1_Remote Sensing and Mineral Spectroscopy_UFRJ

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1

Sensoriamento Remoto Hiperespectral e

Multiespectral de Alta Resolução:

Princípios, Processamento de Dados e

Aplicações

Prof. Carlos Roberto de Souza Filho (IG-UNICAMP)

Perfil do curso:Princípios físicos de sensoriamento remoto; interferências atmosféricas; propriedades espectrais demateriais naturais. Noções sobre medições espectrorradiométricas com sensores portáteis e interpretaçãode dados. Sensores (orbitais e aeroportados) da região do visível, infravermelho próximo, infravermelho deondas curtas, infravermelho médio e infravermelho termal - os programas AVIRIS, HyMAP, SEBASS, HSS,HYPERION e ASTER,. Processamento de imagens multiespectrais (ASTER) e hiperespectrais (AVIRIS,

HyMAP, SEBASS, HYPERION). Exemplos de aplicação da tecnologia de S.R. e PDI em mapeamento geológicoe exploração mineral.

Bibliografia básica:

•Andrew Rencz and Robert A. Ryerson (Editors), 1999, Remote Sensing for the Earth Sciences (Manual of Remote Sensing,Vol 3), John Wiley & Sons; 3rd Edition.•Gary L. Prost, 2002, Remote Sensing for Geologists, Taylor and Francis, 2nd Edition•John A. Richards, Xiuping Jia, 2005, Remote sensing digital image analysis, Springer-Verlag, 2nd Edition.•John R Jensen, 2004, Introductory Digital Image Processing, Prentice Hall 3rd Edition.•Paulo Roberto Meneses & Joséda Silva Madeira Netto, 2002, Sensoriamento Remoto – Reflectânciados Alvos Naturais,Brasília – DF; Editora UnB, 1a Edição.•Steven Drury, 2001, Image Interpretation in Geology, Stanley Thornes Pub Ltd, 3rd Edition.•Steven M. de Jonge Freek D. van der Meer (Editors), 2004, Remote Sensing Image Analysis: Including the Spatial Domain(Remote Sensing and Digital Image Processing), Springer.•Thomas M. Lillesand, Ralph W. Kiefer, Jonathan W. Chipman, (2004), Remote Sensing and Image Interpretation, John Wiley& Sons, 5th Edition.•Freek Van der Meer, 2001, Imaging Spectroscopy: Basic Principles and Prospective Applications, KluwerAcademics.•Volume Especial da Revista Remote Sensing of Environment sobre o ASTER (Vol. 99, No. 1-2), de Dezembro de 2005.•Material bibliográfico do ASTER disponível em: http://asterweb.jpl.nasa.gov/bibliography.asp

Introduction to Spectral Remote Sensing

and Principles of Spectroscopy

• Electromagnetic Radiation

• Atmospheric windows available VNIR, SWIR, TIR

• EMR interactions with matter

• Spectroscopy

Sources: Sources: University of Campinas - Profs. Carlos Roberto de Souza Filho Lecture Notes on Remote SensingCSIRO Exploration and Mining (Australia) - Robert Hewson,Tom Cudahy and Jon HuntingtonJPL/NASA - Mike Abrams, Simon Hook - ASTER DocumentationDrury, S.A., 2001, Image Interpretation in Geology, 3rd Edition.Pontual, S., Merry, N. and Gamson, P., 1997, Spectral Interpretation Field Manual (G-MEX).

REMOTE SENSING OF E ARTH RESOURCES

(i) Source

(iii)Interaction with

surface materials

(ii) Atmos phere

(iv)Retransmission

to the atmosphere

(v)Sensors

USERS

(vi) Data (viii) Finalproducts

(vii) Interpretationand analysis

Analog ic

Digital

Visual

Digital

DATA ACQUISION DATA ANALYSIS

The Electromagnetic Spectrum

Radiowaves

Microvave

Thermal

Infrared (>3μm; <1mm)

Infrared

Near (0.78-1.5μm)

Short (1.5-3 μm)

e Mid (3-5μm)

Ultraviolet(0.28-0,38μm)

X Rays

Rays

Wavelength (μm)

UV

Visible

IV

10-6

0.38 0.780.5 0.6

RedGreenBlue

10-410-5 10-3 10-2 10-1 1 10 10210-7 103 107104 106105 108

1mm 1m

c = f * λ (wavetheory)

E = h * f (quantum theory)

E = h. c /

Electromagnetic EnergyElectromagnetic SpectrumElectromagnetic EnergyElectromagnetic Spectrum

Electromagnetic SpectrumElectromagnetic Spectrum

WavelengthWavelength(nm)(nm)

CosmicCosmicRaysRays

GammaGammaRaysRays

XXRaysRays

MicrowavesMicrowaves(Radar)(Radar)

Radio & TelevisionRadio & TelevisionWavesWavesUVUV

101055 101066 101077 101088 101099 10101010 10101111 1010121210101110101010--111010--221010--331010--441010--55

ShorterWavelengthsHigh Energy

ShorterWavelengthsHigh Energy

LongerWavelengthsLow Energy

LongerWavelengthsLow Energy

V / NIR / SWIR /V / NIR / SWIR /MWIR / LWIRMWIR / LWIR

Optical RegionOptical Region

400400 1400014000

400

0.4

400

0.4

14000

14.0

14000

14.0

1500

1.5

1500

1.5

3000

3.0

3000

3.0

5000

5.0

5000

5.0

700

0.7

700

0.7

NIRNIR MWIRMWIRSWIRSWIRRRGG LWIRLWIRBB LWIRLWIRWavelength

(nm)(μm)

Wavelength(nm)(μm)

EmittedEmittedEnergyEnergy

ReflectedReflectedEnergyEnergy



2

c = f * λ (wavetheory) E = h * f (quantum theory) E = h. c /

Reflected vs. Emitted EnergyReflected vs. Emitted Energy

1

104

1000

100

10

0.1 1 1053 7

I r r a d i a n c e

( W - m - 2 - u m - 1 )

Wavelength (µm)

EarthEmission

(100%)

EarthReflectance

(100%)

r a d i an t ex i t an c e ( W-m-2 - um-1 )

MWIR

Ass umes noatmosphere

.4 .7

Sampling the SpectrumSampling the Spectrum

NIR SWIR MWIR LWIR

400 nm400 nm 700700 15001500 30003000

RRBB

50005000 14000 nm

GG

Panchromatic: one very wide bandPanchromatic: one very wide bandLOWLOW

Multispectral: several to tens of bandsMultispectral: several to tens of bandsMEDMED

Hyperspectral : hundreds of narrow bandsHyperspectral : hundreds of narrow bandsHIGHHIGH

Blackbody radiation curve atthe sun’s temperature

Blackbody radiation curve atincadescentlamp temperature

Blackbody radiation curveat the Earth’s temperature

(373°K = H2O bo iling)

WAVELENGTH (μ

m)

0.1 0.2 10.5 2 105 20 50 100

101

1

102

103

104

106

105

107

108

109

visble radiante energy band

S p e c

t r a l r a

d i a n

t e x c

i t a n c e

( W m - 2

m - 1 )

1000°K

6000°K

200°K

300°K

2000°K

3000°K

500°K

4000°K

ENERGY DISTRIBUTION CURVES FOR BLACKBODIES AT

TEMPERATURES BETWEEN 200°K AND 6000°K

Areas under curves correspond to

the total amount of emitted energy

in all wavelengths

Stefan-Boltzmann´s Law.

