@CG9GH DC=BH A9H<C8 =AD@9A9BH98 =B
@CI8CAD5F9 =F5F895I&CBH5IH 
4. Hyperspectral data pr oces sing with hylite
!MD9FGD97HF5@ =A5;9FM K5G 75DHIF98 IG=B; 5 HF=DC8 ACIBH98
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5B8 ./6CFB9 +=?C@5 G9BGCF +=?C@5 %H8 (I@I =B@5B8 88=H=CB
5@@M H<9 GD97HF5@ 7<5F57 H9F=GH=7G C: <5B8 G5AD@9G 7C@@97H98 8IF=B; ]9@8
75AD5=;BG K9F9 A95GIF98 IB89F @56CF5HCFM 7CB8=H=CBG IG=B; H<9 G=
5'"1 ACIBH98 CB 5 8F=@@ 7CF9 G75BB9F "B H<9 :C@@CK=B; G97H=CB K9
CIH@=B9 H<9 DF9DFC79GG=B; KCF?^CKG =AD@9A9BH98 =B hylite =; 
5B8 H<9=F 5DD@=75H=CB HC H<9  85H5G9H CAD@9H9 89G7F=DH=CBG C: 957<
A9H<C8 5B8 H<9=F =AD@9A9BH5H=CB 75B 69 :CIB8 =B H<9 5DD9B8=79G 57
7CAD5BM=B; H<=G DI6@=75H=CB 5B8 H<9 hylite 8C7IA9BH5H=CB <HHDG
H=BMIF@7CA<M@=H98C7G -<9 hylite GCIF79 7C89 5B8 89H5 =@98 #IDMH9F
BCH96CC?G 7CJ9F=B; 957< DFC79GG=B; KCF?^CK 75 B 5@GC 69 8CKB@C5898
:FCA =H!I6 <HHDGH=BMIF@7CA<M@=H9
4.1. Laboratory acquisition
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5F9 =B7F95G=B;@M 69=B; IG98 HC 5B5@MG9 @=H<C@C;M 5B8 A=B9F5@C;M 5H H<9
AA7A G75@9 7CGH5 9H 5@  -I`5 9H 5@  !MD9FGD97HF5@ 57
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GCIF79H5F;9HG9BGCF 8=GH5B79G 5@@CKG :CF 89H5=@98 5B8 577IF5H9 GD97
HF5@ 7<5F57H9F=G5H=CB C: <5B8 G5AD@9G 5B8 8F=@@ 7CF9G K=H< F9@5H=J9@M @=A
=H98 DFC79GG=B; =; 5
=:HM G9J9B <5B8 G5AD@9G F9DF9G9BH=B; H<9 @=H<C@C;=9G 9L DCG98 5H 
K9F9 G75BB98 IG=B; 5 ,=,I+($ 8F=@@7CF9 G75BB9F 9EI=DD98 K=H< 5B
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hylite K5 G H<9B IG98 HC 7CBJ9FH 957< F5K 9B=L 85H5G9H HC F58=5B79 6M
GI6HF57H=B; 5 85F?F9:9F9B79 5B8 5DD@M=B; G9BGCF 75@=6F5H=CBG 5B8 HC
F9^97H5B79 IG=B; 5 K<=H9 75@=6F5H=CB D5B9@ DD9B8=L  9CA9HF=7
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Fig. 1. (J9FJ=9K A5 D C: H<9 "69F =5B )MF=H9 69@H 5 K= H< @C75H=CBG C: H<9 A5 =B A5 GG=J9 GI @]89 89 DCG=HG <CGH98 =B H<9 %5H9 9JCB=5B HC 5F@M 5F6CB=:9FCIG /C@
75B=7 ,98=A9BH5FM CAD@9L ;F99B  &5 D AC8=]98 :FCA &5 FH=B"N5F8 9H 5@  -<9 ;9C@C;M C: H<9 CFH5 H5@5M5 5B8 9FFC C@CF58C CD9B D=HG 5G
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4.2. Tripod acqu isition
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S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Fig. 2. (J9F J=9K C: H<9 hyli te KCF?^CK :CF 7CFF97H=B; 5B8 @C75@=G=B; @56CF5HCFM 5 HF=DC8 6 5B8 5=F6C FB9 9; ./ 65G98 <MD9FGD97 HF5@ 85H5 7 -<9G9 8=:
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F97H98 D=L9@ F9^97H5B79 9GH=A5H9G K9F9 89F=J98 6M 8=J=8=B; 957< D=L9@
6M =HG F97CBGHFI7H98 =@@IA=B5H=CB GD97HF5 :I@@ 89G7F=DH=CB C: H<=G BCJ9@
7CFF97H=CB A9H<C8 =G 69MC B8 H<9 G7CD9 C: H<=G GH I8M 6IH =G H<9 GI6>97H C:
5B ID7CA=B; DI6@=75H=CB (H<9F GH5H 9 C: H<9 5FH 5H ACGD<9F=7 5B8 HCDC
;F5D<=7 7CFF97H=CB A9H<C8G =AD@9A9BH98 =B hylite 5F9 89G7F=698 =B 89H5=@
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S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
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4.3. UAV acquisition
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4.4. Data fu sion
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7CADCB9BH C: 957< DC=BHG BCFA5@ J97HCF -<IG GD97HF5 CB <CF=NCBH5@
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5. Results: Data analysis and integration
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5.1. Qualitative analysis and visualisation
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5.2. Quantitative measurem ent and feature extraction
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G9H H<5H 75B 69 IG98 HC 8=F97H@M 7CAD5F9 GD97HF5@ 7<5F57H9F=GH=7G 69
HK99B <5 B8G5AD@9 5B8 CD9BD=H G75@9G K=H< H<9 DF=B7=D5@ 5=A C: HF5=B
=B; 5 GID9FJ=G98 7@5GG=]9F CB @569@@98 <5B8G5AD@9G 5B8 5DD@M=B; =H HC
A5D @=H<C@C;M =B H<9  <MD9F7@CI8
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Fig. 3. C@CIF 7CADCG=H9G C: H<9  <MD9F7@CI8 7F95H98 IG=B; <M@=H9 5B8 G<CK=B ; 5 HFI97C@CIF +   BA   BA   BA
J=GI5@=G5H=CB 5 :5@G97C@CIF J=GI5@=G5H=CB +    BA   BA   BA <= ;<@=;< H=B; J5F=5H=CBG =B 7@ 5M 7< @CF=H9 5B8 A=75
7CBH9BH 6  5B8 H<9 ]FGH H<F99 &' 65B8 G 7  J=GI 5@=G5H=CBG C: H<9G9 85H5 75B 69 :CIB 8 5H <HHDGH=BMIF @7CA75 <MD9 F7@CI8
K=89 J5F=9HM C: GD97HF5@ =B8=79G <5J9 699B 89J9@CD98 :CF 9LHF57H
=B; ;9C@C;=75@ =B:CFA5H=CB :FCA AI@H= 5B8 <MD9FGD97HF5@ 85H5 G
H<9G9 5F9 HMD=75@@M 5DD@=98 CB F9ACH9@M G9BG98 G5H9@@=H9 85H5 H<9M 5J C=8
GD97HF5@ 65B8G G9BG=H=J9 HC 5HACGD<9F=7 9::97HG 5B8 GC 75B 69 5D D@=98 CB
6CH< CIH8CCF 5B8 @56CF5HCFM 85 H5 F6=HF5F=@M 7CAD@9L GD97HF5@ =B8=79G
75B 69 75@7I@5H98 IG=B; hylite IG=B; =B6I=@H HCC@G :CF GD97HF5@ F9G5AD@=B;
5B8 7CA6=B5H=CB CF H<FCI;< 8=F97H A5B=DI@5H=CB C: H<9 IB89F@M=B;
85H5 5FF5M IG=B; numpy !5FF=G 9H 5@  09 9LHF57H  ;9C@C;=
75@@M G9BG=H=J9 GD97HF5@ =B8=79G -56@9 :FCA H<9 7CF9G75BB9F =A5;9FM
5B8 <MD9F7@CI8 85H5 -<9G9 =B8=79G K9F9 89J9@CD98 6M I85<M 9H 5@
 HC A5D H<9 ;9C@C;M C: H<9 &H "G5 F9;=CB IG=B; ,-+ 5B8 5=F
6CFB9 <MD9FGD97HF5@ 85H5 5B8 5F9 G9BG=H=J9 HC A=75 7@5M 75F6CB5H 9
5B8 =FCB CL=89 A=B9F5@G -<9 F9GI@HG =; DD9B8=L  5F9 8=F97H@M
7CAD5F56@9 69HK99B H<9 @56CF5HCFM 5B8 CIH8CCF 85H5G9HG 5B8 <=;<
@=;<H G=A=@5F=H=9G 5B8 8=::9F9B79G 69HK99B H<9 J5 F=CIG GD97HF5@
@=H<C@C;=9G 89]B98 =B ,97H=CB 
&=B=AIAK5 J9@9B;H< &0% A5DG 5F9 5@GC 7CAACB@M 5DD@=98 HC
A5D H<9 8=GHF=6IH=CB C: GD97=]7 A=B9F5@G IG=B; <MD9FGD97HF5@ 85H5
!97?9F 9H 5@  CF 9L5AD@9 H<9 DCG=H=CB C: GD97=]7 56GCFDH=CB
:95HIF9G =B H<9 G<CFHK5J9 =B:F5F98 F9;=CB 5F9 J9FM G9BG=H=J9 HC H<9
@9B;H< C: @(! 9(! 5B8 &;(! 6CB8G =B G=@=75H9 A=B9F5@G 5@@CK=B;
577IF5H9 8=G7F=A=B5H=CB 69HK 99B 5 J5F=9HM C: 7@5M A=75 7<@CF=H9 75F
6CB5H9 5B8 5AD<=6C@9 A=B9F5@G !97?9F 9H 5@  J5 B 89F &99F 9H
5@  J5B +I=H9B699? 9H 5@  &=B=AIA K5J9@9B;H< A5DG
