introduction to imaging spectroscopy · the power of optical radiations in narrow, contiguous...
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Introduction to Imaging
Spectroscopy
Lammert Kooistra, Michael Schaepman,
Jan Clevers, Harm Bartholomeus,
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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
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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
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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
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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®istered 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®istered 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).
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Imaging Spectroscopy: The Data Cube Principle
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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).
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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.
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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
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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
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History of imaging spectroscopy
(1960s)(1970s)
(1980s)
(1990s)(2000s)
(2010s)
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Why Spectroscopy Works!
� Path from the sun to the sensor
ϕ
E0 Latm
Edif
Egnd
τdτu
Lg,adj
Lgnd
Lg,dir
Ls
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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
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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.
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Electronic transitions
� High energy & low wavelength[ Q = h•ν = h•c/λ ]
� Broad features
� Between 0.2 & 1.1 microns
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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)
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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
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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
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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
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Spectral Data Richness II
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Example of vegetation stress
Each time step is 10 mins., total duration 8 hrs
Measurement is reflectance plus reflected transmittance
Undisturbedleaf
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Wageningen UR 2003
Laboratory spectrometer
Measures the composition of gases, liquids or solids (PerkinElmer Lambda 900 (275&3300 nm))
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Field spectroradiometers
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Field measurements (MERIS Calibration)
� MERIS Cal/Val (June 2002)� Goniometric Measurements� Direct solar irradiance� Total and diffuse solar irradiance
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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
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Water quality of Lake Garda using Hyperion
� 22nd July 2003
� Chl&A: chlorophyll A
� TR: tripton
� RT&model
� Giardino et al., 2007
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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
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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)
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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.
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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
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End Part I
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Thank you for your attention!
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