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Principles of Spectroscopy:

Much of the next set of pages [until we discuss AVIRIS], we condensed and reworded from a thorough review by Dr. Roger N. Clark of the U.S. Geological Survey, entitled Spectroscopy of Rocks and Minerals, and Principles of Spectroscopy, which you can access in its entirety at a site on the Internet. We took most of the illustrations in this summary from that source.)

Spectroscopy is the science of measuring the spectral distribution of photon energies (as wavelengths or frequencies) associated with radiation that may be transmitted, reflected, emitted, or absorbed upon passing from one medium (vacuum or air) to another (material objects). Imaging spectroscopy is the special case in which spectral characteristics and variations of one variable tie to two additional variables (the spatial dimensions, given by x and y positions), to generate color composite images (pictures), ratio and principal-components images, and classification maps. In particular, images that represent the effects of diagnostic absorption bands can be produced to show specific spatial variability of certain material features that one or more such bands discretely identify.

When illumination (either polychromatic, like sunlight, or monochromatic, such as a laser beam) strikes a material, the electromagnetic radiation will likely partition into one or more components that behave differently. Some of the radiation directly reflects. If the material is transparent, the bulk of the radiation passes through but undergoes a change in direction according to the differences in indices of refraction between the material(s) and the external medium (usually air; or water). If the material is translucent or, more commonly, opaque, fractions (wavelength-variable) of the radiation may penetrate. When it penetrates, its rays undergo refraction, but some rays ultimately reflect. Of the fraction absorbed, some converts to heat, so that the temperature of the object rises, causing an increase in emissions, detectable as thermal radiation.

If the material is granular or polycrystalline, light that reflects will strike a number of surfaces (associated with grain or crystal boundaries), meeting individual surfaces at different angles of incidence and thus scattering the radiation at various angles. The light may bounce around, or back and forth, from several such surfaces before finally leaving as scattered beams. If the object's surface is smooth (mirror-like), a significant fraction reflects at an angle related to the angle of incidence. But, most surfaces tend towards some degree of roughness, so that the percentage or proportion of light reflected directly to the observer (an eye or an instrument) notably decreases. The fraction of radiation that is absorbed also controls the degree of scattering.

For a medium such as air, which also contains CO2 and other gases, water (usually as vapor or tiny droplets), and particulates, some scattering occurs. Hence, we have blue skies from a high degree of scattering at blue wavelengths, and red sunsets from additional scattering at longer wavelengths, leaving the red radiation less affected, i.e., transmitted as red.

13-17: What is the difference, if any, between the processes that give a blue sky and a red sunset? What color is the sky as seen from the Moon's surface? ANSWER

But, air transmits or absorbs the bulk of the radiation, as indicated by this figure, with most of the minima (absorption bands) due to the presence of carbon dioxide, water, and oxygen.

Absorption band diagram due to carbon dioxide, water, and oxygen.

In the Visible-NIR range (VNIR), water ice and dry ice (solid CO2) give characteristic spectral curves, as shown here:

Spectral curve diagram for water ice and dry ice in the Visible-NIR range.

 

Over most of this range, the dry ice remains highly reflective but displays a prominent set of absorption bands around two µm. Water ice reflects at shorter wavelengths, but its reflectance diminishes beyond about one µm. Note that there are several broad absorption bands that reduce reflectance to very low values. Liquid water tends to absorb well over most of the range, reflecting slightly more in the greens and blues.

13-18: From the above two curves, beyond the visible what wavelength regions should be avoided in seeking information about the spectral characteristics of materials? ANSWER

While we need moderate to high reflectances to produce the light tones in pictorial images, the wavelength-dependent absorption bands are the features in a spectral plot that commonly aid in identifying the materials that have bands (narrow to broad) that center at specific wavelengths. In the visible region, the reflected wavelengths control the observed color(s). Thus, a bright green color of an opaque material implies strong reflectance at green wavelengths and near total absorptance in the reds and blues. If, instead, there were also notable red reflectance, yellows to oranges would result. An absorbing medium affects the intensity of incoming radiation according to Beer's Law:

I = I0e-kx

where I0 is the intensity of the incident radiation, e is the natural log, k is a constant that depends on absorption as a function of the complex index of refraction (which takes into account the role of the extinction coefficient, K), and x is the depth of penetration. The bandwidth and depth of any given absorption depends on many factors, one of which, is the spectral composition of the illumination.

To illustrate how we can use absorption bands plus reflectance levels to distinguish chemically similar materials, we now look at the spectra for two minerals: Hematite (Fe2O3) and Goethite (FeOOH). The first spectral curves, obtained with a spectrometer in a laboratory environment, cover the spectral intervals (ranges) between 0.3 and 1.0 µm (VNIR, for visible and near-infrared) and 1.0 to 2.5 µm (SWIR, for Short-Wave InfraRed).


Spectral curve diagram for Hematite and Goethite obtained from a spectrometer in a laboratory environment.