K9F9 75@7I@5 H98 :CF H<9  85 H5G9HG =; DD9B8=L  6M ]HH=B; H<F99
;5IGG=5B :IB7H=CBG HC 5 <I@@ 7CFF97H98 GD97HF5 :FCA  HC  BA
G G<CKB 6M =;G 5B8 5B8 DD9B8=L  H<9 GD97HF5@ =B8=79G 5B8
&0% A5DG :CF H<9 @56CF5HC FM 5B8 CIH8CCF 85H5G9HG 5F9 EI5BH=H5 H=J9@M
7CAD5F56@9 !9B79 K9 DFCDCG9 H<5H H<9M F9DF9G9BH 5 G9H C: ;9C@C;=
75@@M F9@9J5BH :95HIF9G H<5H 5F9 5H @95GH =B H<=G 75 G9 GHI8M =BJ5F=5BH HC
G75@9 5B8 57 EI=G=H=CB A9H<C8
5.3. Automa ted ge ological mapping
-<9 =B8=79G 5B8 A=B=AIA K5J9@9B;H< A5DG 89G7F=698 =B ,97H=CB 
DFCJ=89 5 A9H<C8 :C F 8=F97H@M 7CAD5 F=B; GD97HF5 57EI=F98 IB89F ]9@8
5B8 @56CF5HCFM 7CB8=H=CBG -<=G CD9BG H<9 DCGG=6=@=HM C: HF5=B=B; 5 GI
D9FJ=G98 7@5GG=]9F IG=B; H<9 @=6F5FM C: 7@5GG=]98 <5B8 G5AD@9G =;
5B8 H<9B 5D D@M=B; =H HC 5IHCA5H=75@@M A5D H<9 ;9C@C;M C: H<9  CD9B
D=H "B H<9 :C @@CK=B; G97H=CB K9 9LD@CF9 H<=G CDH=CB 89J9@CD=B; 5 <5B8
H5=@CF98 897=G=CB HF99 H<5H 75B 8=GH=B;I=G< 69HK99B H<9 A5=B 5@H9F5H=CB
A=B9F5@G 5H  5B8 HF5=B=B; 5 F5B8CA :CF9GH 5@;CF=H<A H<5H 75B D9F
:CFA @=H<C@C;=75@ A5DD=B;
5.3.1. Alteration ma pping using a decision tree
,=A=@5F HC DF9J=CIG GHI8=9G =BJ9GH=;5H=B; A=B9F5@ 5@H9F5H =CB 9;
I85<M 9H 5@  @5F? 9H 5@  K9 A5DD98 H<9 8=GHF=6IH=CB C:
G9F=7=H9 5B8 7<@CF=H9 =;  K<=7< 5F9 C: H9B 5GGC7=5H 98 K=H< <M
8FCH<9FA5@ 5@H9F5H=CB =B /!&, 89DCG=HG IG=B; 5 897=G=CB HF99 65 G98 CB
8=GH=B7H=J9 GD97HF5@ 7<5F57H9F=GH=7G C: 957< A=B9F5@ -<9 DF9G9B7956
G9B79 C: 8=5;BCGH=7 GD97HF5@ 56 GCFDH=CBG 5H   5B8  BA
7: )CBHI5@ 9H 5@  K5G A5DD98 IG=B; 5 89DH< 7IHC:: C:  5B 8
H<9 897=G=CB HF99 IG98 HC G9D5F5H9 ?5 C@=B=H=7 7@5M :95HIF9 5H  BA
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Fig. 4. ,D97HF5@ @=6F 5FM DF9G9BH=B ; <I@@ 7CFF97H98 A9 8=5BGD 97HF5 ;F9 9B 5B8 5GGC7=5H98 =BH9FEI5 FH=@9 5F95 ;F9M 75@7I @5H98 CB 5@@ D=L9@G C: H<9 <5B8 G5A
D@9G 7 : =;G  F9D F9G9 BH=B; 957< C: H<9 GD97 HF5@ @=H<C@C;=9G =B H9FDF 9H98 5H  (L=8=G98 (L A5 GG=J9 GI@D< =89 &, HKC J5F=9H=9G C: 7<@CF=H9 <@
5B8  HKC G9F=7= H=7 IB =HG ,9F 5B 8  G<5@9 5B 8 DI FD@ 9 G<5@9 ), -<9 5D DFCL=A5H9 DCG=H=CB C: 7<5F57 H9F=GH=7 56 GCFDH=CB :95HIF9G )CBHI5@ 9H 5@  
5F9 5@GC D@CHH98 :CF F9:9F9B79 ,99 -56@9 :CF 89H5=@98 GD97HF5@ 89 G7F=DH=CBG
Table 1
,D97 HF5@ 89 G7 F=DH=CBG C: H<9 7< 5F57 H9F=GH=7 :95HIF9G 7: )CBHI5@ 9H 5@   %5I?5A D 9H 5@   C: 957< GD97 HF5@ @= H<C@C;M IG98 8I F=B ; GID9 FJ=G9 8 7@ 5GG=]75 H=CB
,97H=CB   ,D97 HF5 :CF 957< C: H<9G9 @=H<C@C;=9G 5F9 D@CHH98 =B =;
@(! :95H IF 9 9(!
:95HIF 9
&;(!
:95HIF 9
9]B= B; 7<5F 57 H9F= GH=7 G ,D97HF 5@ @=H< C@C; M
  BA 99D =F CB 56 GCFD H=CB :95H IF9G 5B 8 GA 5@@ 8CI6 @9@(! :95H IF9 8I9 HC 5GGC7= 5H98 ?5 C@=B =H9 (L =8=G98 ( L
@5H GD 97HF5 K=H< 6FC58 K5H9F :95H IF9 5H  BA &5 GG =J9 GI @D <=89
&,
OBA OBA C I6@9 56 GCFDH= CB 5H   5B 8  BA HMD=75@ C: 7<@CF= H9 @=A= H98 @(! 56 GCFDH=CB 5H   BA 5B 8 @CK
=BH9BG =HM 6F C5 8 K5 H9F :95H IF9 69HK99B  5B 8  BA
<@C F= H9 <@ 
OBA OBA G K=H< < @ 6IH K= H< 899D9F K5 H9F :95HIF 9G 5F CIB8  BA @=?9@M 8I9 HC H< 9 DF9G 9B79 C: A= BCF G9F=7= H9
%CK9F =BH9BG=H M C: 9(! 5B8 &;(! :95H IF9G
<@C F=H9 <@ 
O BA OBA OBA = GH=B 7H @ (! :95HIF9 :F CA G9F= 7=H9 5H Z  BA 5B 8 9(! :95H IF 9 :FCA 7<@C F= H9 5H Z  BA ,9F= 7=H9 5B 8
<@C F= H9
,9F < @
 BA O BA =GH=B 7H @(! :95H IF 9 K= H< A= B= A5 5H  BA AIG 7CJ= H=7 7CAD CG =H=C B != ;< 7F MG H5 @@ =B=HM =B8= 75H98 6M
8=_9F9B79 =B 89DH< C: @(! 5B 8 K5H9F :95H IF 9 7FMGH5@@= B= HM 
,9F= 7=H9 ,9F 
 BA O BA &IG7CJ =H 9HF 5B G=H= CB=B ; HC K5F8 G D< 9B;= H9 @( ! :95H IF9 @C 75H98 5H Z   9DH< C: K5H9F :95HIF 9 F9@5 H=J9 HC
@(! :95HIF 9 GI ;; 9GHG =B7F 95G9 8 K5 H9F 7C BH9BH 7FM GH 5@ @=B= HM  
,9F= 7=H9 , 9F 
@5H GD 97HF5 6IH 8=GH =B7H :F CA &, 8I9 HC GA 5@ @9F B5FF CK 9F K5 H9F :95HIF 9 69HK99B   5B 8  BA BA @CK
@(! 5B8 9(! 56GCFD H=CB :95HIF9 5B8 GH99D9F G@ CD 9 69HK99B  5B 8  BA
,<5@ 9
G 56 CJ9 6IH K=H< @CK9F G@ CD9 69HK99B  5B 8  BA 5B8 G@=; <H@M 899D9F @(! :95HIF 9 )IFD@9 G<5@9 ),
K<=H9 A=75 :95HIF9 5H  BA 6IH BCH  BA 7<@CF=H9 :95HIF9 5H
 BA 6IH BCH  BA 5B8 7<@CF=H9K<=H9 A=75 A=LHIF9G :95HIF9
5H  5B8  BA 88=H=CB5@@M A=75 5B8 7<@CF=H9 7CADCG=H=CB
K5G GD@=H 65G98 CB H<9 DCG=H=CB C: H<9  BA 5B8  BA 56GCFD
H=CBG F9GD97H=J9@M 5@@CK=B; 8=G7F=A=B5H=CB C: 7CADCG=H=CB5@ 9B8A9A
69FG "AD@9A9BH5H=CB 89H5=@G C: H<=G 897=G=CB HF99 5F9 =B7@I898=B DD9B
8=L 
5.3.2. Litholog y mapping using rand om fo rests
-<9 ;9C@C; M C: H<9  D=H K5 G 5@GC =BJ9GH=;5H98 IG=B; 5 F5 B8CA :CF
9GH 7@5GG=]9F =AD@9A9BH98 IG=B; ,7=?=H@95FB )98F9;CG5 9H 5@ 
!MD9FGD97HF5@ =A5;9G C: @569@@98 <5B8 G5AD@9G ,97H=CB  K9F9 IG98
5G HF5=B=B; 85H5 5B8 H<9 F9GI@H=B; AC89@ 5DD@=98 HC A5D @=H<C@C;=9G =B
H<9 <MD9F7@CI8 C: H<9  D=H 7: DD9B8=L  G 89G7F=698 =B ,97H=CB
 H<9 IG9 C: FC6IGH 5B8 ;9C@C;=75@ A95B=B;:I@ :95HIF9G GI7< 5G GD97
HF5@ =B8=79G 5B8 A=B=AIA K5J9@9B;H< A5DG =G ?9M HC H<=G 5DDFC57< 5G
=H 5@@CK98 EI5BH=H5H=J9 7CAD5F=GCB 69HK99B <5B8G5AD@9 G75@9 GD97HF5
57EI=F98 =B 5 @56CF5HCFM 5B8 CIH7FCD G75@9 GD97HF5 57 EI=F98 CIH8CCFG
-<9 F5B8CA :CF9GH A9H<C8 =G 5B 9BG9A6@9 @95FB=B; 7@5GG=]9F 5 @5F;9
G9H C: 897=G=CB HF99 7@5GG=]9FG 5F9 HF5=B98 GI7< H<5H H<9=F =B8=J=8I5@ F9
GI@HG 7CA6=B9 HC ;=J9 5 7CBG9BGIG 7@5GG=]75H=CB 57< HF99 7CBHF=6IH9G 5
IB=H JCH9 5B8 H<9 ]B5@ 7@5GG=]75H=CB @569@ =G 5@@C75H98 65 G98 CB H<9
7@5GG K=H< H<9 ACGH JCH9G -<9G9 9BG9A6@9G C: HF99 7@5GG=]9FG 5F9 9L
D97H98 HC D9F:CFA ACF9 FC6IGH@M 5B8 577IF5H9@M H<5B 5B =B8=J=8I5@ 89
7=G=CB HF99 7@5GG=]9F F9=A5B 
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Table 2
,D97 HF5@ =B8=79G IG98 HC 7<5F57H9F=G9 5B8 7CAD5 F9 G5A D@9 5B8 CIH7FCD
A=B 9F5@C;M -<9 7C@CB =B 8=75H9G H<5H 5B 5J9F 5;9 F9^97 H5B7 9 K5G 75 @7I
@5H98 :CF 5@@ 65 B8 G K=H<=B H<9 GD 97=]98 F5B; 9 @ @ K5J9@9 B;H<G 5F 9 =B
B5BCA9H9FG
"B89L 9]B=H=CB
@(! FCID 7C BH9BH       
@(! FCID
7CAD CG =H=C B
   
