Introduction to Imaging

Spectroscopy

Lammert Kooistra, Michael Schaepman,

Jan Clevers, Harm Bartholomeus,

Outline

� Definition� History� Why spectroscopy works!� Measurement methods

� Non&imaging� Imaging

� Applications

� Analytical Methods� SAM� SUM

� Exercise� Cuprite

� Book Reference� Chapter 5.14 – Hyperspectral Sensing� Chapter 7.19 – Hyperspectral Image Analysis

Definition

� Spectroscopy is everywhere

� Exobiology: in search for extraterrestrial life

� Designing eye&friendly filters for new generation Xenon discharge lamp based headlights

� Rare earth elements doped Euro bills to prevent falsification

� Weaving of silver strings into carpets to increase total reflectivity in office space (to save illumination power)

� Unravel the composition of planets, moons, asteroids, and comets (as done on Mars, Mercury, Jupiter, Moon, Virtanen, etc.)

� Interaction measurement of polymeric surfaces with the environment

� Ballistic analysis in forensic medicine

Definition

� Spectroscopy is the study of light as a function of wavelength that has been emitted, reflected or scattered from a solid, liquid, or gas.

� The quantity measured is usually reflectance(expressed in %)

� Spectroradiometry is the technology for measuring the power of optical radiations in narrow, contiguous wavelength intervals

� The quantities measured are usually spectral radiance

Definition

� In literature, the terms imaging spectroscopy, imaging spectrometry, hyperspectral (e.g., Lillesand, Kiefer, Chipman), superspectral, and ultraspectral imaging are often used interchangeably. Even though semantic differences might exist, a common definition is:

� Imaging spectrometry is the simultaneous acquisition of spatially co&registered images, in many, spectrally contiguous bands, measured in calibrated radiance units, from a remotely operated platform.

� Imaging spectroscopy is the simultaneous acquisition of spatially co&registered images, in many, spectrally contiguous bands, measured as reflectance, from a remotely operated platform.

Schaepman, M.E., Green, R.O., Ungar, S., Boardman, J., Plaza, A.J., Gao, B.&C., Ustin, S., Miller, J., Jacquemoud, S., Ben&Dor, E., Clark, R., Davis, C., Dozier, J., Goodenough, D., Roberts, D., & Goetz, A.F.H. (2006 (accepted)) The Future of Imaging Spectroscopy – Prospective Technologies and Applications. In IGARSS, pp. 5. IEEE, Denver (USA).

Imaging Spectroscopy: The Data Cube Principle

Definition

� Applying this definition results in quantitative and qualitativecharacterization of both the surface and the atmosphere, using geometrically coherent spectral measurements.

� This result can then be used for the

� unambiguous direct and indirect identification of surface materials, water properties, and atmospheric trace gases,

� the measurement of their relative concentrations,

� subsequently the assignment of the proportional contribution of mixed pixel signals (e.g., spectral un&mixing),

� the derivation of their spatial distribution (e.g., mapping), and

� finally their evolution over time (multi&temporal analysis).

Definition

� Spectroradiometric measurements are one of the least reliable of all physical measurements.

� Henry Kostkowski, Reliable Spectroradiometry, 1997

� Three major reasons for large errors in spectroradiometry are:

� The measurement is a multidimensional problem,

� The instability of measuring instruments and the standards used to calibrate these instruments are frequently 1% or more during the complete measurement process, and

� The principles and techniques used for eliminating (or reducing) measurement errors due to this multidimensionality or instability have not been widely disseminated.

Definition

Optical System

Background

Transmissions- medium Photons contributing

to the total signal

Object

esrsr

sr

sr

sr

ta

at

sr

i0 Exitance

in Irradiance

a Absorbed radiance sr Scattered/reflected radiance t Transmitted radiance e Emitted radiance

sr

sr

e

t

t

sr

t

t

i0i0

i0

i1

i1

i2

i2

i2

i2

i2

i2

i3

i3

tt

a

srsr

sr

e

a

sr

sr

a

sr

sr

asr

sr sr

sr sr

a

a

srsr

sr

a

t

sra

t

sr

sr

sr

sra

sr

sr

sr

a

e

e

e

e

e

sr

sr

sr

sr

a

Source

� Contributing sources to a spectroradiometric measurement

NASA MODIS

on TERRA

1999

History of Spectroscopy

Source: Newton, I.: Opticks: or, a Treatise of the Reflexions, Refractions, Inflexions, and Colours of Light, Book I, Plate IV, Part I, Fig. 18, Sam Smith and Benj. Walford, St. Paul’s Church&yard, 1704 –Burndy Library

Sir Isaac Newton

(1642&1727)

Joseph von

Fraunhofer

(1787&1826)

Gustav Robert

Kirchhoff

(1824&1887)

Robert Wilhelm

Bunsen

(1811&1899)

Sir William

Huggins

(1824&1910)

Spectraldispersion

Continuous spectrum,interrupted by dark lines

Explanation ofFraunhofer lines

Absorptionin gas

Composition ofastronomical objects

First imagingspectrometer in space

For complete overview:Schaepman, M.E., 2007. Spectrodirectionalremote sensing: From pixels to processes. JAG 9 (2): 204

History of imaging spectroscopy

(1960s)(1970s)

(1980s)

(1990s)(2000s)

(2010s)

Why Spectroscopy Works!

