1. Signatures of Geologic Materials in VNIR-SWIR
Result of electronic and vibrational transitions (see reading)
Absorption bands strongly affected by
Crystalline structure
Distribution of species in a material
Impurities
Water, hydroxyl, transition metals, carbonate, sulfur are important species

4. MAJOR MINERAL ABSORPTION FEATURE GROUPS
1 - SPECTRAL REFLECTANCE (VNIR + SWIR)
- FERRIC AND FERROUS IRON
- REE
- Al-OH
- Fe,Mg-OH
- HOH
2 - SPECTRAL EMITTANCE (TIR)
- SILICATE BENDING AND STRETCHING MODES
- CARBONATE
- SULFATE

5. COMPOSITIONAL INFORMATION
ASTER
SPECTRAL
REGION/
SPATIAL
RESOLUTION
BAND CENTER,
MICROMETERS
COMPOSITIONAL INFORMATION
VNIR /
15 m
SWIR /
30 m
TIR /
90 m B B B B B B B B B B B B B B
FERRIC AND FERROUS IRON
AND REE ABSORPTION
- AL-O-H IN CLAYS, MICAS,
SULFATE MINERALS
- CO 3
IN CARBONATES
- Mg-O-H IN AMPHIBOLES,
MICAS
- H-O-H IN EVAPORITES, CLAYS
- SILICATE MINERALS,
ESPECIALLY SHIFT TO
SHORTER WAVELENGTHS
- SULFATE MINERALS
- CARBONATE MINERALS

6. IMPORTANT SPECTRAL VARIATIONS WITHIN
CERTAIN ABSORPTION FEATURE GROUPS
1 - I/S WAVELENGTH SHIFT OF Al-OH FEATURES
- I/S ABSORPTION INTENSITY VARIATION
2 - CARBONATE WAVELENGTH SHIFT
3 - CHLORITE WAVELENGTH SHIFT OF Fe, Mg-OH
FEATURES
4 - ALUNITE WAVELENGTH SHIFT OF Al-OH FEATURES

7. Geologic Materials
Wide variety so difficult to uniquely identify a mineral or a rock with just a few spectral measurements (multispectral vs. hyperspectral)
Without hyperspectral data, multispectral analysis relies on
Band ratios and indicies (focus on particular features)
Classification/feature extraction
“Pretty picture” semiquantitative mapping (DCS)

10. Signatures of Biological Materials in VNIR-SWIR
Chlorophyll in vegetation leads to strong absorption in visible.
Water in the plant cells leads to strong reflection (index of refration effect) at microns (the “red edge”).
Reflectance between 1.3 and 2.5 microns is essentially that of water.

11. Biological Materials How do you study dynamic behavior of vegetation?
Look for variations in spectral signatures as function of
Health
Season
Moisture Content
Soil Contaminants
Biomass

13. Compare 0.8, 1.6, and 2.2 micron reflectance to gauge
moisture content. Why not look at 1.4 and 1.9 microns?

14. As vegetation grows, spectra become dominated by its
signature. Can gauge amount of biomass by looking
at microns and comparing it to 0.4 microns (NDVI).

15. Changes in growing cycle reflected in chlorophyll content lead
to changes in slope and position of the “red edge” at 0.7 microns

18. Depth of Penetration
Reflectivity of surfaces in VNIR-SWIR is governed by just the top few microns!
So weathering rinds, desert varnish, snow, vegetation, are all problematic.

20. Effect of Vegetation
Cover: We Need A
Digital Defoliant!

21. Forced Decorrelation
Crippen and Blom (2001) method for suppression of spectral signature of patchy cover
Demonstrated for vegetation.
Snow also feasible.
Material should be spectrally distinct.
Decorrelates brightness values in each band with respect to a given index…

23. RGB (3, 2, 1)
NDVI

24. RGB (3, 2, 1)
NDSI

25. R: SI
G: RDB8
B: RDB6

28. SWIR RELATIVE BAND-DEPTH IMAGES YIELD LITHOLOGIC INFORMATION RAPIDLY
RBD FOR 2.20 MICROMETER ABSORPTION: (B5+B7)/(B6*2)
MUSCOVITE, ILLITE/SMECTITE
RBD FOR 2.33 MICROMETER ABSORPTION: (B7+B9)/(B8*2)
CALCITE
RBD FOR 2.26 MICROMETER ABSORPTION: (B6+B8)/(B7*2)
DOLOMITE
RBD FOR 2.17 MICROMETER ABSORPTION: (B4+B6)/(B5*2)
ALUNITE, PYROPHYLLITE

29. RBD8
RBD7
RBD6
B2/B1

30. After snow and vegetation “removal” and saturation stretch