&;(! FCI D 7CBH 9BH   
  
&;(! FCI D
7CAD CG =H=C B
   
9(! F CID 7C BH9BH     
9FF CIG "F CB "B89L     
9FF =7 (L =89 7CBH9BH  
9FF =7 (L =8 9
7CAD CG =H=C B
   
$5 C@=B FCID =B 89L    
(D5EI9 =B 89L     
+9;C @=H< "B89L     
+9;C @=H< "B89L    
G K=H< A5BM A57<=B9 @95FB=B; A9H<C8G F9GI@HG C6H5=B98 IG=B;
F5B8CA :CF9GHG 75B 69 G9BG=H=J9 HC <MD9FD5F5A9H9FG H<5H 7CBHFC@ :CF 9L
5AD@9 HF99 GHFI7HIF9 5B8 89DH< G =G GH5B85F8 DF57H=79 F9=A5B
 K9 D9F:CFA98 5 ]J9:C@8 7FCGG J5@=85H=CB HC CDH=A=G9 H<9G9 <M
D9FD5F5A9H9FG HCH5@ C:  7CA6=B5H=CBG C: <MD9FD5F5A9H9FG K9F9
H9GH98 IG=B; 5 :CF9GH C:  HF99G -<9 F5B;9 C: <MD9FD5F5A9H9F J5@I9G
H<5H K9F9 H9GH98 5B8 H<9=F CDH=AIA J5@I9 =G GIAA5F=G98 =B -56@9
IF=B; H<9 HF5=B=B; D<5G9 H<9 7@5GG=]9F 57<=9J98 577IF57=9G C: Z
CB 6CH< HF5=B=B; 5B8 H9GH=B; GI6G9HG C: H<9 <5B8G5AD@9 =A5;9 'CH9
H<5H H<9G9 577IF57=9G 5F9 BCH F9DF9G9BH5H=J9 C: H<9 5@;CF=H<AG 5DD@=75
H=CB HC H<9 <MD9F7@CI8 85H5 5G :CF H<=G 85H5G9H H<9 ;FCIB8 HFIH< =G BCH
?BCKB
-<9 F9GI@HG C: H<9 F5B8CA :CF9GH 7@5GG=]75H=CB 5F9 GIAA5F=G98 5G 
J=GI5@=G5H=CBG C: H<9 7@5GG=]98 <MD9F7@CI8 =B =; -<9 8=GHF=6IH=CB
C: @=H<C@C;=9G G<CK 9L79@@9BH GD5H=5@ 7CBG=GH9B7M 9J9B H<CI;< BC GD5
H=5@ ]@H9F=B; <5G 699B 5DD@=98 5B8 CIH@=B9 ;9C@C;=75@@M F95GCB56@9
;9CA9HF=9G H<5H ;9B9F5@@M A5H7< K=H< DF9J=CIG A5DD=B; =;  98
8=B; A95GIF9A9BHG 9LHF57H98 IG=B; H<9 CAD5GG D@I;=B =B @CI8CA
D5F9 -<=9@9 9H 5@  5@CB; 7CBH5 7HG C: H<9 7@95F@M :C@898 G<5@9 IB=H
CIH7FCDD=B; =B H< 9 BCFH<95GH C: H<9 D=H H<9 CFH5 H5@5M5 7CB;@CA9F
5H9 89]B9 5 :C@8 5L=G D@IB;=B; X HCK5F8G X 5B8 5L=5@ GIF:579 8=D
D=B; 5H X HCK5 F8G X -<9G9 A95GIF9A9BHG 5F9 6FC58@M 7CBG=GH9BH
K=H< H<9 ;9B9F5@ GHFI7HIF9 C: H<9 F9;=CB5@ ;9C@C;M S9N&CBH9G 5B8
5F7S5F9GDC  5B8 5@@CK98 IG HC 89J9@CD 5B ID85H98 =BH9FDF9
H5H=CB C: H<9 GHFI7HIF9 C:  =; 
6. Discussion
CAD@9L ;9CA9HF=9G 5B8 =@@IA=B5H=CB 9::97HG A5?9 F9ACH9 G9BG=B;
C: 7@=::G 5B8 CD9BD=H A=B9G K=H< <MD9FGD97HF5@ =A5;=B; 5 G=;B=:=75BH
7<5@@9B;9 #5?C6 9H 5@  %CF9BN 9H 5@  -<9 KCF?^CK DF9
G9BH98 =B H<=G 7CBHF=6IH=CB 5B8 =AD@9A9BH98 =B H<9 CD9BGCIF79 hylite
DMH<CB D5 7?5;9 <9@DG 5A9@=CF5H9 H< 9G9 =GGI9G 6M DFCJ=8=B; A9H<C8G :C F
657? DFC>97H=B; 7CFF97H=B; 5B8 :IG=B; <MD9FGD97HF5@ 5B8 ;9CA9HF=7
85H5 :FCA 5 J5 F=9HM C: G9BGCFG -<9 F9GI@H=B; F9^97H5B79 GD97HF5 5F9
GHCF98 =B 5 ^9L=6@9 <MD9F7@CI8 :CFA5H GI7< H<5H 85H5 :FCA <IB8F98G C:
=B8=J=8I5@ <MD9FGD97HF5@ =A5; 9G 75B 69 =BH9;F5H 98 =BHC 5 G=B;@9 DFC8I7H
:CF J=GI5@=G5H=CB =BH9FDF9H5 H=CB 5B8 5B5@M G=G -<9  B5 HIF9 C: H< =G 5D
DFC57< A=H=;5H9G C77@IG=CB 5B8 8=GHCFH=CB =GGI9G H<5H @=A=H 5DDFC57<9G
F9@M=B; CB CFH<C;F5D<=7 DFC>97H=CB 5B8 :57=@=H5H9G 7FI7=5@ 7CFF97H=CBG
C: =@@IA=B5H=CB 5B8 5HACGD<9F=7 9::97HG =B H<9 <MD9FGD97HF5@ 85H5
-<9  75G9 GHI8M =@@IGHF5H9G H<9 DCH9BH=5@ C: H<=G 5DDFC57< 5D D@=98
HC EI5BH=H5H=J9 ;9C@C;=75@ A5DD=B; C: 5B CD9BD=H A=B9 <@CF=H=7 5B8
G9F=7=H=7 5@H9F5H =CB 5GGC7=5H 98 K=H< A=B9F5@=G5H=CB 7CI@8 69 A5DD98 IG
=B; 5 G=AD@9 897=G=CB HF99 =;  K<=@9 GHF5H=;F5D<=75@@M =ADCFH5BH
<CF=NCBG GI7< 5G H<9 DIFD@9 G<5@9 K9F9 GI779GG:I@@M A5DD98 IG=B; F5B
8CA :CF9GHG =;  ,=;B=:=75BH@M 6CH<  A5DG 8=GH=B;I=G< GI6H@9
J5F=5H=CBG =B A=B9F5@ 7<9A=GHFM =B7@I8=B; H<9 HF5BG=H=CB HCK5 F8G AIG
7CJ=H=7 G9F=7=H9 7@CG9 HC H<9 A5GG=J9 GI@D<=89 A=B9F5@=N5H=CB 5B8 @=H<C
@C;=75@ J5 F=5H=CBG =B 7<@CF=H9 7CADCG=H=CB -<9G9 DFCJ=89 IG9:I@ 5B5
@C;I9G :CF A=B9F5@=N5H=CB J97HCFG 8IF=B; :IHIF9 9LD@CF5H=CB DFC>97HG
5B8 <=BH 5H H<9 DCH9BH=5@ :C F AI@H=G75@9 <MD9FGD97HF5@ =BJ9GH=;5H=CBG
H<5H =BH9;F5H9 85H5 :FCA F9;=CB5@ A=B9 5B8 8F=@@ 7CF9 G75@9G
-<9 7CAD@9L 6IH ;9C@C;=75@@M F95GCB56@9 ;9CA9HF=9G 89@=B95H98 6M
H<9 F5B8CA :C F9GHG A5DD=B; F9GI@H :FCA H<9 G9F=9G C: H97HC B=7 89:CFA5
H=CBG H<5H H<9 <CGH FC7?G <5J9 699B GI6>97H98 HC 5B8 DFCJ=89 =ADCFH5BH
=BG=;<H =BHC H<9 GHFI7HIF9 C: H<9 89DCG=H CF 9L5AD@9 CIF F9GI@HG 7@95F@M
G<CK H<5H H<9 7FMDH=7 CFH5 H5@5M5 7CB;@CA9F5H9IB=H <5G 699B
:C@898 =BHC 5B 5BH=:C FA5@ GHFI7HIF9 =;  -< =G K5G A=GG98 8IF=B; DF9
Fig. 5. 5@G9 7C@CIF 7CA DCG=H9 J=GI5@=G5H=CB ;9B 9F5H98 6M A5 DD= B; H<9 @ (! 9FFCIG 5B 8 (D5EI9 =B8=79G 89]B9 8 =B -56@9 HC F98 6@I9 5B 8 ;F99B F9GD 97
H=J9@M :CF H<9 @56CF5HCFM <5B8 G5AD@ 9 G75BG 5 5B 8 <MD9F7@CI8 6   J=GI5@=G5H=CBG C: H<9G9 85H5 75B 69 :CIB 8 5H <HHDGH=BMIF @7CA75<MD9 F7 @CI8
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Fig. 6. &=B =AI A K5 J9@9B; H< A5D C: H<9 899D 9GH 56GCFDH=CB :95HIF9 69HK99B   5B 8   BA 75@7I@5H98 6M ]HH=B; H<F9 9 ;5IGG=5B :95HIF9 G HC H<=G F5B;9
5B8 G9@97H=B; H<9 899D9G H CB9 +9GI@HG :CF <5B8 G5A D@ 9G 5 5B 8 CD 9B D=H <MD9 F7@CI8 6 G<CK 9L79@@9BH 5;F99A9 BH C@CIF F9 DF9G9BHG :95HIF9 DCG=H=CB 5B 8
6F=;<HB9GG H<9 :95HIF9 89 DH< <@CF=H=7 FC7? G K=H< 5 899D 9(! :95HIF9 5F9 <=;< @=;<H98 =B ;F99B K< =@9 A= 75 CF 7@5M F=7< @=H<C@C;=9G K=H< 5 899D @(! :95HIF9
5DD9 5F =B DI FD@9 5B8 6@I9 6 6F 9J=5H=CBG 7CFF9 GDCB8 HC H<CG9 89]B98 =B =; 5B8 -56@9  J=GI5@=G5H=CBG C: H<9G9 85H5 75B 69 :CIB8 5H <HHDGH=BMIF@
7CA 75<MD9F7 @CI8
Fig. 7. =G HF=6IH=CB C: 5@H9F5H=CB A= B9F 5@G K= H< 8=GH=B7 H=J9 5@H9F5H=CB :95HIF9 G =B H< 9 ,0"+ ;9 B9F5H98 6M D5 GG=B; H<9 AI @H=:95HIF9 A= B=AI A K5J9 @9B;H<
A5DG =; H<FCI; < 5 897=G=CB HF99 -<9 F9 GI@HG <= ;<@=;<H H<9 AIG7CJ=H=7 G9F=7=H9 5@H9F5H=CB DF CL=A5 @ HC H<9 A5GG=J9 GI@D< =89 A=B 9F5@=G5H=CB &;F=7< F9
;=CB5@ 7<@CF=H=7 5@H9F5H=CB 5B8 AC F9 9F=7< 7< @CF=H9G 5GGC7= 5H98 K=H< 5@H9F5H=CB 5@CB; :5I@HG 5B8 K=H<=B H<9 GHC7?KCF? NCB9 C: H<9 89DCG=H A=75 5B8 7@ 5M
F=7< NCB9 B9 5F H<9 GIF:579 =G 5@GC 9J=89BH K<=7 < K9 =B H9FDF 9H HC F9GI@H :FCA F979BH K9 5H<9F=B; -<=G A5D 75B 69 J=9K98 =B  5H <HHDG H=BMIF @7CA
75<MD9F7 @CI8
J=CIG A5DD=B; 75AD5=;BG 9; S9N&CBH9G 5B8 5F7S5F9GDC
 DF9GIA56@M 8I9 HC H<9 8=:]7I@H=9G 8=GH=B;I=G<=B; H<=G @=H<C@C;M
5B8 5779GG=B; H<9 F9@9J5BH CIH7FCDG -<9 <MD9F7@CI8 A5DD=B; F9GI@HG
5B8 5GGC7=5H98 GHFI7HIF5@ A95GIF9A9BHG =;G 5B8 <5J9 H<IG 5@
S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
Table 3
!MD9FD5 F5A9 H9F J5@I9 G H9GH98 8I F=B; <MD9 FD5F5A9 H9F CDH=A= G5H=CB 5B 8
H<9=F 7CFF9GDCB8=B ; J5@I9G CF 5 89H5=@98 89G7 F=D H=CB C: 957< <MD9FD5F5
A9H9F D@95G9 F9:9F HC H<9 G7=?=H @95FB 8C7 IA9 BH5H=CB
!M D9FD 5A 9H9F -9GH98 F5 B; 9 (DH= AIA J5 @I 9
&5 L= AIA :95H IF9G D9F HF 99 
&5 L= AIA HF 99 89DH<  
&=B= AI A G5 AD @9G GD @=H 
&=B= AI A G5 AD @9G @95: 
CCHGH F5 D -FI9 5 @G9 -FI9
@CK98 IG HC 7CA9 ID K=H< 5 F9J=G98 GHFI7HIF5@ =BH9FDF9H5H=CB C:  =;
 :IFH<9F <=;<@=;<H=B; H<9 J5@I9 C: CIF 5DDFC57< LD@CF5H=CB ;9C@C
;=GHG 5H  <5J9 G=B79 J5@=85H98 5GD97HG C: H<=G GD97HF5@ =BH9FDF9H5H=CB
H<FCI;< H5 F;9H98 ]9@8 A5DD=B; C: H<9 DIFD@9 G<5@9 IB=H 5B8 :C@898 
7CB;@CA9F5H9
-<9 + F9GI@HG 5@GC <=;<@=;<H GCA9 7<5@@9B;9G H<5H 7CI@8 69 58
8F9GG98 =B :IHIF9 GHI8=9G =FGH@M 5 7CAD5F=GCB C: H<9 7@5GG=]75H=CB F9
GI@HG K=H< H<9 ;9C@C;M A5D C: S9N&CBH9G 5B8 5 F7S5F9GDC 
GI;;9GHG H<5H H<9 F5B8CA :C F9GH 7@5GG=]9F =G BCH 56@9 HC 577IF5H9@M 8=G
H=B;I=G< 69HK99B 6@57? G<5@9G 5B8 A5GG=J9 GI@D<=89G -<=G =G IBGIFDF=G
=B; 5G 6CH< IB=HG 5F9 7<5F57H9F=G98 6M ^5H 5B8 ;9B9F5@@M @CK
F9^97H5B79 GD97HF5 =B H<9 /'"+ 5B8 ,0"+ !CK9J9F =H =G DCGG=6@9 H<5H
H<9G9 IB=HG 7CI@8 69 GI779GG:I@@M 8=GH=B;I=G<98 IG=B; :95HIF9G H<5H <=;<
@=;<H GI6H@9 8=::9F9B79G =B H<9 J=G=6@9 5B8 /'"+ D5 FHG C: H<9 GD97HFIA 7:
=; CF 6M 75DHIF=B; 5B8 =BH9;F5H =B; @CB;K5 J9 =B:F5F98 =A5;9FM
H<5H 75 B 69HH9F 8=G7F=A=B5H9 G=@=75H9 A=B9F5@G 5GGC7=5H98 K=H< H<9 A=B9F
5@=N5H=CB 9; EI5FHN
,97CB8@M K9 5@GC =BH9FDF9H H<5H H<9 ,9F=7=H9 IB=H 5GGC7=5H98 K=H<
CL=8=G98 5B8 K95H <9F98 A5H9F=5@ 5@CB; H<9 BCFH<9FB F=A C: H<9 D=H F9