In this plot, the Goethite curve averages about 0.2 reflectance units above the Hematite curve. We use this procedure to separate multiple spectra that have similar reflectance levels. In this case, the two curves nearly coincide, if we place Goethite at its actual values. The absorption band at 0.86 µm for Hematite and 0.90 µm for Goethite permit us to distinguish the two spectrally but only with a high resolution spectrometer. These two minerals would not differentiate, if a broad-band system, such as the Multispectral Scanner band 4 on Landsat, were the observing sensor. The OH molecule in the Goethite has a slight influence on its curve at about 2.4 µm. When we examine these two minerals in the mid-IR (thermal) range, a notably different response clearly separates them.

Spectral curve diagram for Hematite and Goethite in the Mid-IR (thermal) range.

Here, there is no offset, so the overall reflectance of Hematite is greater. Note the dual narrow absorption bands for Hematite around 3 µm. A paired absorption band for Goethite near 6 µm is distinct from the single band for Hematite at 7 µm. At longer wavelengths, including two in the 8-14 µm interval available to thermal sensors, Hematite shows several shallow absorption bands (sometimes called "troughs," as contrasted to "peaks"). As we shall see later with several more examples, these MIR spectra can contain varied and definitive absorption features of considerable utility in distinguishing between and within classes of materials. Unfortunately, no one has developed yet a fine resolution instrument like AVIRIS (operating between 0.4 and 2.5 µm) for air/space platform use.

13-19: Disregarding possible atmospheric interactions, what narrow wavelength band is best for separating and mutually identifying goethite from hematite? ANSWER

One more example emphasizes the power of detailed spectra in discriminating similar materials. We present offset; (i.e., scaled), curves covering a portion of the SWIR range for several minerals in the Kaolinite family of clays.

 

Spectral curve diagram for several minerals in the Kaolinite family of clays from a portion of the SWIR range.

WXL refers to well-crystalized, while PXL refers to poorly-crystallized. Although the gross expression of the absorption features is very similar among the four samples, slight shifts in the absorption band near 2.2 µm and other fine curve shifts suggest that under exceptional circumstances we could distinguish the members of this clay group, but only with difficulty by AVIRIS.

Absorption bands play a key role in defining the spectral curves for organic matter, such as vegetation. Consider this general curve (lighter line width) depicting the VNIR spectrum for a healthy oak leaf.

 

 

Spectral curve diagram for a healthy oak leaf in the VNIR range.

At longer wavelengths, its pigments and cellular matter absorb light. Water bands also have a notable effect. Chlorophyll absorption dominates in the visible region, removing red and blue reflectances, leaving green as the dominant spectral wave range. The sharp rise in reflectance at 0.7 µm, continuing well beyond 1.1 µm, is largely the result of the walls of multiple cells reflecting the light. The second curve, rendered in heavier line weight, describes the spectrum of an oak leaf that is now dried and brown.

The next illustration shows four spectral curves, each for a particular vegetation type, and each, of the upper three, offset by 0.05 units from the one below. In general, these plots are nearly identical, with variations mainly in the depths of individual absorption bands.

Spectral curve diagram of the same material with slightly offset ranges.

Although difficult for the eye to detect and distinguish, there are real differences in equivalent absorption bands that allow us to make separations. The absorption band at 0.7 µm is a case in point. We need to use special processing to single out small differences.

13-20: If the spectral curves for these four vegetation types are so similar, how can we hope to distinguish them in the field? ANSWER

A procedure that facilitates making this distinction is continuum-removal. The continuum consists of the so-called, "background absorption," which is in essence an extrapolation of the baseline of the general curve (fits a smoothed curve to the general trend so as to extend across the base of absorption bands). This local reduction specifies the continuum and is determined by mathematic manipulation of absorption coefficients by a subtraction process.

The depth of an absorption band, D, is:

D = 1 - Rb/Rc

where Rb is the reflectance at the bottom (trough center point) of a band and Rc is the continuum base.

The result for the above four vegetation plots (and several other crop types) is a set of continuum-removal curves that show slight to moderate differences in relative reflectances at a minimum centered on 0.68 µm. At least four of these crops appear distinguishable by their separations in the 0.56 to 0.66 µm interval.

 

 

Continuum-removal diagram showing the difference in relative reflectances for various vegetation types.

The technique can work particularly well in picking diagnostic bands for minerals that are very similar in crystal structure but differ in substitution of one chemical element (usually as an ion) for another. The common minerals, Calcite (CaCO3) and Dolomite (Ca,MgCO3) have a prominent absorption band near 2.3 µm, which reaches about the same depth in spectra of each species. The continuum-removal diagram for both shows that Dolomite reaches its trough point at a slightly lower wavelength.

Continuum-removal diagram for Dolomite and Calcite.

This approach to absorption band analysis has proved to be a powerful tool for enhancement and separation of small but often significant differences that allow us to properly identify materials (those belonging to related groups and those unrelated but with absorption bands that tend to coincide).

13-21: Thematic Mapper Band 7 covers the spectral range 2.08 - 2.35 µm. Any chance that dolostone (main mineral is dolomite) can be distinguished from limestone (calcite)? ANSWER

 

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Primary Author: Nicholas M. Short, Sr. email: nmshort@epix.net

Collaborators: Code 935 NASA GSFC, GST, USAF Academy
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