Summary of skills covered:
|Data needed:||Students will collect and graph their own data using a spectrometer.|
|Equipment and Software needed:||
|Related book exercise
No text necessary.
|Data Source:||Not applicable.|
A webinar on the use of infrared imagery is also available for viewing
During this activity you will collect, manipulate, and graph data to understand the properties of light. You will also gain an understanding of the electromagnetic spectrum and reflectance of light by creating your own spectra from your data, and graphing it on the handouts that are provided.
Figure 1: The electromagnetic spectrum.
X-rays, thermal radiation, microwaves, radio waves, and gamma radiation all travel through space at the speed of light. They interact with matter both electrically and magnetically, and together are called electromagnetic radiation. By sensing electromagnetic radiation, we can see the world around us. When you listen to the radio in your car, the songs you hear (or at least the signal your radio uses to vibrate the speakers) are also the result of electromagnetic radiation traveling from the antenna at the radio station to the antenna on your car. Different kinds of electromagnetic radiation differ in wavelength and this results in a spectrum. The visible spectrum (the colors that humans can ‘see’) is only a small portion of the larger electromagnetic spectrum (Figure 1). The electromagnetic spectrum is divided into major types of radiation which include:
Our eyes are sensitive to the areas of the electromagnetic spectrum between the colors red and purple. Our eyes measure of the amount of radiation reflected from objects around us, and our brains translate these measurements into an image of our surroundings. Although we cannot see it, objects around us interact with the invisible radiation the Sun radiates across the entire spectrum. The wavelengths outside of the visible wavelengths can only be measured with the aid of special equipment. By designing sensors that are sensitive to these wavelengths of light we can use artificial “eyes” to study these interactions. You will use such equipment today to measure wavelengths of light that your eyes cannot see.
Each type of electromagnetic radiation has its own unique wavelength and moves through space as a wave. The wavelength of electromagnetic radiation is the distance from one crest of a wave to the next wave crest (or one trough to the next trough: Figure 2). These types of waves can also be described by their frequency. The frequency of a wave is the number of whole waves or cycles that pass by a given point in a certain amount of time.
Figure 2: The wavelength of electromagnetic radiation is measured from crest to crest.
When visible light radiation hits an object, some of it reflects off the object and into our eyes. Not all of the light will be reflected off the object as some of it may be absorbed or even transmitted through the object itself. The way that light is absorbed by an object usually determines what color it appears, and is determined largely by the chemistry of the surface (the atoms and molecules that make up an object). If a blank sheet of paper does not absorb any light, it appears white because it reflects all wavelengths equally. If all light that hits an object is absorbed, then no light will be reflected off of it and it will appear black.
Figure 3: Artists representation of remote sensing satellite orbiting the Earth.
Most of the time when light hits an object, only certain wavelengths of visible light are absorbed. A good example of partial light absorption occurs when light strikes a leaf. Leaves typically absorb wavelengths that correspond to blue, yellow, orange, and red wavelengths. This differential absorption is due to the chemical chlorophyll, present in most healthy leaves, which absorbs these wavelengths of light and converts the light energy into sugars to be used for food by the plant in a process called photosynthesis. The green color we see from the leaf is a result of the green wavelengths reflected by chlorophyll, since this is what is reflected from the leaves and can travel to our eyes, as well as the relative absence of blue, yellow, orange and red wavelengths which are absorbed. Leaves also contain other pigments which can give them other colors depending on the amount of pigment present:
These differences in absorption and reflectance of different colors of light give us important clues to understanding and interpreting the world around us. When absorption differences are observed from a satellite image or airplane, scientists can determine the ripeness of crops, health of forests, origin of pollutants, etc. These sensors can provide vital information that is used by an array of everyday business needs.
In this activity, you will obtain reflectance data for a green leaf, standardize the results against a white poster board, and perform data analysis. Although it may not be obvious, the process you will follow is very similar to that used by scientists who use Earth observation satellites, such as Landsat, to study Earth’s surface from space. Landsat is the world’s longest-running moderate resolution satellite series; since 1972, one or more Landsat satellites have been observing the Earth’s surface. Like the ALTA II Spectrometer, the Landsat satellites record the electromagnetic radiation reflected from Earth in various portions of the spectrum. This information is then sent back to Earth as satellite images, and is used by experts in many different fields, including agriculture, forestry, and regional planning.