GI@HG :FCA GID9F;9B9 7@5M A=B9F5@G :CFA=B; =B K95H <9F98 7<@CF=H9 JC@
75B=7G .B:CFHIB5H9@M <5B8G5AD@9G :FCA H<9G9 @C75H=CBG 7CI@8 BCH 69
Fig. 8. &5D 5 7F CGGG97H=CB 6 5B8 @CB;G97H=CB 7 J=9KG C: H<9 + 7@5GG=]75H=CB -<9 <5 B8 G5AD @9G IG98 HC HF5=B H<9 + 5F9 CJ9F@5=B =B 5 IG=B ; 5DDF CL=
A5H9 @C75H=CBG A95GIF98 K=H< 5 <5B8<9 @8 ), 5B8 7C@CIF98 6M H<9=F @569 @ 7 : -56@9  ,5A D@9G G9@97H98 :CF 1+ 5B5@MG9G  DD9B8=L  5F9 5@GC <=;<
@=;<H98  J=GI 5@=G5H=CBG C: H<=G 7@5GG=]75H=CB 75 B 69 :CIB8 5H <HHDGH=BMIF@ 7CA 75<MD9F7 @CI8
Fig. 9. ,7<9 A5H=7 GHFI7HIF5@ 7FCGG G97H=CB C: H<9 CFH5 H5@5M5 CD9B D=H 65G98 CB 5B =B H9FDF 9H5H=CB C: H<9 <MD9FGD97 HF5@ A5DD= B; F9GI @HG 5B8 GHFI 7HIF5@ A95
GIF9A9BHG 9LHF57H98 :FCA H<9  <MD9 F7@CI8 .B =HG 5F9 @569 @@98 57 7CF8=B; HC =;G 5B8 5B 8 8F 5D98 CB H<9 &' J=GI5@=G5H=CB DF9G9BH98 =B =; 9 8
8=B; A9 5GI F9A9 BHG 9LHF57H98 65 G98 CB H<9G9 A5DD= B; F9GI @HG 5B8 H<9  HCDC;F5D< M 5F9 CJ9F@5=B CB 5 5B 8 D@ CHH98 CB 5 @CK9F <9 A=GD<9 F9 9EI5@5F95
GH9F9C;F5D <=7 DFC>97H=CB 6 IG=B; ,H9F9CB9H  @ @A9B8= B;9F   CBHCIFG =B 6 K9F9 75@7I@5H98 IG =B; H<9 $5A6 A9 H<C8 @ @A9B8= B;9F 9H 5@
 5B8 IG 98 HC 89]B9 H<9 5J9F5;9 CF=9BH5H=CB C: 957< :C@8 @=A6 5B8 <9 B7 9 9GH=A5 H9 H<9 CF=9BH5H=CB C: H<9 :C@8G 5L=5@ D@5B 9
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S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
F9HF=9J98 8I9 HC 5779GG @=A=H5H=CBG 5B8 GC K9F9 BCH =B7@I898 =B CIF
HF5=B=B; 85H5G9H "H =G @=?9@M H<5H =: G5AD@9G 7CI@8 69 F9HF=9J98 H<9B H<=G
GID9F;9B9 NCB9 7CI@8 69 A5DD98 5G 5 8=GH=B7H @=H<C@C;M 6M H<9 + ,=A=
@5F@M 7<@CF=H=7 G<5@9G CIH7FCDD=B; 5@CB; H<9 GCIH<9FB A5F;=B C: H<9 D=H
7CI@8 BCH 69 8=GH=B;I=G<98 :FCA 7<@CF=H=G98 JC@75B=7G =B H<9 BCFH< 8I9 HC
5 @57? C: G5AD@9G :FCA H<=G IB=H =B H<9 HF5=B=B; 85H5G9H 7: =; 
9GD=H9 H<9G9 @=A=H5H=CBG CIF F9GI@HG 5F9 5 7@95F 89ACBGHF5H=CB H<5H
K=H< 589EI5H9 7CFF97H=CBG 5B8 75F9:I@ :95 HIF9 G9@97H=CB <MD9FGD97HF5@
=B:CFA5H=CB 75B 69 EI5BH=H5H=J9@M 7CAD5F98 69HK99B @56CF5HCFM 5B8
CIH7FCD G75@ 9G J9B H<CI;< H<9 F5 B8CA :CF9GH 7@5GG=]9F K5 G HF5=B98 9L
7@IG=J9@M CB @56CF5HCFM57EI=F98 GD97HF5@ =A5;9FM C: =B8=J=8I5@ <5B8
G5AD@9G =H K5G 56@9 HC GI779GG:I@@M 7@5GG=:M H<9  <MD9F7@CI8 5B8 9L
HF57H A95B=B;:I@ ;9C@C; =75@ =B:CFA5H=CB -<=G 5DDFC5 7< <5G G=;B=:=75BH
DF57H=75@ 58J5BH5;9G CJ9F HF58=H=CB5@ A9H<C8G 6975IG9 H<9 B998 :CF
GI6>97H=J9 @56CIF=BH9BG=J9 5B8 DCH9BH=5@@M IBG5:9 ]9@8A5DD=B; HC
7F95H9 HF5=B=B; @569@G =G F98I798
-<=G 5DDFC57< =G A589 DCGG=6@9 6M H<9 =BH=A5H9 =BH9;F5H=CB C: ;9C
A9HF=7 5B8 GD97HF5@ 85H5 J=5 5 <MD9F7@CI8 )F9J=CIG GH5H 9C:H<95FH 5D
DFC57<9G 9; $FIDB=? 5B8 $<5B  5F9 @=A=H98 6M 7CB:C IB8=B; 5H
ACGD<9F=7 5B8 =@@IA=B5H=CB 9::97HG K<=7< F98I79 H<9 577IF57M C: 5IHC
A5H=7 A5DD=B; A9H<C8G -<9 =BH9;F5H=CB C: <=;<F9GC@IH=CB ;9CA9HFM
=BHC H<9 GD97HF5@ DFC79GG=B; KCF?^CK 5@@CKG G=;B=:=75BH@M 69HH9F 7CF
F97H=CB C: H<9G9 9::97H G 5B8 H<IG ACF9 57 7IF5H9 GD97HF5@ 89F=J5 H=J9G 5B8
7@5GG=]75H=CBG )F9J=CIG A9H<C8G :CF 7CF9;=GH9F=B;  ;9CA9HFM K=H<
GD97HF5@ 85H5 9; #5?C6 9H 5@  <5J9 699B @=A=H98 6M =B577IF5H9
5B8 @56CF=CIG A9H<C8G :CF 9GH=A5H=B; H<9 DCG=H=CB 5B8 CF=9BH5H=CB C:
H<9 <MD9FGD97HF5@ G9BGCF -<9 )B) GC@IH=CB =AD@9A9BH98 =B hylite 7=F
7IAJ9BHG H<9G9 =GGI9G 5B8 5@ @CKG A5BM 8=::9F9BH <MD9FGD97HF5@ 85 H5G9HG
HC 69 657?DFC>97H98 5B8 :IG98 =BHC 5 <MD9F7@CI8 -<9 J5 @I9 C: H<9G9
85H5 =G :I FH<9F 9B<5B798 6M H<9 5GGC7=5H98 <=;< F9GC@IH=CB ;9CA9HFM 5G
H<=G  =B:C FA5H=CB =G 7F=H=75@ :CF =BH9FDF9H=B; H<9 ;9CA9HFM C: ;9C @C;=
75@ 6C8=9G -<=G =G 9L9AD@=]98 6M CIF 56 =@=HM HC A5D :C @898 IB=HG 5H 
J=GI5@=G9 H<9 F9GI@HG =B  5B8 9LHF57H GHFI7HIF5@ A95GIF9A9BHG H<5H
7CBGHF5=B H<9 :C @8G 5L =5@ D@5B9 =; 
=B5@@M CIF F9GI@HG 5@GC GI;;9GH H<5H GCA9 <MD9FGD97HF5@ 89F=J5H=J9G
9; A=B=AIA K5J9@9B;H< A5DG 5B8 65B8 F5H=CG 5F9 F9@5H=J9@M G75@9
=BJ5F=5BH :C F DFCD9F@M 7CFF97H98 85H5G9HG -<=G F5=G9G H<9 =BH9F9GH=B;
DCGG=6=@=HM H<5H &% 5@;CF=H<AG HF5=B98 CB @=6F5F=9G C: <5B8G5AD@9G
7CI@8 5=8 A5DD=B; 57 H=J=H=9G 5H @5F;9F G75@9G 5B8 697CA9 8=;=H5@ ;9C@C
;=GHGH<5H 5GG=GH =BH9FDF9H5H=CB 9::CFHG 6M C6>97H=J9@M 7CBJ9FH=B; !,"
85H5 :FCA 8F=@@ 7CF9 CIH7FCD A=B9:5 79 5B8 5=F6CFB9 75AD5=;BG =BHC
@=H<C@C;=75@ A5 DG 5B8 @C;G -<=G KCI@8 DFCJ=89 5 IB=]98 5D DFC57< H<5H
5A9@=CF5H9G =GGI9G K=H< =B7CBG=GH9BH @C;;=B; 5B8 A5DD=B; K<=7< 7CA
ACB@M D@5;I9 A=B9F5@G 9LD@CF5H=CB 5B8 =B 8C=B; GC :5 7=@=H5H9 9::CFHG HC
GMBH<9G=G9 5B8 <CAC;9B=N9 F9;=CB5@ 85H5 G9HG "H 5@GC DFCJ=89G 5 A97<5
B=GA :CF ;9B9F5H=B; H<9 @5 F;9 5B8 FC6IGH HF5=B=B; 85H5 G9HG H<5H 5F 9 7F=H=
75@ :CF H<9 GI779GG:I@ 5DD@=75H=CB C: AC89FB A57<=B9 @95FB=B; A9H<C8G
7. Conclusion
-<9 CD9BGCIF79 hylite D57?5; 9 DFCJ=89G 5 IB=:CFA KCF?^CK :C F
:IG=B; F5K <MD9FGD97HF5@ 85 H5 :FCA AI@H=D@9 G9BGCFG 5B8 57EI=G=H=CB
;9CA9HF=9G =BHC F58=CA9HF=75@@M 5B8 ;9CA9HF=75@@M 7CFF97H98 <MD9F
7@CI8G -<9 D57?5;9 75 B H<9B 69 IG98 HC 89F=J9 ;9C@C;=75@@M F9@9J5BH
85H5 DFC8I7HG GI7< 5G A=B=AIA K5J9@9B;H< A5DG 65B8 F5H=CG 5B8
GD97HF5@ 7@5GG=]75H=CBG -C 89ACBGHF5H9 H<=G K9 IG98 hylite HC 7CA6=B9
 ;FCIB865G98 5B8  ./6CFB9 <MD9FGD97HF5@ =A5;9G =BHC 5 G=B
;@9 F9^97H5B79 <MD9F7@CI8 -<=G K5G IG98 HC A5D @=H<C@C;M 5B8 5@H9F
5H=CB A=B9F5@C;M HC 5H H<9 C FH5 H5 @5M5 A=B9 5B 8  7<5F57H9F=G9 H<9
GHFI7HIF9 5B8 ;9CA9HFM C: H<9 FC7?G <CGH=B; H<9 89DCG=H 5B8  =89B
H=:M GI6H@9 7<5B;9G =B 5@H9F5H =CB A=B9F5@C;M H<5H 7CI@8 69 IG98 5G A=B
9F5@=N5H=CB J97HC FG -<9G9 F9GI@HG <=;<@=;<H H<9 DCH9BH=5@ C: <MD9FGD97
HF5@ =A5;=B; :CF F5D=8 5B8 C6>97H=J9 A=B9:579 A5DD=B; 5B8 7CF9
@C;;=B; 6CH< C: K<=7< 5F9 9GG9BH=5@ HC AC89FB A=B=B; 9LD@CF5H=CB 5B8
CF989DCG=H F9G95F7<
Decl aration of Competing Interest
-<9 5IH<CFG 897@5F9 H<5H H<9M <5J9 BC ?BCK B 7CAD9H=B; ]B5B7=5@
=BH9F9GHG CF D9FGCB5@ F9@5H=CBG<=DG H<5H 7CI@8 <5J9 5DD95F98 HC =B^I
9B79 H<9 KCF? F9DCFH98 =B H<=G D5D9F
Acknowledgem ents
-<9 5IH< CFG KCI@8 @=?9 HC 57 ?BCK@98;9 9LH9BG=J9 GIDDCFH :FCA H5
@5M5 &=B=B; 8IF=B; ]9@8KCF? 7CB8I7H98 :CF H<=G DI6@=75H=CB 5B8 GI6
G9EI9BH J5@=85H=CB C: H<9 F9GI@HG -<=G F9G95F7< 5@GC F979=J98 :IB8=B;
:FCA H<9 IFCD95B .B=CBG !CF=NCB  F9G95F7< 5B8 =BBCJ5H=CB DFC
;F5A IB89F ;F5BH 5; F99A9BH 'C  ,- K5 G GIDDCFH98 K=H< :IB8
=B; :FCA -CH5@ +C69FH 3=AA9FA5BB =G ;F5H9:I@@M 57?BCK@98;98 :CF
]9@8 5GG=GH5B79 CF99B 69FH #I5B9@=D9 IGHCG 5B8 '5 CA= F5NNC
5F9 57?BCK@98;98 :CF <9@D=B; K=H< G5AD@9 DF9D5F5H=CB 5B8 8F5:H=B;
];IF9G 09 KC I@8 5@GC @=?9 HC H< 5B? %5 IF9BH =@@9F9G 5B8 5B 5B CBMACIG
F9J=9K9F :CF H<9=F =BG=;<H:I@ 5B8 7CBGHFI7H=J9 7CAA9BHG
Append ix A. Suppleme ntary data
,IDD@9A9BH5FM 85H5 HC H<=G 5FH=7@9 75B 69 :CIB8 CB@=B9 5H <HHDG
8C=CF;>CF9;9CF9J
Referenc es
5G9 B ! !C B?5J 55 F5  %I7=99F  35F7 C-9>5 85 )#  *I 5B H=H5 H=J9
F9AC H9 G9BG =B; 5H I@HF 5<=;< F9GC @IH= CB K= H< ./ GD97HF CG7CDM F9 J=9K C:
G9BG CF H97<BC@C;M A95G IF9A 9BH DFC798IF9G 5B8 85 H5 7CFF 97H=CB KCF? ^CKG
+9AC H9 ,9BG   <H HDG 8C= CF ;  FG  
7CG H5 " $< C858 58 N589< & -IG5 % <5A =G = ) @C5 ;I9B + 
A5 7<=B9 @9 5FB= B; :F 5A 9KCF ? :C F 8F =@@ 7CF9 A= B9F5 @ A5 DD=B ; IG =B;
<MD9FG D97HF5 @ 5B8 <=;< F9GC @IH= CB A= B9F5 @C ;=75 @ 85 H5 :I G= CB "  # ,9@ -CD
DD@ 5FH < (6G +9 ACH9 ,9BG    <HHDG 8C= CF ; 
#,-+,  
@@A 9B8= B;9F + 0  ,H9F9CB9H 
@@A 9B8= B;9F + 0 5 F8 CNC ' =G< 9F  &   ,HFI7HIF 5@ ;9C@ C; M
5@ ;CF= H<AG /97HCF G 5B 8 H9BG CF G 5 A6F= 8; 9 .B=J 9FG= HM )F 9GG
9A=G , ) &= 7?@9H<K5 =H9 , -IFB 9F  #5A9 G & + ? 7=N , -<=9@9 ,-
5B; 5G < !   FCIB865 G98 5B 8 ./5G9 8 D<CHC; F5 AA 9HFM AI @H=
G75@ 9 <= ;<F9 GC @IH=CB A5 DD=B ; HCC@ :C F GH FI7HIF 5@ ;9C@ C;M 5B8
D5@9 CG9= GA C@C;M # ,HFI 7H 9C@   <H HDG 8C= CF ;  > >G;
  