Higher T => >> amount of emittedenergy

M = τ . T4

τ = Stefan Boltzmann’scte. = 5,67 . 10-8 W.m2

Wien´s Displacement Law

λmax = A/T

A = 2898μm . °K

600 K-1000K - fires

ALVO

TRANSMITIDA,REFLETIDA

TRANSMITIDA,REFLETIDA ABSORVIDA ABSORVIDA

TRANSMITIDATRANSMITIDA

ABSORVIDA ABSORVIDAESPALHADAESPALHADA

ESPALHADAESPALHADAESPALHADAESPALHADA

TODA ENERGIA TRANSMITIDA ATRAVESSA A ATMOSFERA E ALCANÇA O SENSOR SEM

SOFRER ALTERAÇÃO

TODA ENERGIA TRANSMITIDA ATRAVESSA A ATMOSFERA E ALCANÇA O SENSOR SEM

SOFRER ALTERAÇÃO

ENERGIA ABSORVIDAESQUENTA A ATMOSFERA

OU É RE-EMITIDA COM SUASCARACTERÍSTICAS

ESPECTRAIS ALTERADAS

ENERGIA ABSORVIDAESQUENTA A ATMOSFERA

OU É RE-EMITIDA COM SUASCARACTERÍSTICAS

ESPECTRAIS ALTERADAS

ScatteredScattered

Scattered

Absorbed

Absorbed

Transmitted

Transmitted

TargetReflected Image from the NASA Langley Research Center, Atmospheric Sciences Division.

http://asd-www.larc.nasa.gov/erbe/ASDerbe.html



3

Electromagnetic Energy Atmospher ic Absorp tion

Electromagnetic Energy Atmospher ic Abs orpt ion

Transmitância Atmosférica

UV NIRVIS SWIR MWIR LWIR

T r a n s m

i t â n c

i a T o

t a l ( % )

BAIXA

ALTA

Comprimento de Onda (μm)

1.0

0.4

0.6

0.8

0.2

0.00.4 0.5 0.6 0.8 1 432 5 10

Absor ção Atmos férica

Energia (luz) Transmitida

WAVELENGTH (μm)

T o t a l T r a n s m i s s i o n ( % )

Atmosp heric Absor ption

Energy(lig ht) transmitted

LOW

HIGH

Atmospheric transmittance (windows)

Atmospheric Windows

“Reflected Wavelengths” “Emitted Wavelengths”

A t m o s p

h e r i c T r a n s m

i s s

i o n

TypesTypes ofof EnergyEnergy RecordedRecorded byby SensorsSensorsandand RespectiveRespective RegionsRegions ofof the Spectrumthe Spectrum

Sensor Sun

Incoming Solar EnergyReflectedReflected SolarSolar EnergyEnergy

Sensor

EmittedEmitted thermalthermalenergyenergy

Atmosp here

SAR Antenna

BackscatteredBackscattered energyenergypulsepulse

Surface

MicrowavesMicrowaves

VISVIS – – NIRNIR -- SWIRSWIR TIRTIR

InformationInformation aboutabout chemicalchemical compositioncomposition

ofof surfacesurface materialsmaterials

InformationInformation aboutabout physicalphysical characteristicscharacteristics

((geometrygeometry andand shapeshape) of) of surfacesurface materialsmaterials

Atmosp here

U.V VIS IR

Energy

0.3μm 1μm 10μm 100μm 1mm 1m

Wavelength

Sun’s Energy ( 6000°K)

Earth’s Energy (300°K)


Transmittance

SOURCES

ENERGY

ATMOSPHERICTRANSMITANCE

0 %

100 %

U.V VIS IR

HumanEye

PhotographyThermalScanners

Mult ispect ral Scanners

Radar andPassive

Microwave


BlockedEnergy

Wavelength

Wavelength

Interaction of energy and objectsInteraction of energy and objects

Transmitted EnergyTransmitted Energy

Abso rbed Ener gy Abso rbed Energ y

Reflected EnergyReflected EnergyVV--MWIRMWIR

Emitted EnergyEmitted EnergyMWMW--LWIRLWIR

Energy Balance Equation: EI (λ) = ER(λ

) + E A(λ

) + ET(λ

)Energy Balance Equation: EI (λ) = ER(λ) + E A(λ) + ET(λ)

Incident EnergyIncident Energy



4

Reflected EnergyReflected Energy

• The manner in which a material reflects energy is primarily afunction of the optical properties and surface roughness of thefeature.

• Most objects are diffuse reflectors

• The manner in which a material reflects energy is primarily afunction of the optical properties and surface roughness of thefeature.

• Most objects are diffuse reflectors

Specular Reflectance

Specular Reflectance

DiffuseReflectance

DiffuseReflectance

Angl e of Inc iden ce = Ang le of Ref lectan ce Angl e of Inc iden ce = Ang le of Reflect ance

SmoothSurface

Rough

Surface(Microscopic)

EnergyScattered in

All Direct ions

Reflectance: Is the ratio of reflected energy to incident energy. Varies with wavelength

Function of the molecular properties of the material.

Reflectance Signature: A plot of the reflectance of a material as a

function of wavelength.

Reflectance: Is the ratio of reflected energy to incident energy. Varies with wavelength


Reflectance Signature: A plot of the reflectance of a material as a

function of wavelength.

Reflected EnergyReflected Energy

Red brickKaoliniteSandy loamConcreteGrass

All sol ids and li qui ds

have reflectancesignatures that

potentially can be

used to identify them.

All sol ids and li qui dshave reflectance

signatures that

potentially can be

used to identify them.

Emissive EnergyEmissive Energy• Emissiv ity- is a measure of how efficiently an object radiates energy compared to a

blackbody at the same temperature.

Varies with wavelength


• EmissivitySignature - A plot of emissivity as a function of wavelength. All

materials have emissivity signatures that potentially can be used to identify them.

• Emissiv ity- is a measure of how efficiently an object radiates energy compared to a

blackbody at the same temperature.

Varies with wavelength


• EmissivitySignature - A plot of emissivity as a function of wavelength. All

materials have emissivity signatures that potentially can be used to identify them.

Blackbody

Graybody

Selectiveemitter (emissivitysignature)

Selectiveemitter (emissivitysignature)

E m i s s i v i t y

0

0.5

1.0

Wavelength

Red brick Kaolinite

Grass Water

Black paint Concrete

ABS.

Fe

2+

Fe3+ REDPEAK

ABSORPTION ALTERED ROCKS SHOWHIGH REFLECTANCE

IN THIS REGION

(OH-) HYDROXYLSMINERALS (Clays),-

CARBONATES, MICAS,CHLORITE, AMPHIBOLES

DOMINANTMINERALOGICAL

EFFECTS

VEGETATIONREFLECTANCE

LEAF WATER CONTENTCELL STRUCTURELEAFPIGMENTS

TM7

SWIR ~ 2.2mm

REFLEC.PEAK

SWIR~ 1.6mm

TM5

H2O

1.4mm

WATER ABSORPTION

1.93mm

H2O

FRACA ABSORÇÃO

DE ÁGUA

REFLECTANCEPEAKVIS ~ 0.54mm

50

30

20

10

00.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.62.4

400 600 800 1000 1200 1400 1600 1800 2000 2200 26002400

WATER ABSORPTION

BANDS

2.6mm-2.73mm

BL-GREEN- RED.

