OBJECTIVES for the overall lab:

1. Review the basics of spectroscopy, including how to identify different materials using spectra.

1. Develop an understanding of general spectroscopic features of rocks and minerals

1. Learn how to identify specific rocks and minerals in the visible and near-infrared wavelength range


The above figures illustrate the electromagnetic radiation spectrum, including visible light.

Spectroscopy is the study of the interaction between radiation and an object, as a function of wavelength. A spectrum is a 2-d plot of the intensity of radiation from an object vs. its wavelength. [Note the word ‘spectrum’ is singular, and ‘spectra’ is plural]. The radiation that is emitted from an object is modified by its compositional properties. The emitted radiation of a rock is controlled by its chemical makeup (the atoms and bonds within its minerals). Since the spectrum of a rock will change based on variations in rock chemistry, this is one way we can identify different rock compositions using spectra. In the visible wavelength region, the chemistry of an object is reflected in its color. This color strongly controls the shape of its spectra, as we will see later in lab.


A trained geologist can gather diagnostic information just by looking at the color, texture, density, and other physical properties. A typical human eye will respond to wavelengths from about 380 to 750 nm (the ‘visible’ portion of the wavelength spectrum). To generate the data for the first part of this lab, we used a portable reflectance spectrometer to extend our “vision” to a slightly longer wavelength range. The ALTA II spectrometer wavelength range is 470-940 nm (or 0.47-0.94 m — see table below). In the second part, we will look at the reflectance spectra of minerals out to even longer wavelengths into the near-infrared.

Useful Wavelength Units

Converting nanometers to meters: 1 nm = 1×10-9 m

Converting microns to meters: 1 m = 1×10-6 m

Converting microns to nanometers: 1 m = 1000 nm

Watch the lab video where your instructor demonstrates the use of the ALTA II spectrometer, and uses it to collect the data you’ll need for the 1st part of the lab exercise.

1. Below is the data table generated using the ALTA II Reflectance Spectrometer on the orange and the basketball. It is your job to plot this data: either sketch and label their spectral shape on the plot below or graph it (with labels) in Excel if you are comfortable with using that software for graphing. (Note that relative reflectance value is only needed to draw the spectral shape. While the overall shape of a spectrum should remain constant, it may shift up and down along the y-axis due to changing lighting conditions. Since these are RELATIVE values only, this is one of the ONLY times in this class you are not required to specify the units).

Wavelength (nm)BasketballOrange
470 blue80180
525 cyan113375
560 green133545
585 yellow2361030
600 orange3441150
645 red4041380
700 deep red3021462
735 IR14261233
810 IR23761413
880 IR33831130
940 IR43601005








Wavelength (nm)

Examining your reflectance data, and comparing it to the wavelengths associated with different colors of light on page 1, what can you conclude about the relationship between the color you see and reflectance patterns? Does the position of your peak intensity (highest reflectance) make sense, given the color of the objects we analyzed?


1. Now that you understand how to acquire and look at visible spectra, you will learn how spectra are used to identify different minerals. In the lab video, we also collected reflectance data on a series of mineral specimens.

a) Watch the video and then briefly describe each of the four minerals presented, given what you see and what the instructor says about each.





b) Now that you have visually examined the suite of minerals, use the ALTA II spectrometer data provided and the spectral library plot on the following page to identify the mineral name of each sample (A, B, C, and D). Be aware that the wavelength unit of the plot is in microns (m) so you’ll need to convert your units to compare directly (see page 2 for the conversion factor). A spectral library is just a set of spectra taken in a laboratory setting of a set of standard, already-identified minerals. (Note that while the reflectance value on the y-axis may be shifted up or down due to lighting conditions, the overall shape of the spectra must match). Again, feel free to plot this in Excel if you’d like.

Wavelength (nm)Mineral AMineral BMineral CMineral D








Wavelength (nm)







A= B=

C= D=

2. Now we will look at some spectra taken in the visible and near-infrared (longer wavelengths). The longer wavelength range is sensitive to: 1) the energy transitions of electrons between orbital shells within particular atoms that make up many (but not all) minerals, and 2) vibrations of the bonds between those atoms. Both the electron transitions and bond vibrations absorb energy at different wavelengths, which are diagnostic of the absorbing mineral. Because of this, visible and near-infrared wavelengths are useful for identifying many types of minerals. Below is an example of several minerals in this wavelength range (note that the spectra have been vertically offset so you can more easily see the differences in their shapes):






a) Minerals rich in iron (Fe) often have a large, broad ‘bowl-shaped’ absorption feature at around 1.0 m or so, because of electronic transitions in the Fe atom. Which of the above minerals contains Fe?

b) The “Unknown mix” is a rock. As rocks are aggregates of multiple minerals, this rock is composed of two minerals. As such, the spectrum of this rock has components of the spectral shape of both minerals (i.e. it has absorption features that are present in both). What two minerals (from the choices olivine, calcite, and kaolinite) make up the “Unknown mix” rock?

3. Finally, we will look at an example spectrum from the planet Mars. CRISM (Compact Reconnaissance Imaging Spectrometer for Mars) is a spectrometer on board the Mars Reconnaissance Orbiter spacecraft, orbiting Mars. Planetary scientists have used the CRISM visible and near-infrared spectra to interpret some of the mineralogical variations on the surface of Mars, including the identification of new outcrops of phyllosilicates (clay minerals). Below is an example image that CRISM has taken in a region called Nili Fossae.


Off Clay (bland)

On Clay


5 km

CRISM scene from the Nili Fossae region

Picture 4

We’ve taken spectra from both an area rich in clay (“On Clay,” signified in red) and an area with little or no clay (“Off Clay,” signified in green). Below we have them plotted together on the same graph. Note that they both have a similar overall slope, but that the “Off Clay” spectrum is more “bland” with no distinct absorption features.

To enhance the signature in the “On Clay” spectrum, as planetary spectroscopists often do, we will divide the “On Clay” spectrum by the “Off Clay” (or bland) spectrum. This is done by dividing the reflectance value of every point in the “On Clay” spectrum by the reflectance of the “Off Clay” spectrum at the same wavelength. Dividing one spectrum by the other removes the features in common to both spectra (for example, the overall sloping of the spectra) and enhances the features that make them different. This gives us a so-called “ratioed spectrum” as seen below.

Picture 3

Finally, we will compare the ratioed spectrum of our clay-rich outcrop with several different phyllosilicates (sheet silicates, including clays) from a spectral library (samples from Earth, measured in a laboratory spectrometer). On the next page we have the Mars clay-rich outcrop (“Outcrop”) plotted with other laboratory phyllosilicates (“SMECTITE”, “KAOLINITE”, and “ILLITE”). Note: smectite, kaolinite, and illite are common clay minerals on Earth.

Picture 7





a. Identify the type of phyllosilicate that is found in the Nili Fossae outcrop (Hint: be sure that the wavelength value of the minimum point of each absorption feature matches the Nili Fossae outcrop spectrum):

b. On Earth, these clays form in the presence of liquid water. What implication does this statement have for the Nili Fossae area on Mars?



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