C;; G -  ,D 97HF5@ )MH< CB ,)M
CI65B ;5 -CA6 9H , !I CH  /=H=BG " !9 I69F;9 F , /9IJ 9  =G9@9 
!9KG CB + IMCH  &5 F7CHH9  <5A 69F@5B 8 &  -<9F A5 @
=B:F 5F 98 <M D9FG D97HF5 @ =A 5; =B; :CF A= B9F5 @C;M A5 DD=B; C: 5 A= B9 :579
+9AC H9 ,9BG  
F58 G? =  $5 9<@9F   %95F B= B; (D 9B/ CAD IH9F J= G=CB K= H< H<9
(D 9B/ @= 6F 5F M (+9=@@M &98=5 "B 7
F9=A5 B %  +5 B8CA :CF9 GHG &5 7< %95F B  
I7?@9M , # $I FN - ! !C K9@@ # ,7<B9= 89F   -9FF9G HF=5 @ @= 85F 5B8
<MD9FG D97HF5 @ 85H5 :IG= CB DFC8 I7HG :CF ;9C@ C;=7 5@ CIH7FC D 5B 5@ MG =G C AD IH
9CG7=    <HHD G 8C= CF ; > 75 ;9C   
@5F ? +' ,K 5M N9  %= JC $  $C ?5 @M +  ,IH@ 9M ,# 5@HCB #
&7CI;5@ + + 9BH    "A 5; =B; GD 97HFCG7C DM 5FH < 5B8 D@ 5B 9H5F M
F9AC H9 G9BG=B; K=H< H<9 ., , -9HF57 CF 89F 5B8 9LD9FH GM GH9A G # 9CD <MG +9G
)@5B 9HG  
I85 <M - #CB9G & -<CA 5G & %5 I?5A D  5 779HH5 & !9KG CB +
+C8; 9F  /9FF 5@ @ &  '9LH ;9B9F5 H=CB A=B9F5@ A5 DD=B; *I 99BG@5 B8
5= F6CF B9 !M &5 D 5B8 G5 H9@@=H 9 ,-+ GIFJ 9M G   )9FH< )I6@=7 @M
J5= @56@9 +9 D ) 
9F=B; & &=7? @9H<K5 =H9 , -<=9@9 ,- /C @@ ;; 9F , F I89B + 
+9J= 9K C: 8F CB9G D< CHC; F5 AA 9HFM 5B8 9A9F;= B; G9BG CF H97<BC@C ;M :CF H<9
GHI8M C: 8M?9 G 9GH DF 57 H=G9G 5B8 :IHIF9 DCH9BH=5@ # /C @75B C@ 9CH<9FA +9 G
  <HHD G 8C= CF;  > >J C@ ;9CF 9G   
=9N&C BH9G  9@@ =8C &I@5 G  ,P B7<9N 5 F7S5 - 5F7 =5 F 9GDC # 
%=H<C;9C7<9A=G HFM C: /C@75B=7 +C 7?G =B H<9 +SC -=BHC &=B9 "6 9F=5 B )MF= H9 9@H
!I9@J 5 ,D5=B "BGH =HIHC 9C@U;=7 C M &=B9FC 89 G D5T5 &5 8F=8
=9N&C BH9G  5 F7=5 F 9GDC #   9C@C; =75@ A5D C: H<9 +=C -=BHC 5F 95 