1.30.72

R E F L E C T A N C E ( % )

CHLOROPHYL ABSORPTIONS

0.45μm 0.65μm

0.38 3.0

nmmm l

H2O

H2O

1.1μmTM4

0.96μm

0.7mm

( “ re d e dg e” )40

VISIBLE NEAR INFRARED SHORTWAVE INFRARED

Al-OH Mg-OH CO3=

Fe3+Fe2+

A T M O S P H E R I C

A B S O R P T I O N

VEGETATIONVEGETATION SOILSOIL WATERWATER

1 2 3

MSS74 5 6

A T M O S P H E R I C

A B S O R P T I O N

REFLEC.PEAK

WATER ABSORPTION

Vegetation SpectroscopyVegetation Spectroscopy



5

outrospigmentos

R e

f l e c

t â n c

i a águaestrutura

do dossel eestrutura foliar

água

componen tes bioquím icos:proteínalignina

celulose

chlorophyland otherpigments

water dossel

structureleafcell structure

water

biochemicalcomponents :proteinlignin

cellulose

Wavelength ( m)

Green

Vegetation Altered

Vegetation

Soil

R e

f l e c

t a n c e

( % )

Wavelength ( m)

R e

f l e c

t a n c e

( % )

SPECTRAL BEHAVIOUR OF VEGETATION

R e f l e c t â n c i a

ALTA

BAIXA

Pine

Abet o Asp en

GramaGrass

Comprimento de Onda (μm)

Curvasde Reflectância Espectralde Alguns Tipos de Vegetação

Visível Infraverm.Próximo0.4 0.9μm0.6 0.70.5

Reflectance Spectra of different types of vegetation

Wavelength

Visible Near Infrared

R e

f l e c

t a n c e

90

80

70

60

50

40

30

20

10

0

0.4 0.5 0.6 0.7 0.8 0.9

Pine

Oak

Asp en

R e

f l e c

t a n c e

( % )

Wavelength (μm)

Grass

VISIBLE NIR

TM1 TM2 TM3 TM4

Influência (i) do conteúdo de

clorofila; (ii) da forma, área e

número de folhas e, (iii) da

estrutura geral (celulose),nas

propriedades espectrais de

plantas. Embora exibam

propriedades similares no

espectro visível, as plantas

podem ser facilmente

distinguidas pela sua

reflectância no infravermelho

próximo (NIR).

Effects of (i) chlorophyll content;

(ii) of the shape, area and

number of leaves and; (iii) cell

structure of celulose on the

spectral properties of plants.

Although plants show similarsignatures in the visible

spectrum, they may be

distinguished in the NIR.Reflectance curves 1-5 show pro gressive stages of colo r changes

in leaves, previously to the Autumn. The colors varies from green,

to yellow-green, to red-green, to maroon, until they dry completely.

60

0

20

40

0.4 0.6 0.8 1.0 1.2

Wavelength (microns)

R e

f l e c

t a n c e

( % )

TM2 TM3 TM4TM1

Visible Near Infrared

0.7 1.10.90.5

Mineral SpectroscopyMineral Spectroscopy

InteractionInteraction BetweenBetween ElectromagneticElectromagneticEnergyEnergy andand SurfaceSurface MaterialsMaterials

RocksRocks // MineralsMinerals

Energy Source(Sun) Sensor

Photons reflected/emitedtowards thesensor

after interact ingwithsurfacematerials

((mineralsminerals andand rocksrocks))



6

Spectral Regions Relevant to GeologySpectral Regions Relevant to Geology

• Visible and near infrared (VNIR) – 400 - 1000 nm

– Iron oxides (Hematite, Goethite, Jarosite) – REEs

– Vegetation

• Shortwave Infrared (SWIR) – 1000 - 2500 nm

– (OH) bearing minerals

• Clays, phyllosilicates, amphiboles, sulphates

– Carbonates

• Thermal Infrared (TIR) – 8000 - 12000 nm

– Silicates: quartz, feldspars, garnets, pyroxenes

– carbonates

PhenomenaPhenomena ResponsibleResponsible ForFor SpectralSpectral BehaviorBehaviorofof MineralsMinerals andand RocksRocks

10-6 10-410-5 10-3 10-2 10-1 1 10 10210-7 103 107104 106105 108

1mm 1m

VisibleVisible

Electronic

Transitions

ElectronicElectronic

TransitionsTransitions

VibracionalVibracional


Nuclear Nuclear


SpinSpin

OrientationOrientation

TV / RadioTV / Radio

MicrowavesMicrowaves

Thermal InfraredThermal Infrared

(>3µm - <1mm)

InfraredInfraredNear (0,78-1,5 µm)

Shortwave (1,5-3 µm)UltravioletUltraviolet

(0,28-0,38 µm)

XX--RaysRays

--RaysRays

Wavelength (µm)

Causes of SpectralCauses of Spectral Behaviour Behaviour

• Absorption coefficient – wavelength-dependent

– compositional

– electronic and/or vibrational processes

• Scattering effects – Diffuse and/or specular reflection

– Volume and/or surface scattering – Single and/or multiple scattering

– wavelength-dependent

Spectral Regions Relevant to GeologySpectral Regions Relevant to Geology

• Visible and near infrared (VNIR) – 400 - 1000 nm

– Iron oxides (Hematite, Goethite, Jarosite)

– REEs

– Vegetation

• Shortwave Infrared (SWIR) – 1000 - 2500 nm

– (OH) bearing minerals

• Clays, phyllosilicates, amphiboles, sulphates

– Carbonates

• Thermal Infrared (TIR) – 8000 - 12000 nm

– Silicates: quartz, feldspars, garnets, pyroxenes

– carbonates

SPECTRAL SIGNATURESSPECTRAL SIGNATURES

1. Mineralogy

2. Cation Composition

3. Crystallinity (disorder)

4. Water (free, absorbed, structural)

5. Particle size

6. Orientation

7. Mixtures

8. Organic matter



7

Physical BasisPhysical Basis

• Minerals exhibit diagnostic features at various

wavelengths which provide a means for their

remote identification.

• These features are produced by electronic or

vibrational processes resulting from the

interaction of electromagnetic energy with the

atoms and molecules which comprise the

minerals that make up a rock.

• The different processes require different amounts of

energy to proceed, and therefore are manifest in

different wavelength regions.

• Electronic processes require the most energy and

results in spectral features at visible to near infrared

wavelengths.

• Fundamental vibrational processes require less

energy, and occur beyond 2.5 um. Between 0.5 and 2.5

um there is an overlap of features due to both

processes.

Physical BasisPhysical Basis

• Electronic Processes

– Crystal field effects, Charge Transfer

Bands, Conduction Bands, Color Centers

• Vibration Processes

– Fundamentals, Water and Hydroxl,Carbonates Other groups, e.g phosphates

Physical BasisPhysical Basis Crystal Field EffectsCrystal Field Effects

• Most common electronic process, seen in

spectra of transition elements.

• Electron moves from lower to higher energy

state by photon absorption.

• Crystal field varies with crystal structure

allowing mineral identification.

Reflectance spectra of two olivines, showing change in band shape and position

with composition. 1 um band due to crystal field absorption of Fe 2+.

Fo - forsterite (Mg2SiO4) in the forsterite-fayalite (Fe22+ SiO4) solid solution

series. Fo29 has an FeO content of 54% while Fo91 has an FeO content of 8%.

The 1 um band position varies from 1.08 um at Fo 10 to 1.05 um at Fo 90.

From Clark (1999).

Charge Transfer AbsorptionsCharge Transfer Absorptions

• Inter-element transitions where the

absorption of a photon causes an electron to

move between ions or between ions and

ligands.

• Very strong compared with crystal field

effects. Typically centered in the ultra violet

with wings extending into the visible.

• Cause of red color in iron oxide.