Foresters use Landsat satellite imagery to identify specific areas of their fields where crops are stressed. Using near infrared and other wavelengths, they can identify crops with insect infestations, irrigation needs, disease, or differences in soil fertility. Vegetation stress in crops can often be discovered and mitigated long before it is evident to the human eye. By the time humans can visually notice the damage, the situation is often too late to correct. Firefighters use Landsat images to identify ‘hot spots’ (using the thermal wavelengths) to coordinate firefighting efforts during a large forest fire event. Urban planners can compare Landsat images over time to identify growth areas of a city using an array of wavelengths. The use of satellite imagery, such as Landsat, is invaluable to our economy.
Feel free to explore additional information about the Landsat program here: http://landsat.gsfc.nasa.gov/education/.
Figure 4: The ALTA II Spectrometer.
The ALTA reflectance spectrometer (Figure 4) works very similarly to a sensor aboard a Landsat satellite. The spectrometer is like a mechanical eye. When you go outdoors on a sunny day and look at a leaf, it appears green. As mentioned above, this green color is due to the absorption by the leaf of red and blue wavelengths of light, and the reflection of green wavelengths to your eye. In this case, the source of the light is the sun, shining on the leaf. If you looked at the same leaf in the middle of the night it would not look green to you (unless you used a flashlight!). The ALTA spectrometer uses a light source (something like a flashlight) to illuminate an object you want to study, before using a sensor (a bit like your eye) to measure the amount of light that the object reflects.
If you look at the back of the spectrometer you will see a ring of small lamps. These lamps are the source of the light you will measure. The larger object in the middle of the ring is the sensor, or detector. Like your eye, the detector measures the amount and characteristics of light reflected by any object placed beneath the spectrometer. If you place an object beneath the spectrometer and push the blue button, the spectrometer will shine blue light (light with a wavelength of about 470 nanometers, nm, where a nanometer is a billionth of a meter) onto the object, and the sensor will at the same time measure how much of that light is reflected. If you push the red button, the spectrometer will shine red light onto the object and measure the amount of red light (645 nm) that is reflected. You will notice that the lower four buttons are not colored. Pressing one of these buttons will cause the ALTA to shine infrared light onto the object, a wavelength invisible to our eyes. By pressing these buttons you will be able to measure how much infrared light an object reflects – you will be able to measure invisible light!
Objects can look very different under infrared compared to how they look in the visible parts of the spectrum (natural light). For example, at visible wavelengths snow and clouds look very similar – they both reflect lots of light at all visible wavelengths, and hence look white to us. However, in the infrared part of the spectrum, snow reflects very little light (and appears dark) whereas clouds reflect a lot of radiation (and appear bright). To make use out of the way in which objects on Earth’s surface reflect different amounts of light at different wavelengths, scientists and engineers have designed, built, and launched satellites to make measurements from space. Although the sensors that these satellites use to make these measurements are more complex and expensive than the ALTA II spectrometer, they in fact work in a similar way, exploiting much the same physical principles. After finishing this exercise, you will be able to say, “I know how the satellite collected that image!” the next time you see a satellite image on the television weather report.
1. Turn the spectrometer “on”. Place the spectrometer, lamp side down, on a green leaf so that the lamp and sensor array are over the leaf. Note the display number (given in millivolts) when you are not pressing any buttons on the color switch pad and no ALTA lamps are on (Figures 4 and 5). Record this on Table 1 as the “Dark voltage.” Start with the blue lamp, and turn it on by pushing the blue switch pad button on the ALTA face while continually holding it down. The display number will change from its “dark” value. Initially it will vary a lot, but within a few seconds it will settle down and stop fluctuating so much (the reason you need to hold the button down). There may be some variations in the last couple of digits, but when the display number is fairly constant, record it on the reflectance calculation worksheet in the “Blue” row and “Sample” column. Using the same procedure, work through the rest of the lamp colors on the ALTA, recording all measurements on the data sheet (e.g. cyan lamp, green lamp, yellow lamp, all the way through IR4 lamp).
2. Graph your raw results on the handout “Graph 2: Spectrometer Voltage vs. Color”, where the number you read from the ALTA display goes on the Y axis. Label the curve you produce “Leaf”.