F5G9F , 0<=H 6CIF B % 25 B; $ +5 A5 B5 =8CI  C BBCF ) )CFC D5 H 
,CC@ 9 ) &5GCB ) C K5 F8  )<=@ =DG +  &=B9F5 @C ;= 75@ :5 79
A5 DD=B ; IG=B ; <MD9FG D97HF5 @ G75B B=B; :CF A=B9 A5DD =B; 5B 8 7CBHFC @ "B
IGH F5 @5 G=5B "BGH =HIH9 C: &= B=B; 5B8 &9H5 @@IF ;M )I6@ =75H=C B ,9 F=9G )F 9G9BH98
5H H<9 H< "BH9FB 5H=CB5 @ &= B=B; 9C@ C;M C B:9F9B79 DD 
=F5 F8 95I &CBH 5IH   @ CI8 CA D5F9
F99B  9FA5B & ,K =HN9F ) F 5=; &  HF 5BG: CF A5 H=CB :CF

S.T. Thiele et al. Ore Geology Reviews xxx (xxxx) 104252
CF 89F= B; AI @H=G D97H F5 @ 85 H5 =B H9FA G C: =A 5; 9 EI 5@ =HM K=H< =A D@ =75H =C BG :CF
BC=G 9 F9AC J5 @ " -F 5BG 9CG7= +9ACH9 ,9BG   <H HDG 8C= CF ;
 
!5 9GH & I 85<M - %5 I? 5A D  F 9;CF M ,  *I 5B H=H5 H=J9 A=B9F5 @C;M
:FCA =B :F 5F 98 GD97HF CG7C D=7 85 H5 " /5 @=85 H=CB C: A= B9F5 @ 56IB 85B7 9 5B8
7CAD CG =H=C B G7F= DHG 5H H< 9 +C7?@9 5 7<5B B9@ =F CB 89DC G= H =B 09GH9FB IGH F5 @= 5
7CB 9C@   
!5 FF =G  + &=@@ A5 B $ # J5 B 89F 05@H , # C AA 9FG + /=FH 5B 9B )
CIFB5 D95I  0=9G9F  -5M@ CF # 9F; , ,A =H < '# $9FB + )= 7IG
& !CM9F , J5 B $9F? K= >? & ! F 9HH & !5 @85B9  89@ +SC #
0=969 & )9H9FG CB ) RF5 F8 &5 F7 <5BH ) ,< 9DD5F8 $ +988M -
097?9GG9 F 0 665 G= ! C<@?9  (@ =D <5BH -   F F5 M
DFC; F5 AA =B ; K=H< 'IA)M '5 HIF9    <HHD G 8C= CF ; 
G   
!97?9F  J5 B +I=H9B699?  # J5 B 89F 09F:: ! & 5?? 9F 0 ! !9KG CB
+ J5 B 89F &99F   ,D97HF 5@ 56 GC FDH=CB :95H IF9 5B5@ MG =G :CF
]B8=B; CF 9 HIHCF= 5@ CB IG=B; H<9 A9H<C8 =B ;9 C@C; =75@ F9AC H9 G9BG =B; "
9CG7= +9 ACH9 ,9BG &5 ;   <HHD G 8C= CF ; & +, 

!CB?5J 55 F5  G?9@= B9B &  )V@V B9B " ,5 5F = ! (> 5B 9B ! &5 BB=@ 5 +
!C@A@IB8  !5 ?5@5 - %= H?9M ) +C GB9@@ -  +9ACH9 G9BG=B; C: 
;9CA 9HFM 5B8 GIF: 57 9 AC=G HIF9 C: 5 D95H DFC8 I7H=CB 5F 95 IG =B; <MD9FG D97H F5 @
:F5A 9 75 A9F5 G =B J= G= 6@ 9 HC G<CF HK5 J9 =B:F 5F 98 GD97HF 5@ F5 B;9G CB6C 5F 8 5
GA 5@ @ IBA5 BB 98 5=F6 CF B9 J9<=7@9 ./ " -F 5BG 9CG 7= +9AC H9 ,9BG 

!CB?5J 55 F5  $5 =JCG C> 5 # &Q ?M B9B # )9@@ =? ?5 " )9GC B9B % ,5 5F = !
,5 @C ! !5 ?5@5 - &5 F? @9@=B % +C GB 9@@ -  !M D9FG D97HF5@
F9^ 97H5B79 G= ;B5HIF 9G 5B 8 DC =BH 7@CI8G :CF DF 97=G =CB 5;F= 7I@HIF9 6M @= ;<H
K9=;<H ./ =A5; =B ; GMGH9A ",)+ , BB )<CH C;F5 AA +9ACH9 ,9BG ,D5H "B:
,7=  
"BJ9FB C  S 9N&CBH9G  +C G5  5F7 S5 F 9GDC # &5 HC G # 5F7 S5 %C 6UB
#% 5 FJ 5@ <C # 9@@=8 C  5 GH9@@CF5B 7C # & M5@ 5  5H=GH5 & #
+I6= C  F 5B58 C " -CFB CG  (@ =J 9=F5 #- +9M  F 5W>C / ,P B7<9N
5F7 S5 - )9F9 =F5 3 +9DF 9G5G ) ,C@P  + ,C IG5 )  "BHFC8 I7H=CB
5B8 9C@C; =75@ ,9HH=B; C: H<9 "69F =5 B )MF= H9 9@H =B 09=<98 ) 8  
5B8 )F98=7 H=J9 &C 89@@ =B; C: &5 >C F &= B9F5 @ 9@HG =B IFC D9 &= B9F5 @ +9GC IF79
+9J= 9KG ,D F= B;9F "B H9FB5H =CB5@ )I6@ =G <=B; <5A DD  <H HDG 8C=
CF;  4
#5?C 6 , 3=AA 9FA5 BB + @C5 ;I9B +   -<9 B998 :CF 577IF5 H9 ;9CA 9HF= 7
5B8 F5 8=CA 9HF= 7 7CFF 97H=CB G C: 8F CB96C FB9 <M D9FG D97HF5 @ 85 H5 :CF A= B9F5 @
9LD@ CF5H=C B &)! M, -C -CC@ 6CL :CF DF9DFC7 9GG= B; 8F CB96CFB 9
<MD9FG D97HF5 @ 85H5 +9 AC H9 ,9BG   <HHDG 8C= CF ;  FG  
$=FG7< & %CF9 BN , 3=AA 9FA5 BB + B8F 95B= % -IG5 % )CGD =97< ,
#57?=G7< + $<C858 58N589< & <5A =G = ) .B;9F  !V8@ ) @ C5;I 9B
+ &=88 @9HCB & ,I H=B9B + (>5@5  &5 HH=@ 5 # 'CF86Q7? ' )5 @A I #
) -=@>5B 89F & +IG? 99B=9A = -   !M D9FG D97HF5 @ CI H7FC D AC89@G :C F
D5@5 9CG9=G A= 7 GHI8=9G )<CHC; F5 AA +9 7   <HHDG 8C =CF ; 
D<CF 
$=FG7< & %CF9 BN , 3=AA 9FA5 BB + -IG5 % &V 7?9@ + !V 8@ ) CCM G9B
+ $< C858 58N589< & @ C5 ;I9B +  "BH9;F 5H=C B C: H9FF 9GHF =5 @ 5B 8
8FCB 96CFB 9 <MD9 FGD9 7HF5 @ 5B 8 D<CH C;F5 AA 9HF= 7 G9 BG=B ; A9 H<C8G :CF
9LD@ CF5H=C B A5DD=B; 5B8 A= B=B; AC B= HCF= B; +9AC H9 ,9BG   <HHD G 
8C= CF ;  FG  
$@IMJ9F - +5 ;5 B$9 @@9M  )RF9N  F5B ;9F  IGG CBB= 9F & F 989F=7
# $9@@ 9M $ !5 AF =7 ? # FCIH # CF@ 5M ,  #IDM H9F 'CH96C C?G5
DI6@ =G<= B; :C FA 5H :C F F9 DFC8 I7=6@9 7CAD IH5H=C B5 @ KCF? ^ CKG =B % ). DD

$F IDB=?  $< 5B ,  @ CG 9F5 B; 9 ;F CIB8 65G9 8 <MD9FG D97HF5 @ =A 5; =B ; :CF
A= B=B; 5D D@=75H=CBG 5H J5 F=CIG G7 5@ 9G +9J= 9K 5B8 75 G9 GHI8=9 G 5 FH< ,7= +9J
 
$F IG9   989@@ + % -5F5 B=? # / )9DD=B 0  095H<9F6 99 ( 5 @J =B 0
&  &5 DD =B; 5@ H9F5 H=CB A=B9F5 @G 5H DFCG D97H CI H7FC D 5B8 8F =@@ 7CF9
G75@ 9G IG =B; =A 5; =B; GD97HF CA9HFM "B H # +9A ,9BG   
$IFN -! I7? @9M , # !C K9@@ # ,7<B9= 89F   "BH9;F 5H=C B C:
D5BC F5 A= 7 <MD9FG D97H F5 @ =A 5; =B; K=H< H9FF 9G HF=5 @ @=85 F 85 H5 )<CH C;F5 AA
+97    <HHD G 8C= CF ; >      L
%5I?5A D  +C8; 9F  %9 F 5G & %5 AD =B9B ! %5 I "  )9>7 =7 
,HFC A6 9F; # F 5B 7=G ' +5 A5 B5 =8CI   &= B9F5 @ D<MG =7C7 <9A=GHFM
IB89F@ M= B; :95H IF965G9 8 9LHF 57H= CB C: A= B9F5 @ 56IB85B79 5B8 7CAD CG =H=CB
:FCA G<CF HK 5J9 A= 8 5B 8 H< 9FA5 @ =B:F 5F 98 F9^97H5 B79 GD97HF 5 &= B9F5 @G  