8

Reflectance spectra of iron oxides: hematite (Fe2O3) and goethite (FeOOH). The intense absorption

around 0.4 um is due to charge transfer. The 0.9 and 0.86 u m absorption features are due to transitions

(crystal field absorption).

From Clark (1999).

Vibrational Vibrational ProcessesProcesses

• The bonds in a molecule or crystal lattice act like

springs with attached weights. The frequency of

the vibration depends on the strength of the bond

and mass of the elements.

• For a molecule with N atoms, there are 3N -6

normal modes of vibration called fundamentals.

• The fundamental vibration modes of silicate

minerals occur near 10 um.

Silicate MineralsSilicate Minerals

0.8

1

1.2

1.4

1.6

1.8

E

m i s s i v i t y ( O f f s e t f o r c l a r i t y )

8 10 12 14Wavelength (micrometers)

Quartz

Olivine

Hornblende

Augite

Muscovite

Albite

0

0.2

Vibrational Vibrational ProcessesProcesses

• Also vibrations can occur at multiples of

the fundamental frequency.

• The additional vibrations are called

overtones when they involve multiplesof a single fundamental mode, and

combinations when they involve

different modes of vibration.

Reflectance spectra showing vibrational bands

due to OH, and H2O (from Clark 1999).Reflectance spectra showing vibrational

bands due to OH, CO3 and H2O (from Clark

1999).

Radiance andRadiance and

EmissivityEmissivity



9

PlancksPlancks FormulaFormula

⎥⎦

⎤⎢⎣

⎡−⎟⎟

⎠

⎞⎜⎜⎝

⎛ =

1exp 25

1

T

C C

M

λ λ

λ

where:

blackbody spectral exitance.

= wavelength.

absolute temperature.

first radiation constant.

second radiation constant.

λ

λ

M

T

C

C

=

=

=

=1

2

0

20

40

60

80

100

R a d i a n c e ( W / m * m * m ) / 1 . 0 e 6

4 6 8 10 12 14 16 18 20Wavelength (micrometers)

450K

350K

273.15K

SpectralSpectral EmissivityEmissivity

Materials are not perfect blackbodies, but instead emit radiation in

acordance with their own characteristics. The ability of a material

to emit radiation can be expressed as the ratio of the spectral

radiance of a material to that of a blackbody at the same

temperature. This ratio is termed the spectral emissivity:

λ λ λ ε = L L( (Material) / B lackbody)

SpectralSpectral EmissivityEmissivity (cont.)(cont.)

The most intense absorption features in the

spectral of all silicates occur near 10 µm in theregion referred to as the Si-O stretching region or

reststrahlen band.

The emissivity minimum occurs at relatively shortwavelengths (8.5 µm) for framework silicates (quartz,feldspar) and progressively longer wavelengths for

silicates having sheet, chain and isolated SiO4

tetrahedra.

Gypsum

Quartz

Sinter

Alunite

Kaolinite

Montmorillonite

Jarosite

Dolomite

Calcite

E m i s s i v i t y ( o f f s e t f o r c l a r i t y )

Spectral Analysis



10

Sources of Spectral FeaturesSources of Spectral Features -- VNIR VNIR

• Electronic processes which involve the transfer

of electrons from lower to higher energy states

within electron orbits (crystal field) or from the

ligand to the cation (charge transfer)

• Minerals included in this group:

– Hematite, Goethite, Jarosite

Hematite

Jarosite

Goethite

Wavelength (μ

m)

R e

f l e c

t a n c e

( % )

VNIR spectra of key Fe-bearing minerals

0.4 1.4

Crystal Field

Charge transfer adsorption

0,90-0,92um

0,86-0,92um0,65um

REE-bearing VNIR SpectraREE-bearing VNIR Spectra

• crystal fieldeffects

VibrationalVibrational TransitionsTransitions (SWIR)(SWIR)

• Phenomena that occur at molecular levels, caused by molecular vibrations and their effects over the bonds

between their atoms (stretch & bend). The vibrations that matter to SWIR remote sensing are not the main

ones (called fundamentalsfundamentals), but the secondary ones, called overtonesovertones and combination tonescombination tones.

• They occur generally between 1,2 a 5,0 µm and are typical of materials that contain:

•• OO--HH-- , H2O, CO32-, PO4

3- and BO33-

• The most common absorption feature of this type in geologic materials is due to OO--HH-- (hydroxylhydroxyl), common in

several minerals. The exactλ

of the feature depends on the place within the molecule where thehydroxilis located and also on the strength of the bond . These characteristics may be associated with specificfeatures, used to identify the presence of several types of minerals through the analysis of theirreflectance spectra.

• Minerals that have spectral absorption features due to vibrational transitions:

– kaolinite/dickite/haloysite - chlorites (Mg – Fe)

– pyrophyllite - biotite/phlogopite

– illite/sericite/muscovite - amphiboles (actinolite/tremolite/hornblende)

– smectites - carbonates (calcite/dolomite/siderite/magnesite/ankerite)

– Mg-clays - sulphates (alunite, gipsum, jarosite)

– chalco-silicates (epidote) - Mg-phylosilicates(talc, serpentine)

– zeolites (natrolite) - Ammonium-bearing minerals (buddingtonite, NH4-illite/sericite)



11

Sources of Spectral FeaturesSources of Spectral Features -- SWIR SWIR

• Vibrational processes related to OH – Di-octahedral and Tri-octahedral

• Fundamental stretches (2.7 - 3.0 um region)

• Fundamental bends (9.0 - 11.0 um region)

• Overtone and combination tones (SWIR active)

• 1400 nm feature (1st overtone of OH

fundamental stretching vibration)

• 2000-2500 nm features (combination of

stretching and bending vibrations)

SWIR Spectra of Minerals

Wavelength (μm)

R e f l e c t a n c e ( % )

Silicates -> ions (OH-)

+

(Mg-OH e Al-OH,...)

vibrational process

bond-bending

combinations

Absorption features at

2.2 - 2.3 m.

Micas e Clay Minerals

Kaolinite

Muscovite

Montmorillonite

SWIR Spectra of Minerals

Wavelength (μm)

R e f l e c t a n c e ( % )

vibrational process

(OH-) and H2O

in the mineral

crystalline structure

Absorption features

at 0.94 , 1.14 , 1.4 and

1.9 μm.Minerals with OH- or H2O molecules

Gipsum

Montmorillonite

HYDROXYL MINERAL GROUPS- Mineral Absorption Bands in the2000 - 2500 nm region

Al(OH) 2160 - 2170 nm – Pyrophyllite, Alunite

Al(OH) 2180 - 2228 nm – Halloysite, Kaolin ite, Dickite, Nacrite (doublets at ~1.4 and ~2.2μm) – Muscovit e, Illite, NH4-Illite (single, symmetric absorption features at~1.4 and ~2.2μm) – Montmorillonite, Palygorskite (asymmetric absorption feature at~1.4μm)

“Fe(OH)” 2230 -2260 nm – FeOH Chlorite, FeOH Biotite

“ Fe(OH)” & Al (OH) 2260 - 2298 nm – Jarosite, Nontronite & Gibbsite

• “ Fe-Mg(OH)” 2300 - 2330 nm – Phlogop ite I and II, Mg-Chlorite, Hornblende (edenite), Actinol ite/Tremolite, Talc, Serpentine (antigorite), Saponite

• “Fe-Mg(OH)” 2330 - 2360 nm – Epidote, Mg-Fe Chlorite, Fe-Chlorite, Biotite, Fe-Biotite, Hornblende

• Si (OH) 2240 nm (b ro ad ) – Opaline silica

HYDROXYL MINERAL GROUPS- Mineral Absorption Bands in the

2000 - 2500 nm region Significance of (OH)Significance of (OH)--Bearing MineralsBearing Minerals

• Mineralised environments: ie. alteration zonation (mica,chlorite, pyrophyllite, sulphates etc)

• Primary rock types (mica, amphiboles, chlorite, serpentineetc.)