� Path from the sun to the sensor

ϕ

E0 Latm

Edif

Egnd

τdτu

Lg,adj

Lgnd

Lg,dir

Ls

Why Spectroscopy Works!

The influence of the major absorption bands of atmospheric water vapour, carbondioxide and ozone on spectral signatures of vegetation, measured with the AVIRIS sensor; Flevoland test site, July 5th 1991.

wavelength (Hm)

1.90.4 0.7 1.0 1.3 1.6

20

15

10

5

0

radiance (mW/cm2/Hm/sr)

H2O

H2O

H2O

H2O H2O

H2O

O2; H2O

CO2

CO2

CO2

potatoes

maize

absorption features

Absorption features in spectra

� Electronic transitions

� Isolated atoms and ions have discrete energy states. Absorption of photons of a specific wavelength causes a change from one energy state to a higher one.

� Vibration processes

� The bonds in a molecule or crystal lattice are like springs with attached weights: the whole system can vibrate.

Electronic transitions

� High energy & low wavelength[ Q = h•ν = h•c/λ ]

� Broad features

� Between 0.2 & 1.1 microns

Vibration processes

� The frequency of vibration depends on the strength of each spring (the bond in a molecule) and their masses (the mass of each element in a molecule)

Vibration processes

� Low energy & high wavelength

� Narrow features (10&20 nm)

� Stretching of molecular bonds

� Water 1.4 +1.9 µm

� AlOH 2200 nm

� MgOH, 2300 nm

� CaCO3, 2320&2350 nm

Energy levels

2

1

0 0

1

2 4

3

2

1

0

00

HH

H H

Spectrum

2.74

2.66

6.47

Wavelength ( m)µ

H0

H H

Ene

rgy

Normal modes

0.8

0.6

0.4

0.2

0.0

Ref

lect

ance

[sca

led

from

0-1

]

24002200200018001600140012001000800600400Wavelength [nm]

0.8

0.6

0.4

0.2

0.0

Kaolinite Dolomite Hematite

Kaolinite Absorption Feature

Dolomite Absorption Feature

Hematite Absorption Feature

Kaolinite Absorption Feature

Unambiguous Identification of Spectral Diversity

Spectral Data Richness I0.15

0.10

0.05

0.00

L s [W

/(m

2 sr

nm)]

24002200200018001600140012001000800600400Wavelength [nm]

0.15

0.10

0.05

0.000.15

0.10

0.05

0.000.15

0.10

0.05

0.00

Total Radiance at Sensor (MODTRAN 4)

Imaging Spectrometer (10 nm FWHM)

Landsat 7

SPOT 4

Spectral Data Richness II

Example of vegetation stress

Each time step is 10 mins., total duration 8 hrs

Measurement is reflectance plus reflected transmittance

Undisturbedleaf

Wageningen UR 2003

Laboratory spectrometer

Measures the composition of gases, liquids or solids (PerkinElmer Lambda 900 (275&3300 nm))

Field spectroradiometers

Field measurements (MERIS Calibration)

� MERIS Cal/Val (June 2002)� Goniometric Measurements� Direct solar irradiance� Total and diffuse solar irradiance

Observations by Data Acquisition Systems� Four categories of sensors

� Exploratory missions• ESA: SPECTRA (1) and APEX (1/2); NASA: ESSP and AVIRIS

� Technology demonstrators / operational precursor missions• ESA: CHRIS/PROBA (2) and APEX (1/2); NASA: Hyperion/EO&1

� Systematic measurement missions• ESA: MERIS/ENVISAT (3); NASA: MODIS/TERRA and on AQUA, GER: ENMAP (2012),

IT: PRISMA (2012), NASA: HYSPIRI (2013)

� Operational missions• ESA: MSG&1 (4); NASA: NOAA AVHRR

Source: http://www.esa.inthttp://www.apex&esa.org

1 1/2 2 3 4

Water quality of Lake Garda using Hyperion

� 22nd July 2003

� Chl&A: chlorophyll A

� TR: tripton

� RT&model

� Giardino et al., 2007

Direct method: Mapping of Plant Functional Types

grass

herbs1

herbs2

dwarf shrub

shrub

forest

Objective: monitoring PFTs relevant forhydrodynamic roughness in floodplains

Material:HyMap image Millingerwaard

Method:MNF & SMAImage based EndmembersAccuracy assessment

grass herbs1 herbs2

dwarf shrub shrub forest

Abudance map per PFT

Conclusions:• SMA offers potential to characterize complex structure and compositionof floodplain ecosystem• Spatial distributions of PFTs well in agreement with actual situation, fractional coverage shows deviations.• The use of field information for endmember selection is an important requirement

Change of PFT distribution in Millingerwaard

0

5

10

15

20

25

30

35

40

SNV MNV RNV SWS MWS MWT

Plant Functional Type

Su

rfac

e A

rea

(ha)

2001 (CASI)2004 (HyMap)

Mapping invasive species

Underwood, E., Ustin, S., and DiPietro, D. (2003).

Mapping nonnative plants using hyperspectral imagery,

Remote Sensing of Environment, Vol. 86(2), p. 150&161.

Summary

� IS evolved over last 35 years from experimental technique to systematic measurement mission

� Technology development essential to safeguard high quality measurements

� Shift from qualitative to quantitative products &> development of physicallly based RT models

End Part I

Thank you for your attention!

© Wageningen UR