%9=G H9@ #& &5F7 CIL  -<=R6@9A CBH  *I 9G58 5  ,PB7<9N  @AC8U J5 F
+ )5G7 I5@  ,P9N +   -<9 JC@7 5B=7 <CGH 98 A5 GG =J 9 GI@D<=89
89DCG= HG C: H<9 "69F=5 B )MF=H9 9@H +9J= 9K 5B 8 DF 9:57 9 HC H<9 -<9A 5H=7 "G GI9
&=B9F 9DCG= H5  
%C<   (DH=75@ J=6F 5H=CBG =B G< 99H G=@= 75H9G # )<MG ,C @=8 ,H5H9 )<MG
 
%CF9 BN , ,5 @9<= , $=FG7< & 3=AA 9F A5 BB + .B;9 F  /9GH ,[F9 BG9B 
@C5 ;I9B +  +5 8=CA 9HF= 7 7CFF 97H=CB 5B 8  =B H9;F 5H=C B C: @CB; F5 B; 9
;F CIB8 65 G98 <M D9FG D97HF5 @ =A 5; 9FM :C F A= B9F5 @ 9L D@CF 5H =CB C: J9FH =75@
CIH7FC DG +9AC H9 ,9BG   <H HDG 8C= CF ;  FG  
%CK9    (6>9 7H F97C;B=H =CB :F CA @C 75@ G75@ 9=B J5 F= 5BH :95HIF 9G =B
)FC7 998=B;G C: H<9 ,9J9BH< "  "BH9FB 5H=C B5@ C B:9F 9B79 CB C ADIH9F /= G=CB
)F9G 9BH98 5H H<9 )FC7 998=B;G C: H<9 ,9J9BH< " "B H9FB5H =CB5@ CB:9F9B79 CB
CADIH9F /=G= CB DD   JC@  <HHDG 8C = CF;  " / 

&5 FH=B "N5F 8  F =5 G  F=5G & IA= 9@ ) ,5 B89FGC B # 5 GH 5T CB 
%5J5B89=F5  ,5 B7<9N #  B9K  ;9C@C;=75@ AC 89@ 5B8
=BH9FD F9H5 H=CB C: GH FI 7HIF5@ 9JC@ IH=C B C: H<9 KCF@ 87@5G G += C -=BHC /& , 89DC G=H
"69F=5 B )MF= H9 9@H ,D5=B  (F 9 9C@ +9 J   <H HDG 8C= CF ;
> CF 9;9CF9J  
&I>5 & %C K9     5GH 5D DFCL=A 5H 9 B95F 9GH B9=;<6CFG K=H< 5IHCA5 H=7
5@;CF= H<A 7CB: =;IF5H =CB /", ))  
&IFD <M +# &CBH9=FC , -  &5 DD=B ; H<9 8=GHF= 6I H=CB C: :9FF =7 =F CB
A= B9F5 @G CB 5 J9FH =75@ A= B9 :5 79 IG =B; 89F= J5 H=J9 5B 5@ MG =G C: <M D9FG D97HF5 @
=A 5; 9FM  BA ",)+, # )<CHC;F5 AA +9AC H9 ,9BG  
&IFD <M +# -5M@ CF 3 ,7<B9=89F , '=9HC #  &5DD=B; 7@ 5M A= B9F5 @G =B
5B CD9B D=H A= B9 IG=B; <M D9FG D97HF5 @ 5B 8 %=+ 85 H5 IF # +9ACH9 ,9BG 