• Weathering regimes and processes (kaolinite and illitechemistry, smectites, gibbsite, sulphates etc)

• Fluid composition, temperature/pressure

– e.g. Al/Mg-Fe substitution

– e.g. High temperature species: Pyrophyllite, Topaz, Dickite, etc.

– e.g. Crystallinity: Illite and kaolinite



12

Al Al --(OH) Mineral Spectra(OH) Mineral Spectra

• Most have their major combination bandabsorptions between 2160 and 2228 nm

• Some (kaolinites) have doublets in this range

• Many also have smaller secondary featuresbetween 2300 and 2400 nm

• Minerals include in this group:

– Pyrophyllite Alunite Halloysite

– Kaolinite Dickite Nacrite

– Muscovite Illite Montmorillonite

– Palygorskite

Al(OH) Mineral Spectra Al(OH) Mineral Spectra2160-2228 nm

Montmorillonite

Illite

Kaolinite

Pyrophyllite

R e f l e c t a n c e ( S p e c t r a O f f s e t f o r C l a

r i t y )

Al(OH) Mineral Spectra (zoom) Al(OH) Mineral Spectra (zoom)

Montmorillonite

Illite

Kaolinite

Pyrophyllite

R e f l e c t a n c

e ( S p e c t r a O f f s e t f o r C l a r i t y )

Kaolinite Group SpectraKaolinite Group Spectra

• Kaolinite (Kandite) Group: – Kaolinite

– Dickite

– Halloysite

– Nacrite

• All tend to havediagnostic doubletstructures near 1400

and 2200 nm

Kaolinite

Halloysite

Dickite

R e f l e c t a n c e

• Different 1400 nm doubletspacings

• Different absorption geometry between2160 and 2210 nm

Al-OH (Kaolin) Spectra Al Al--OH (Kaolin) SpectraOH (Kaolin) Spectra Hydroxyl Mineral Absorption Bands inHydroxyl Mineral Absorption Bands inthe 2000the 2000 -- 2500 nm region2500 nm region

• Al(OH) 2170 - 2210 nm – Topaz, Pyrophyllite, Kaolinite, Montmorillonite, Muscovite,

Illite

•• Fe(OH)Fe(OH) 22402240 -- 2320 nm2320 nm – – JarositeJarosite,, NontroniteNontronite,, SaponiteSaponite,, HectoriteHectorite

• Mg(OH) 2300 - 2400 nm – Chlorite, Talc, Epidote, Amphibole, Antigorite, Biotite,

Phlogopite

• Si(OH) 2240 nm (broad) – Opaline silica



13

Fe(OH) and Fe/Mg(OH) MineralFe(OH) and Fe/Mg(OH) MineralSpectraSpectra -- II

• Have their major combination band absorptions between2240 and 2320 nm, between the Al(OH) and Mg(OH) regions


– Saponite (Mg,Fe) Nontronite (Fe) Hectorite (Li,Mg)

– Jarosite (Fe) Fe-rich illite

• The first three are smectites and have deep water bandsnear 1900 nm

Fe(OH) Mineral Spectra (2240 - 2320 nm)Fe(OH) Mineral Spectra (2240 - 2320 nm)

Hydroxyl Mineral Absorption Bands inHydroxyl Mineral Absorption Bands inthe 2000the 2000 -- 2500 nm region2500 nm region


Illite

• Fe(OH) 2250 - 2300 nm – Jarosite, Nontronite, Saponite, Hectorite

•• Mg(OH)Mg(OH) 23002300 -- 2400 nm2400 nm – – Chlorite, Talc,Chlorite, Talc, EpidoteEpidote, Amphibole,, Amphibole, Antigorite Antigorite,, BiotiteBiotite,, PhlogopitePhlogopite


MgMg--(OH) Geol. Significance(OH) Geol. Significance

• Weathering and alteration products of mafic rocks

• Components of propyllitic alteration zones

• Weathering components of kimberlitic rocks

• Secondary biotite in porphyry alteration systems

MgMg--(OH) Mineral Spectra(OH) Mineral Spectra -- II

• Have their major combination bandabsorptions between 2300 and 2400 nm

• Many have two features in this range

• Some have strong secondary featuresnear 2260 nm (believed to be related toiron)


– Amphiboles Talc Chlorites

– Epidote Phlogopite Biotite

– Anthophyllite Antigorite

Mg(OH) Mineral SpectraMg(OH) Mineral Spectra2300-2400 nm



14

Mg(OH) Mineral SpectraMg(OH) Mineral Spectra Chlorite SWIR SpectraChlorite SWIR Spectra

Wavelengths of Chlorite features vary with Mg / Fe composition.

Note in this plot the 1900 nm water band does not change but

all the other chlorite features vary as these two chlorites havedifferent Mg / Fe ratios.

Fe absorption near1100 nm causes variable

gradients in this region

Hydroxyl Mineral Absorption Bands in the2000 - 2500 nm region


Illite

• Fe(OH) 2250 - 2300 nm – Jarosite, Nontronite, Saponite, Hectorite

•• Mg(OH)Mg(OH) 23002300 -- 2400 nm2400 nm – – Chlorite, Talc,Chlorite, Talc, EpidoteEpidote, Amphibole,, Amphibole, Antigorite Antigorite,, BiotiteBiotite,, PhlogopitePhlogopite


Si(OH) Mineral Spectra

• Have a very broad feature near 2240-2250 nm

• Sometimes also associated with deepwater bands near 1430 and 1930 nm

• Minerals included in this group

– Opaline silica

Si(OH) Mineral SpectraSi(OH) Mineral Spectra2240 nm

Hydrothermal opaline silicaspectra from Cuprite Nevada

Other Minerals active in the SWIROther Minerals active in the SWIR

• Carbonates

• Sulphates

• NH4 minerals

–buddingtonite



15

Carbonates – Geol. Significance

• Zonation possibly indicative of proximityto base metal carbonate-gold systems – Distal to porphyry source & cool

• (Fe) Siderite

• (Mn) Rhodochrosite

• (MnMg) Kutnahorite

• (MgCaFe) Ankerite

• (MgCa) Dolomite

• (CaMg) Mg-Calcite

• (Ca) Calcite

– Proximal to porphyry & hot

Carbonate SWIR Spectra

• Major 2300 - 2400 nm feature• Minerals included in this group

– Calcite, Dolomite, Magnesite, Siderite, Ankerite

• Ferroan species show broad absorptionnear 1000 nm

• Many carbonates also have a smallabsorption feature near 2000 nm

Carbonate SWIR SpectraCarbonate SWIR Spectra2300-2400 n m

Carbonate SWIR SpectraCarbonate SWIR Spectra

Mg Ca

Sulphate Mineral SpectraSulphate Mineral SpectraSulphates have their (OH) bands inrelatively unique positions and are

easily interpreted

Ammonium Mineral SWIR Spectra Ammonium Mineral SWIR Spectra



16

• VNIR spectral effects ⇒ changes in iron oxide unit cell

• Al3+ substitution in Hematite and Goethite – Al3+ smaller cation than Fe - distorts unit cell