3. Ask your fellow students what their display numbers were for green and infrared-3 (IR3).There will be a lot of variation, even though the leaves should be similar and everyone is using the same spectrometers. The problem is that even if you all looked at the same leaf, the measurements you made using different spectrometers will all be slightly different because you are all using different spectrometers. The problem of variation between different spectrometers also arises when scientists make measurements from space. As such, scientists and engineers go to great lengths to make sure measurements made from different satellites can be directly compared with each other. This is especially important when using satellites to study Earth’s climate. Scientists want to be sure the changes they observe in, for example, sea surface temperatures recorded over a 30 year period, are real and not just due to the use of different sensors on different satellites.
To correct for these differences between instruments and to allow you to more directly compare you results with those of your classmates, measurements of the amount of light reflected by the leaf can be given as the percentage (or proportion) of light reflected by the leaf at each wavelength. One way to measure how much light hits the leaf and how much is reflected is to take reflectance measurements of a standard material, and then compare the amount of light the leaf reflected to the amount that the standard reflected.A standard material is something for which we know (or at least reliably assume) how much light is reflected. Good standards for this experiment are heavy white paper or white poster board, which reflect almost all of the light that hits them. Satellites in Earth orbit also use similar “white standards” although the material used is much more expensive than white poster board. White photocopy paper or notebook paper is decent but not ideal; the paper thinner than white poster board, and allows some light to pass through it.
To measure the reflectance standard, put the spectrometer on the white card and measure the output voltage for each lamp (Figure 5), in the same way you did for the leaf. Write these numbers in the worksheet in the column labeled “Standard White Paper” which can be seen in Figure 6. You’ll notice that while the light measured from the leaf varies a lot with color (with wavelength) the white standard varies much less. A perfect white standard would not vary at all, but your card is a good, and cheap, alternative. Scientists use a white material called “Spectralon” which costs about $350 for a piece the size of a quarter.
Graph your results on “Graph 2: Spectrometer Voltage vs. Color” and label the curve you produce “White standard”. Compare it with your leaf curve.
Figure 5: Spectrometer data collection over white paper.
Figure 6: Data collection worksheet.
4. With the “Standard White Paper” data, you can now calculate the percentage of light reflected by the leaf. For each color, divide the display voltage number for the leaf (minus the dark voltage) by the display voltage number for the white paper (minus the dark voltage), then multiply by 100. Record the value on the worksheet. This value is called the percent reflectance as shown below.
5. Using your results, graph your % Reflectance on the “Percent Reflectance vs. Color” graph. If you were to plot the white card as a standardized reflectance in the same way, you would find that at every color the reflectance would be 100%. Compare this to the “Standard White Paper” curve you plotted on Graph 2. Here the Spectrometer voltage varied with color. This is the purpose of relating the raw spectrometer values for your sample (the leaf) to the white standard; it removes reflectance variations caused by differences in the spectrometers, to leave only those color variations that are due to the chemical properties of the sample.
You have now calculated a reflectance spectrum for a green leaf. You can calculate the reflectance spectrum for other objects (asphalt, pavement, dirt, leaf litter) and compare the results.
In addition to measuring observations on the surface of the earth in the blue, green, red, and near infrared wavelengths (like the Alta II), the Landsat satellite sensor can also record observations in other wavelengths as well (such as thermal bands). Using thermal wavelengths, Landsat sensors are able to assess and map heat differences on the earth’s surface. How might this be helpful to scientists? How could you collect this information?
This website provides in-depth information about the electromagnetic spectrum, radiative physics, and Earth’s radiation budget.
This exercise gives students the chance to learn more about Landsat and explore how different types of radiation affect our ability to interpret the Earth.
A print-friendly version of this exercise can be accessed from here.
STUDENT WORKSHEET: TAKING A REFLECTANCE SPECTRUM
Name: _____________________________________Date: _________________
Partner(s): __________________________________Period: _______________
**Note: Look at the x-axis. A nanometer is one billionth of a meter. To give you an idea just how small a unit of measurement this is, one nanometer is about 1000 times narrower than a human hair. Imagine taking a hair from your head and slicing it, lengthwise, into 1000 pieces. The wavelengths of light in this part of the spectrum (the distance between successive peaks or troughs of the electromagnetic wave) is very, very small indeed.
A print-friendly version of this exercise can be accessed from here.