'9G6=H )+ IF? =B )+ !I ;9B<C@ HN  ! !I 665F 8 ,& $I7<5F 7NM? &
  GHF5 H=;F 5D <=7 A5 DD=B ; IG =B; 5 8= ;=H5@ CI H7FC D AC89@ 89F= J9 8 :FCA
./ =A 5; 9G 5B8 GH FI 7HIF9:FCA AC H= CB D< CHC; F5 AA 9HFM 9CGD<9F9 
 <HHDG 8C=CF ;  , 
)98F9; CG5  /5 FCEI5IL  F5A :CFH  &= 7<9@ / -<=F =C B  F =G 9@ (
@CB89@ & )F9HH9B<C:9F ) 09=G G + I6C IF; /  ,7=? =H@95F B
&5 7<=B9 @95F B=B; =B )MH<CB # &57< %95F B +9G  
)CBHI5 @ , &9 FF M ' 5AG CB )  &9L ,D97HF 5@ "BH9FD F9H5 H=CB =9@8
&5 BI5@ IG, D97 =B H9FB5H =C B5@ ,M 8B9M
*I9G 585   F95D DF 5=G5@ C: H<9 GHFI 7HIF 9 C: H< 9 ,D5B =G < G9;A 9BH C: H<9
"69F=5 B )MF= H9 9@H &= B9F 9DC G= H5   <HHDG 8C= CF ;  
G  
+5A5 B5=8 CI  + 09@@G &   !M D9FG D97HF5 @ =A 5; =B; C: =FCB CF 9G =B
)FC7 998=B;G C: H< 9  H< "B H9FB5H =C B5@ C B;F9 GG :C F DD@ =98 &=B9F5 @C ;M " &
,DF= B; 9F DD 
+CH<9F  $C @A C;CFCJ / @5? 9   F5 6IH "B H9F5 7H=J 9 CF9 ;F CIB8
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," + )!   & )F9GG %C G B;9 @9G 5 @= :CFB =5 D  <HHDG 8C= CF ;
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!9=B7?9  $= FG 7< & @ C5 ;I9B +  "BH9;F 5H=C B C: J9GG 9@65 G98
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7C5G H5 @ 7@=::G =B H<9 F7H=7 +9AC H9 ,9BG   <HHD G 8C= CF;  
FG  
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5@ H9F5 H=CB =B @C K GI @:=8 5H=C B 9D=H<9FA 5@ GM GH 9AG 5G 89H97H98 6M "+, 5B8 1+ 
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+9J  
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<CGH =B; A5 GG =J9 GI@: =89 89DC G=HG =B H<9 "69F=5B DMF= H9 69@H ,D 5= B 7CB 9C@
  <HHDG 8C =CF ;  ;G 97CB;9 C  
-<=9@9 , - FCG9 % ,5AGI  &= 7?@9H<K5 =H 9 , /C@@;; 9F ,  F I89B  +
 +5 D=8 G9A= 5I HCA5 H= 7 :F57 HIF9 5B 8 7C BH57H A5 DD =B; :CF DC=B H 7@CI8G
=A 5;9G 5B8 ;9CD<M G= 75@ 85 H5 ,C @=8 5FH <  
-I`5 % $9FB & $<C8 5858N5 89< & @5B B=B + @C5 ;I9B + IHNA9F #
 J5@ I5 H=B; H<9 D9F: CF A5 B79 C: <M D9FG D97HF5 @ G< CF HK5 J9 =B:F 5F 98
G9BG CFG :C F H<9 DF9GC FH=B; C: 7CAD @9L CF 9G IG =B; A5 7<=B 9 @95F B=B; A9H<C8G
&=B9F B;   <HHDG 8C =CF ;  > A= B9B;   
J5 B 89F &99F  $C D5\? CJP / $CI7?P % J5B 89F 09F:: ! &  J5 B
+I=H 9B699?  # 5?? 9F 0!  05J9 @9B;H< :95HIF9 A5DD=B; 5G 5
DFCL M HC A= B9F5 @ 7<9A =G HFM :C F =BJ9GH=; 5H =B; ;9C@C; =7 GM GH9A G B 9L5A D@9
:FCA H<9 +C85@E I=@5 F 9D=H<9FA 5@ GM GH 9A "B H # DD@ 5FH < (6G
9C=B:CFA5 H=CB   <HHDG 8C = CF;  > >5 ;   
J5 B 89F &99F   J5 B 89F 09F: : ! &  J5 B +I=H9B699? #  !97?9F  
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# 0C@85= -  &I @H= 5B8 <MD9FGD97HF5 @ ;9C@ C;=7 F9 ACH9 G9BG=B;
F9J= 9K "B H # DD@ 5 FH< (6 G 9C= B:CF A5 H=CB   <HHDG 8C= CF ;
 > >5 ;   
J5 B +I=H9B699? # 5?? 9F 0 ! J5 B 89F 09F:: !& 39;9FG - (C GH<C 9?
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K5J9@9B;H< DCG= H=CB C: 899D9GH 56GC FDH=CB :95H IF9G HC 9LD@CF 9 A=B9F5 @ 8=J9FG =HM
=B <MD9FG D97HF5 @ =A5; 9G )@ 5B9H ,D57 9 ,7=   
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<9A )<MG   
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8=GD @5 79A9BH CDH= 75@ ^ CK K=H< 899D A5H7<=B; "B )FC7998= B;G C: H<9 "
"BH9FB 5H=C B5@ CB: 9F9B79 CB CAD IH9F /= G= CB DD 
25 B; $ 0<=H 6CIF B % &5 GC B ) !IBH=B;HCB #   &5 DD=B; H<9 7<9A=75@
7CAD CG =H=CB C: B= 7?9@ @5 H9F=H9G K= H< F9^97H5 B79 GD 97HF CG7C DM 5H $CB= 5A 6C '9K
5 @98CB=5 7CB 9C@    
3<CB; 2 05B; 1 1I 2 05B; , #=5 - !I 1 3<5C # 09= % 3<5B; %
 &= B= ./6C FB 9 <MD9FG D97HF5 @ F9AC H9 G9 BG=B ; F CA C6G9 FJ 5H=C B 5B 8
DFC7 9GG= B; HC 5D D@=7 5H=C BG " 9CG7= +9AC H9 ,9 BG &5 ;   <HHD G 
8C= CF ; & +,   
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... This largely involves applications based on RGB imagery and photogrammetry in stockpile volume surveying, site infrastructure inspections, and some environmental monitoring. However, UASs have the potential to act as interoperable technology with a broad range of applications that include geological pit mapping [22], geotechnical analysis, geophysical survey, rock slope stability assessment, water quality monitoring, erosion and soil loss estimation, acid mine drainage (AMD) mapping, subsidence detection and safety management (e.g., tailings dams, road haulage, etc.), 4 rehabilitation, and post-mining environmental monitoring [23,24]. In complex environments within the mining value chain, the need for Digital Terrain Models (DTM) of high precision and high spatial resolution can be fully addressed with drones equipped with light detection and ranging (LiDAR) technology [25]. ...
... Hyperspectral RS can close this gap by providing continuous data coverage complementing existing mapping capabilities. This makes hyperspectral RS data indispensable for a wide range of applications including monitoring land cover changes, detection and quantification of soil erosion, water quality monitoring, management of waste materials and TSFs, monitoring reclamation and restoration efforts, assessment of vegetation 22 regrowth and ecosystem recovery, identification of areas prone to AMD and contamination, and detecting contaminant plumes and fugitive gas emissions from the mining facilities. Areas in the resource sector yet to benefit from the routine use of HSI include stockpile mapping, geometallurgy and ore processing, re-mining/ re-valorization of TSFs and waste, close-to-face sorting to aid resource allocation and transport, surface mineralogy mapping to aid block modelling and deposit modelling, open pit lake monitoring, and active TSF monitoring. ...
Preprint
Full-text available
Hyperspectral imaging data holds great potential for various stages of the mining life cycle in active and abandoned mines. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite im-agery yields high spectral resolution, high signal-to-noise ratio (SNR), and global availability with breakthrough satellite sys-tems like EnMAP, EMIT, and PRISMA, limited spatial resolution poses challenges for mining sectors, which require decimeter- to centimeter-scale spatial resolution for applications such as reconciliation, ore/waste estimates, geotechnical assessments, and en-vironmental monitoring. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the pit/ mine scale, with the capability for frequent, user-defined re-visit times. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers to detect different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we review of applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging in or appropriate to the mining sector, especially for hyperspectral VNIR-SWIR UASs. If directly applicable, draw on previous insights derived from airborne, satellite, and ground-based imaging systems. We also discuss common practices for UAS survey planning and sampling considerations for interpretation.
... This largely involves applications based on RGB imagery and photogrammetry in stockpile volume surveying, site infrastructure inspections, and some environmental monitoring. However, the UAS has the potential to act as interoperable technology with a broad range of applications that include geological pit mapping [8], geotechnical analysis, geophysical survey, rock slope stability assessment, water quality monitoring, erosion and soil loss estimation, Acid Mine Drainage (AMD) mapping, subsidence detection and safety management (e.g., tailings dams, road haulage, etc.), and post-mining environmental monitoring [9,10]. In complex environments within the mining value chain, the need for Digital Terrain Models (DTMs) of high accuracy and high spatial resolution can be fully addressed with a UAS equipped with light detection and ranging (LiDAR) technology [11]. ...
Article
Full-text available
Hyperspectral imaging technology holds great potential for various stages of the mining life cycle, both in active and abandoned mines, from exploration to reclamation. The technology, however, has yet to achieve large-scale industrial implementation and acceptance. While hyperspectral satellite imagery yields high spectral resolution, a high signal-to-noise ratio (SNR), and global availability with breakthrough systems like EnMAP, EMIT, GaoFen-5, PRISMA, and Tanager-1, limited spatial and temporal resolution poses challenges for the mining sectors, which require decimetre-to-centimetre-scale spatial resolution for applications such as reconciliation and environmental monitoring and daily temporal revisit times, such as for ore/waste estimates and geotechnical assessments. Hyperspectral imaging from drones (Uncrewed Aerial Systems; UASs) offers high-spatial-resolution data relevant to the pit/mine scale, with the capability for frequent, user-defined re-visit times for areas of limited extent. Areas of interest can be defined by the user and targeted explicitly. Collecting data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions offers the detection of different minerals and surface alteration patterns, potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. This is related to but not exclusive to detecting deleterious minerals for different processes (e.g., clays, iron oxides, talc), secondary iron oxides indicating the leakage of acid mine drainage for rehabilitation efforts, swelling clays potentially affecting rock integrity and stability, and alteration minerals used to vector toward economic mineralisation (e.g., dickite, jarosite, alunite). In this paper, we review applicable instrumentation, software components, and relevant studies deploying hyperspectral imaging datasets in or appropriate to the mining sector, with a particular focus on hyperspectral VNIR-SWIR UASs. Complementarily, we draw on previous insights from airborne, satellite, and ground-based imaging systems. We also discuss common practises for UAS survey planning and ground sampling considerations to aid in data interpretation.
... Even though this method sounds straightforward, we argue that it is still considered an exhaustive search method to establish the pixel-to-point relationship due to the irregularity and unordered nature of lidar data. Inspired by the works in [14,15], we adopt the opposite approach, i.e., for each 3D point, find the nearest pixel. More precisely, convert 2D images into 2D points with their associated spectral features. ...
Conference Paper
Despite the extensive body of research conducted on the fusion of lidar and hyperspectral data for land cover classification in urban areas, the predominant approach has been the utilization of rasterized lidar data merged with hyperspectral data. This image-centric methodology tends to overlook the primary advantage inherent in lidar technology—namely, the production of 3D point cloud data. In our work, we present a framework demonstrating how we infer semantic information from 3D point cloud data, comprising both lidar and hyperspectral features—a concept we refer to as a 3D hyperspectral point cloud. We illustrate the generation of hyperspectral point clouds and evaluate the performance of various deep learning models for point learning. Our findings on the original test data of the 2018 IEEE GRSS Data Fusion Challenge, disclosed by IEEE Image Analysis and Data Fusion Technical Committee, indicate that recent deep learning models not only produce better shapes for predicted objects but also yield more precise semantic information. Finally, we plan to release the 3D hyperspectral point cloud data to the community, hoping to inspire future studies on data fusion in the point cloud domain.
... Then, the remote sensing data collection is comparable and allows trend analysis, change detection and forecasts [31]. For mapping and surveying applications, a correct attitude and position allow for the creation of high-resolution maps, data fusion or multi-sensor mapping [48][49][50]. Often, mapping applications require the data to be linked to a geographic information system (GIS) for accurate georeferencing [51,52]. ...
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Unmanned aerial vehicles (UAVs) and radar technology have benefitted from breakthroughs in recent decades. Both technologies have found applications independently of each other, but together, they also unlock new possibilities, especially for remote sensing applications. One of the key factors for a remote sensing system is the estimation of the flight attitude. Despite the advancements, accurate attitude estimation remains a significant challenge, particularly due to the limitations of a conventional Inertial Measurement Unit (IMU). Because these sensors may suffer from issues such as drifting, additional effort is required to obtain a stable attitude. Against that background, this study introduces a novel methodology for making an attitude estimation using radar data. Herein, we present a drone measurement system and detail its calculation process. We also demonstrate our results using three flight scenarios and outline the limitations of the approach. The results show that the roll and pitch angles can be calculated using the radar data, and we conclude that the findings of this research will help to improve the flight attitude estimation of remote sensing flights with a radar sensor.
... Four UAV surveys were conducted using a DJI Mavic Air 2 to collect >3000 digital photographs (4000×3000 pixels) covering the Puga valley floor, geothermal manifestations within it, and the adjacent~250 m high cliffs north of Puga and near Sumdo (Fig. 1). The Agisoft Metashape Professional 1.8.4 was then used to reconstruct dense 3-D models of these cliffs and the Puga valley floor, resulting in a photogrammetric digital outcrop model (e.g., Khanna et al., 2020;Thiele et al., 2021). These were meshed and textured (by back-projecting the original image data) and, for the valley floor region, converted to an orthomosaic and associated DEM with 5.54 cm/pix and 11.1 cm/pix resolution respectively. ...
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The Puga valley, in Ladakh, contains one of India's most prospective geothermal systems. Substantial geophysical and geochemical research has been conducted to characterise this system, though uncertainties regarding the subsurface reservoir's geometry and permeability structure remain a barrier to its development. In this contribution , we aim to fill some of these knowledge gaps by integrating new geological data and structural analyses with previously published geochemical and geophysical interpretations, and derive an integrated conceptual model of the geothermal system. Using digital outcrop techniques and field mapping, we identify and charac-terise several important structures (faults and foliations) that facilitate fluid flow in the otherwise impermeable Tso Morari gneiss. Petrological and field evidence for outcropping hydrothermally altered lithologies, may have formed in a geothermal system analogous to the active one, are also presented. Based on these observations and a simplified finite-element model, we suggest that tectonic and topographic stresses likely control reservoir architecture and connectivity. Lastly, we caution that geomorphological evidence for neotectonic movement on faults at Puga indicate the need for seismic hazard assessment prior to exploitation of the geothermal system, and identify potential parallels between Puga and the Yangbajing geothermal field in China.
... The latter study presents a machine learning approach for classifying geological datasets into relevant categories. Moreover, Thiele et al. (2021) introduced a Python workflow, hylite, for creating hyperclouds that integrate geometric information with hyperspectral reflectance data. This approach facilitates datadriven mapping of geological exposures and mineralogy, demonstrating its effectiveness in mapping volcanic-hosted massive sulphide (VHMS) mineralization in an open-pit mine. ...
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We develop a Transformer-based model enhanced with a Channel Attention Module (CAM) to capture the inter-channel dependencies in 3D hyperspectral point cloud data for geological applications. We hypothesize that specific channels of hyperspectral data correspond to distinct mineral types, and therefore, exploiting the relationships among these channels is beneficial for our analysis. We evaluate our method using the newly released Tinto dataset, which consists of 3D hyperspectral point clouds featuring three different spectral ranges: LongWave Infrared (LWIR), ShortWave Infrared (SWIR), and Visible-Near Infrared (VNIR).We explore four different CAMs from various networks—SENet, ECANet, CBAM, and DANet—and successfully integrate them into a CNN-based model to enhance feature representation. We specifically tailor the channel attention to our use of 3D hyperspectral point cloud data. Our experiments demonstrate significant improvements in performance after incorporating the CAM into our backbone model, which draws inspiration from the Point Cloud Transformer architecture and Vector Self-Attention mechanism. These results highlight the potential for further research into enhancing classification accuracy using hyperspectral data in geological applications. The code will be released on https://github.com/aldinorizaldy/CAM-Transformer.
Conference Paper
We argue that traditional 2D hyperspectral imaging is not adapted to many modern challenges. With the rise of high spatial resolution, hyperspectral sensors mounted on different platforms (e.g. drones, terrestrial, satellites) and innovative applications (e.g. urban mapping, mining monitoring), projections, occlusions, perspective effects and data processing limit the use of 2D hyperspectral imaging. We propose that 3D hyperclouds, in which Lidar or photogrammetric point clouds are augmented with hyperspectral attributes, can address numerous of these challenges. We demonstrate the benefits of hyperclouds and dedicated machine learning architectures with several realistic examples.
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Hyperspectral imaging is gaining widespread use in the resource sector, with applications in mineral exploration, geometallurgy and mine mapping. However, the sheer size of many hyperspectral datasets (>1 Tb) and associated correction, visualisation and analysis challenges can limit the integration of this technique into time-critical exploration and mining workflows. In this contribution, we propose and demonstrate a novel open-source workflow for rapidly processing hyperspectral data acquired on exploration drillcores. The resulting products are adaptable to the varied needs of geologists, geophysicists and geological engineers, facilitating better integration of hyperspectral data during decision making. These tools are applied to process hyperspectral data of 6.4 km of exploration drill cores from Stonepark (Ireland), Collinstown (Ireland) and Spremberg (Germany). The results are presented via an open-source web-viewing platform that we have developed to facilitate easy on and off-site access to hyperspectral data and its derivatives. We suggest that maximum value can be extracted from hyperspectral data if it is acquired shortly after drilling and processed on-site in real time, so that results can be quickly validated and used to inform time-critical decisions on sample selection, geological interpretation (logging) and drillhole continuation or termination. This timeliness and accessibility is key to ensure rapid data availability for decision makers during mineral exploration and exploitation. Finally, we discuss several remaining challenges that limit the real-time integration of hyperspectral drill core scanning data, and explore some opportunities that may arise as these rich datasets become more widely collected.
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Reflectance spectroscopy allows cost-effective and rapid mineral characterisation, addressing mineral exploration and mining cha