– Up to 33% Al substitution for Fe in Goethite

– Broadens and shifts absorption to longer wavelengths

– 900 nm crystal field absorption - 39 nm shift

• Mn2+ and Fe2+ substitution for Fe3+ in Maghemite – Broad conduction band - reduces albedo

– Ref: Morris et. al. (1985)

Mineral ChemistryMineral Chemistry -- Spectra (1)Spectra (1) Mineral ChemistryMineral Chemistry -- Spectra (2)Spectra (2)

• SWIR Absorptions related to vibration of

octahedrally coordinated atoms (Al3+, Fe2+,Fe3+, Ca2+, Mg2+, Cr3+, Ti4+, vacancies)

• Tschermak substitution (e.g. white micas)

– Tetrahedral Si4+ for Al3+

– Octahedral Mg2+ or Fe2+ for Al3+

– Increase interlayer cations K, Na, Ca

• Cation substitution (Al, Fe and Mg) in chlorite,

biotite, phlogopite

– Mg number (Fe:Mg ratio)

White MicaChemistry

Muscovite

PhengitePhengite

(Mg,Fe)(Mg,Fe)octoct SiSitettet == AlAloctoct AlAl tettet

Wavelength (nm)

4.004.00

3.403.40

3.603.60

3.803.80

3.203.20

3.003.00

21902190 22052205 22102210 2215221521952195 22002200

RRIIIIII == AlAloctoct + V + Cr+ V + Cr

muscovitemuscovite

phengitephengite

R I I I ( m o l )

From Scott and Yang, 1997

• Tschermak substitution

• Longer λ => less Al, more Si anddivalent cations (Mg and Fe++)

Chlorite Spectral CharacteristicsChlorite Spectral Characteristics

Compositional Effects - IIICompositional EffectsCompositional Effects -- IIIIIIChlorites

Wavelength of FeOH absorption versus Mg number

y = -16.243x + 2261.6

R 2 = 0.9011

2242

2244

2246

2248

2250

2252

2254

2256

2258

2260

2262

0 0.2 0.4 0.6 0.8 1

M g N umbe r

W a v e l e n g t h ( n m )

Compositional Effects - IVCompositional EffectsCompositional Effects

--

IVIV

Chlorites

Wavelength of M gOH absorption versus Mg number

y = -41.2x + 2365.5

R 2 = 0.9192

2320

2325

2330

2335

2340

2345

2350

2355

2360

2365

0 0.2 0.4 0.6 0.8 1

M g N umbe r




17

Compositional Effects -VCompositional EffectsCompositional Effects --VV

Biotites and Phlogopites

Wavelength of MgOH absorption versus Mg number

R 2 = 0.9071

y = -41.184x + 2361.4

2315

2320

2325

2330

2335

2340

2345

2350

2355

2360

2365

2370

0 0.2 0.4 0.6 0.8 1

M g N u mb er


CrystallinityCrystallinity

• Ordered versus disordered kaolinites

– More ordered samples produce stronger, sharper

absorptions: doublets are more sharply defined

– The Hinckley Index – usually clear correlation

– Other Kaolin family variations

• (Halloysite, Kaolinite, Dickite)

• Ordered versus disordered illite / muscovites

– 1M, 2M & 2T illites

Kaolinite Hinckley Index SeriesKaolinite Hinckley Index Series Water EffectsWater Effects

• Water is SWIR active

– reduces overall brightness

– reduces spectral contrast of mineral features

– may even completely obscure features

• Water is a blackbody in TIR

• Major water absorptions at 1450, 1920, 2700 and 7000 nm

• Major ramp down from 1000 - 2700 nm

• Samples should therefore be “dry”

• SWIR can identify different types of water

• Hydrous species (eg. Smectites, Halloysite)

SWIR Water SpectrumSWIR Water SpectrumWater has its own SWIR spectrum

that mixes with mineral spectra

Dry and Wet Cracow KaoliniteDry and Wet Cracow KaoliniteWet samples can compromise

spectral interpretation



18

Particle Size Effects - 1

• Rock versus Powder measurements – Generally smaller particle size (powders) yields

brighter spectra

– Powders produce relatively weaker absorptionsdue to greater surface scattering and less volume

scattering

• Not all minerals react to grain size effects in the

same way or to the same degree

– volume (multiple/single) scattering

– absorption coefficient (opaque/transparent)

Particle Size EffectsParticle Size Effects

Powders yield brighter

spectra than rocks

Particle Size EffectsParticle Size Effects

These three calcite grain sizes illustrate thatsmaller particle sizes yield brighter spectra

with reduced absorption depths

Mineral Mixture EffectsMineral Mixture Effects

• Linear mixtures – magnitude of spectral features correlated with abundance

– single scattering (e.g. many clays)

• Non-linear mixtures – Magnitude of spectral features correlated non-linearly with

abundance (e.g. carbonates)

– multiple scattering

– contrasting absorption coefficients (opaques andtransparent materials like sulphides mixed withcarbonates/quartz/mica/chlorite).



19

Kaolinite / Muscovite MixturesKaolinite / Muscovite Mixtures

Computed additive mixtures

Muscovite / Chlorite MixturesMuscovite / Chlorite Mixtures

Computed additive mixtures

QuartzMicroclineOrthoclaseAlbite

QuartzMicroclineOrthoclaseAlbite

Visible -SWIR

thermal IR

Library DHR - Quartzites

R e f l e c t a n c e

SilicaCrystallinity

0.45

0.55

0.65

0.75

0.85

0.95

7.5 8.5 9.5 10.5 11.5 12.5 13.5

wavelength (um)

e m i s s i v i t y

CUP001A

CUP001B

0

1000

2000

3000

4000

5000

6000

7000

8000

15 25 35 45 55 65

XRD 2theta

i n t e n s i t y

Cup1A

Cup1B

Opaline

Chalcedony



20

Feldspars

• Ubiquitous

• 11 types

(structure-

chemistry)

• K-Na-Ca ternary

• Alkali vs

plagioclase

• Chemistry, temp

• Igneous rock

classification

• Alteration

Alkali

feldspars

Plagioclase feldspars

Feldspar TIR Reflectance Spectra

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

7.5 8.5 9.5 10.5 11.5 12.5 13.5

wavelength (μ

m)

r e f l e c

t a n c e

microcline (K)

orthoclase (K/Na)sanidine (K/Na)

albite (Na)

labradorite (Na/Ca)

anorthite (Ca)

9.62

9.48

10.0

9.0

10.5

9.3

alkali

plagioclase

Field TIR

spectra

y = 12.7x - 46.8

R2

= 0.61

0.95

1

1.05

1.1

1.15

1.2

1.25

3.765 3.77 3.775 3.78

XRD d-spacing

r a t i o

o f m F T I R e

m i s s i v i t i e s

( 9 . 6 μ m / 9 . 9 μ m )

albite-rich

0

0.05

0.1

0.15

0.2

0.25

0.3

8 8.5 9 9.5 10 10.5 11

wavelength (μ

m)

e m

i s s

i v i t y

Y100i.txt

Y101ii(B)txt

Y107b.txt

Y107c.txt

Y107l.txt

Y115ii.txt

Y121ii.txt

Y122i.txt

Y123iii.txt

Y123iv.txt

Y124i.txt

Y124iv.txt

Ca albite-rich

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

8 8.5 9 9.5 10 10.5 11

wavelength (μ

m)

e m

i s s

i v i t y

Y100ii.txt

Y101viii.txt

Y109i.txt

Y111iii.txt

Y112i.txt

Y112iv.txt

Y112iii.txt

Y113ii.txt

Y113i.txt

Y116i.txt

Y118iii.txt

Y119i.txt

Y119iv.txt

Y127i.txt

Na anorthite-rich0

0.05

0.1

0.15

0.2

0.25

8 8.5 9 9.5 10 10.5 11

wavelength (mm)

e m

i s s

i v i t y

Y101ix.txt

Y101vii(A)txt

Y108i.txt

Y110i.txt

Y110ii.txt

Y114i.txt

Y114ii.txt

Y120ii.txt

Albitised monzodiorites

Feldspar ChemistryTIR (all l) and XRD (3.7 d-spacing)

y = 0.7267x + 1.0317

R2 = 0.6705

3.768

3.77

3.772

3.774

3.776

3.778

3.78

3.782

3 .7 66 3 .7 68 3 .7 7 3 .7 72 3 .7 74 3 .7 76 3 .7 78 3 .7 8 3 .7 82

actual XRD d-spacing

p r e d i c t e d X R D d

- s p a c i n g

-0.012

0

0.012

7.5 8.5 9.5 10.5 11.5 12.5 13.5

wavelength (μ

m)

F R C " w e

i g h t e d " e m

i s s

i v i t y

9.6

10.59.0

8.213

Alb iti sati on

Na-rich

Ca-rich

PLS Final Regression Coeffs.

Garnets

• structural andchemical variations

– X3Y2Z3O12 where Z is

Si4+ ; X and Y vary

VNIR-SWIR

0

0.5

1

1.5

2

2.5

3

3.5

7.5 8.5 9.5 10.5 11.5 12.5 13.5

wavelength ( m)

m e a n - n o r m l a s i e d r e f l e c t a n c e

spessartine

andradite

grosssularite

pyrope

almandine

Mg-Al

Mn-Al

Al-Ca

Fe-Ca

TIR

2 groups - isomorphous

substitiuion(1) ugrandite (uvarite, grossular,

andradite) – Ca-richY site - (Al3+,

Fe3+, Ti3+ and Cr3+)

(2) pyralspite (pyrope-almandine-

spessartine) – Ca-poor

Pyroxenes



21

TIR JHU Library - Olivines

NAME SOURCE COST RANGE (nm) INSTRUMENT SOFTWARE CHARACTERISED

C OM PA TI BI LI TY A NC ILLA RY D ATA

MINLIB/3000.REF CSIRO/ DEM Nil 400-2500 IRIS XSPECTRA Samples

JPL JPL Free 400-2500 Beckman XSPECTRA Yes

USGS USGS Free 400-2500 Beckman XSPECTRA Yes

VICM CSIRO/DEM Nil 1300-2500 PIMA-II XSPECTRA/PIMAVIE

W

Some

AUSM CSIRO/DEM Nil 1300-2500 PIMA-II XSPECTRA/PIMAVIE

W

Some

SPECMIN Spe ctral Interna tio nal $US2 000 1300 -250 0 PIMA-II XSPE CT RA/ PIMAVIE

W

Yes

ISPL/USGS ISPL ? 1300-2500 PIMA-II XSPECTRA/PIMAVIE

W

Yes

SALISBURY Jack Salisbury Free MID IR FTIR XSPECTRA ?

CO2

Laser CSIRO/DEM Free 9.2-11.5 CO2Laser XSPECTRA Some + Samples

F ree= P ub licd omain N il= No co st t o p ro jec t

Available Spectral Libraries Available Spectral Libraries

JHU John HopkinsUniv. Free 2000-25.000 Yes

SWIR Spectral Libraries

• USGS & JPL libraries

– available in ENVI

– 0.4 to 15 μ m reflectance

– Minerals

– Vegetation

TIR Spectral LibrariesTIR Spectral Libraries• Johns Hopkins Univ. TIR library (available in ENVI)

– 0.4 to 15 μ m, hemispherical reflectance

– Minerals• Igneous (coarse and fine grained)

• Sedimentary (coarse and fine grained)

• Metamorphic (coarse and fine grained)

– Environmental• Soi ls

• Vegetation

• Water and snow

• Lunar

• Meteor

• Man made

FieldField--LaboratoryLaboratory--Mine SpectrometersMine Spectrometers•• IRIS Mk IV and Mk VIRIS Mk IV and Mk V VNIRVNIR--SWIRSWIR

•• PIMAPIMA--II and PIMAII and PIMA--SPSP SWIRSWIR

•• Ocean OpticsOcean Optics VNIRVNIR

•• ASD ASD FieldSpecFieldSpec ProPro VNIRVNIR--SWIRSWIR

•• COCO22 LaserLaser TIRTIR

•• MicroFTIRMicroFTIR SWIRSWIR--MIRMIR --TIRTIR

•• OARSOARS--TIPS (TIPS (HyLogger HyLogger )) VNIRVNIR--SWIRSWIR--MIRMIR-- TIRTIR

•• ASD ( ASD (FaceMapper FaceMapper )) VNIRVNIR--SWIRSWIR--MIRMIR --TIRTIR



22

Analytical

Spectral

Devices

• Fieldspec Pro

– Various configurations

– 350-2500 nm

– 10 nm spectral resulotion @ SWIR

• TERRASPEC

– More robust fibre

– contact

http://www.http://www.asdiasdi.com/.com/

TERRASPEC

Fieldspec Pro

FieldSpec FR

(CARY - 5G)

FieldSpec FR

Field Spectrometer –

FIELDSPEC FR

Field Spectrometer –

FIELDSPEC FR

FIELDSPEC FR Field Portable Spectrometer FIELDSPEC FR Field Portable Spectrometer FIELDSPEC FR Field Portable Spectrometer

• 1512 channels (spectral bands)

between 350-2500nm

• 10 measurements per second

• IFOV 25º but adaptabledown to 1º

• allows simulation of any remote sensing

system based on reflection of sun light

Field Spectrometer - PIMAField Spectrometer - PIMA PIMA Field Portable Spectrometer PIMA Field Portable Spectrometer

• SWIR only (1300 - 2500 nm)

• Suitable for phyllosilicates, sulphates, carbonates

• Internal light source (no atmospheric effects)

• “Contact” mode of measurement

• 2 nm sampling, 4 nm resolution

• 1 cm FOV

• 8 second to X minute measurement (integration)

• Australian developed & supported

• Superior SNR and spectral resolution



23

Core LoggingContinuous coreContinuous core

/chip scanning/chip scanning

0.50.5--1 cm1 cmresolutionresolution

10,000’s of10,000’s ofobservationsobservations

~ 1 m / minute~ 1 m / minuteat presentat present

1000’s1000’s metresmetres ofofcore/chipscore/chips

Field μFTIR Thermal Infrared

Spectrometer SpectralRa nge

5000-666 cm-1 (2.0-15.0 µm) (Nominalrange, but

fullrange with hot source is 6410-415 cm-1, or 1.56-24 µm.)

S pe ct ra l Sa mpling N/A

Data Interval 3 cm-1

SpectralRe solution 6 cm-1

Field of View 4.6°

S ca n Tim e 1 se c ( us ua lly ave ra ge d fo r 1 6 s ec on ds )

Power Source2.5 kg 12 V battery in sling pack for spectrometer and blackbody (4 hr. operation). Computer independently powered.

Size Optical head 25 x 25 x 20 cmElectronics/computer case 33 x 46 x 5 cm

WeightOpticalhead 4.4 kgElectronics/computer case 7.55 kg (with computer)Battery 2.5 kgLight duty tripod 1.5 kg

Field μFTIR Thermal Infrared

Spectrometer Raw Data

Wavelength (micrometers)

7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00

R a w

O u t p u t ( I n s t r u m e n t U n i t s )

0.0

6.00

12.00

18.00

24.00

30.00

Cold Blackbody Warm Blackbody Sample

Calibrated Data


7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00

R a d i a n c e ( W / m 2 u m s r )

5.00

6.00

7.00

8.00

9.00

10.00

Calibrated quartz

Apparent Emissivity


7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00

A p p a r e n t E m i s s i v i t y

0.60

0.70

0.80

0.90

1.00

1.10

Apparent quartz emissivity



24

Field vs Lab.


7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00

0.50

0.62

0.74

0.86

0.98

1.10

Fie ld measurement (uFTIR) Laboratory measurement (Nicolet)

Spectral Analysis Methods

• Spectral enhancement

– Hull quotient spectra• Background, continuum or hull removed

– Derivative spectra

• 1st or 2nd derivatives

• Feature extraction

– Gaussian decomposition - wavelengths, depths, widths andasymmetries

• Automatic Mineral Identification

– Tetracorder

– Spectral Assistant

• Similarity measures

– Partial Unmixing

– Spectral Angle Mapper

• Quantification

– Partial Least Squares

SoftwareSoftware• SIMIS (Spectrometer-Independent Mineral Identification Software)

– Field/lab spectra

• TSG (The Spectral Geologist) – Field/lab and core spectra

• TSA (The Spectral Assistant)• TSG-Core

• PIMAVIEW-111 – Field/lab spectra

• ASD – Field/lab spectra

• ENVI (Environment for Visualising Images) – Hyperspectral images


• Tetracorder (USGS SpecLab) – Hyperspectral images


• Nei l PendockSuite – ASTER and hyperspectralimages

• CSIRO/HyVista Suite – ASTER and hyperspectralimages

• ERMapper – ASTER

Reflectance, Hull and HullQuotient Spectra

Reflectance, Hull and Hull

Quotient Spectra

.... Hull or continuum

.... Hull quotient spectrum

Reflectance spectrum ....

Continuum Slope Effect



25

Spectral Analysisand its application to

Exploration and Mining

DrDr SashaSasha PontualPontual , , AusSpec AusSpec InternationalInternational

Main Approaches to SpectralMain Approaches to Spectral

Data AnalysisData Analysis

• Manual Interpretation

• Mineral identification

software

– Automated

– User defined training libraries

• Spectral parameters / digital

mineralogy

Mineral Identification SoftwareMineral Identification Software

• Rely totally upon training library

• Some have fixed libraries (e.g. TSA)

• Some have user defined libraries (i.e. built into TSG)


• Fast, consistent, digital output

• Still misses many subtle

variations

• But very useful with large

datasets

(if used intelligently)


• Questionable accuracy (i.e. if more than 2 minerals)

• Danger of “black box” mentality

• User must carry out visual checks

• User must use other knowledge (geology, target etc.)

ExampleExample

• Reconnaissance phase

• Ridge and Spur sampling

• ~5 x 5 km area

• over 2000 samples collected for

geochemical analysis

• Measured on-site using PIMA II



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Dominant Mineral Map: TSA resultsDominant Mineral Map: TSA results

IlliteParagoniteKaoliniteHalloysiteGibbsite

~ 5 x 5 kmridge and

spur samples

Single Mineral GroupSingle Mineral Group

TSA results - classextraction scalars

Illite Group

Distribution

Colours relate to

signature strength

(spectral

weightings)

Spectral ParametersSpectral Parameters

• They are measurements of:

– Wavelength

– Depth

– Width

– Areas of absorption features

– Or combinations of these values i.e. commonly asratios of depths of features

• Influenced by mineralogical factors such as

composition and crystallinity

A Few Common ParametersA Few Common Parameters

• Wavelength AlOH – illite composition

• Depth AlOH/water – illite-smectitecrystallinity

• Kaolinite crystallinity

• Wavelength MgOH/CO3

• Depth of AlOH, MgOH or FeOH

Used in over 90% of projects –

calculated automatically

Advantages of Spectral ParametersAdvantages of Spectral Parameters

• Highly specific controlled by only one or twovariations in mineralogy

• Consistent

• Very fast

• Produce digital results that can be integratedwith other data

• Allow results to be presented in a familiarformat(i.e. to the non-spectral expert geologists)

Understanding Spectral ParametersUnderstanding Spectral Parameters

• Can be influenced by several factors

• Can mean different things with different

datasets

By themselves spectral parameters arenot intelligent!



Calculating Spectral ParametersCalculating Spectral Parameters

• TSG calculates spectral parameters using

any of these methods:

– The spectral profile (i.e. directly from the

spectra)

– Arithmetic expressions (i.e. ratios)

– Feature parameters (i.e. based on

deconvolution of the spectra)

– Class Extraction Scalars (i.e. data filtered by

Class, eg. TSA Mineral 1, lithology etc.)

Provide information on:

• Alteration – Zoning, lithology and structure

• Weathering – Weathering profiles

– Weathered altered signatures

Patterns of Mineral Distribution

Applications to Mineral Exploration Applications to Mineral Exploration

IlliteIllite CrystallinityCrystallinity MapMap

Class extraction of

Spectral Parameters

- Hot coloursindicate increasedillite crystallinity

- Greys are samples with noillite

Scatterplot screen in TSG

Data Integration

• Geochemical data - elemental distribution, and

mineralisation

• Geophysical data - changing physical

characteristics

• Spectral Data - associated mineralogical

variation

Understanding alterationUnderstanding alteration--

mineralisationmineralisation relationshipsrelationships

10m

50m

55m

60m

100m

150m

200m

L i t h o l o g y

T a r g

e t

M g O

K O

2 A l O 2

3

M g O

/ K O

2

ChloriteMg Fe C

h l o r i t e

S e r i c i t e

m u s c o v i t e

p h e n g i t e

Depth

Geochemical Data Mineralogical Data(Spectral Data)

Data IntegrationData Integration

0 9 1 0 1 1 1 2 0 1

2 0 2 10 50 4

0 6 0 7 0 8 1 4 1 5 1 6 1 7

1 0 0 m E 2 0 0 m E 3 0 0 m E 4 0 0 m E 5 0 0 m E 6 0 0 m E 7 0 0 m E 8 0 0 m E 9 0 0 m E 1 0 0 0 m E11 0 0 m E 1 2 0 0 m E1 3 0 0 m E1 4 0 0m E

3 0 0 R L

3 5 0 R L

4 0 0 R L

4 5 0 R L

0 9 1 0 1 1 1 2 0 1

2 0 2 10 50 4

0 6 0 7 0 8 1 4 1 5 1 6 1 7

1 0 0 m E 2 0 0 m E 3 0 0 m E 4 0 0 m E 5 0 0 m E 6 0 0 m E 7 0 0 m E 8 0 0 m E 9 0 0 m E 1 0 0 0 m E11 0 0 m E 1 2 0 0 m E1 3 0 0 m E1 4 0 0m E

3 0 0 R L

3 5 0 R L

4 0 0 R L

4 5 0 R L

As ppm

Sericite Composition

Fe Carbonate

Basalt

Basalt

Basalt

Geochemistry

Mineralogy(Spectral data)

Mineralisation

Specifically mappingthe alteration envelope

Muscovite & kaolinitecharacterise mineralised structures

Case Study: Allendale, VictoriaCase Study: Allendale, Victoria

1_Remote Sensing and Mineral Spectroscopy_UFRJ

Documents

Transcript of 1_Remote Sensing and Mineral Spectroscopy_UFRJ