Teacher's Guide

The fifteenth expedition of the JASON Project is focused on the rainforests of Panama. In January 2004, students, teachers, and scientists will all travel to Barro Colorado Island, Panama, to make measurements of terrestrial vegetation there and to better understand how natural seasonal climate changes as well as human activities may affect the forest there. In support of the expedition, NASA’s Earth Observatory team is pleased to host this four-part exercise to help teachers and students learn about satellite remote sensing and how scientists use the unique vantage point of space to observe and measure plants.

Exercise 1: The Electromagnetic Spectrum

After reviewing the on-line primer, have your students build true- and false-color images using Landsat multi-spectral data. Bands 3, 2, and 1 correspond to red, green, and blue, respectively--selecting this combination of bands will make true-color image. You will notice that the composite in ICE appears rather dark. This is because much of the light at those wavelengths are scattered and absorbed by gases and particles in the atmosphere, thus diminishing the brightness and clarity of the signal that is actually reflected at the surface. Students can “correct” the true-color composite image by toggling the red, green, and blue sliders beneath each band. Have them experiment to see if they can make the image look “natural color” to their eyes.

Answers to “Questions to consider”:

What features seem to be more prominent, or brighter, in each of the visible (red, green, and blue) bands? What features appear less prominent, or darker? Why do you think so?

The waters of Lake Gatun as well as the Atlantic (upper left) and Pacific (lower right) appear the darkest. This is because things in the water tend to absorb light and reflects very little, primarily in the blue band. However, water can become more reflective when there are increasing amounts of organisms or sediments near the surface. Depending upon its content, water reflects most strongly in the blue (and sometimes green) band. If you look carefully, you will see some stretches of the Panama Canal that appear to have near-surface sediments.

The forest canopy is a little brighter than the water in the visible bands. While it also strongly absorbs most visible light, it reflects primarily green light. Bare land surfaces and cities are the most reflective surfaces in the region and therefore appear as the brightest features.

Please note that each of the individual visible bands appear rather dark on the screen. This is because those wavelengths of energy must travel through the atmosphere on their way up to the satellite sensor. During this trip, some of the light gets absorbed or scattered by gases and particles in the air. Use the sliders under each of the red, green, and blue thumbnails to “stretch,” or increase, the brightness for each of those bands. Shifting the red and green sliders to the left by about 75%, and the blue slider by about 60%, results in an image composite that appears “natural color.”

Now select various combinations of visible and infrared bands to see which combination offers to best contrast between water, vegetated land surface, and human-developed land surface. Which band combination seems to work best, and why? (Note: If you experience problems with ICE you may need to clear your Web browser’s “cache” after each composite that you build.)

Scientists often use Landsat bands 4, 3, and 2 (as red, green, and blue, respectively) to make false-color images that give good contrast between vegetated land surfaces, bare or urbanized land surfaces, and water. In this combination, heavily vegetated areas appear burgundy or bright red, bare or sparsely vegetated land surface appears brown, cities look blue-gray, and water is black. Vegetation very strongly reflects near-infrared bands, whereas water very strongly absorbs them.

Another interesting Landsat band combination to try is 7, 4, and 2 (as red, green, and blue, respectively). The resulting false-color image again shows water as black, vegetated land surface as bright green, bare land surfaces and urban areas as reddish brown. While this combination gives good contrast between some features (and green is a more intuitive representation of vegetation), it is hard to distinguish between urban areas and bare land surface areas.

Students may find that Landsat bands 7, 5, and 1 (as red, green, and blue, respectively) offers the best, most intuitive false-color combination. This composite image has good contrast between all of the various surface types. Forests are dark green, sparsely vegetated and bare land surfaces are light green, urban areas are blue-gray, and water is dark blue.

Exercise 2: Mapping Vegetation with NDVI

After reviewing the on-line primer with your students, have them take note of the formula for making an NDVI (Normalized Difference Vegetation Index) image using the Image Composite Editor. You can tell them, or let them discover from the primer, that they must use Landsat bands 4 and 3 to make the vegetation index. Upon selecting bands 4 and 3 (as channels 1 and 2, respectively) and clicking “build,” the ICE tool will display those bands in the first two thumbnails and the result of them added together in the third thumbnail. This is half of the NDVI formula already prepared. Now, to complete the operation, students should change the math operation from “add” to “subtract” under the first two thumbnails. (Be careful to leave the numbers set at “1.0” as it is a multiplying coefficient that describes how much of the values in each thumbnail ICE should compute. Leaving it set at 1.0 means “1 times the brightness values currently displayed.”) Next, change the pop-down menu between the second and third thumbnails to “divide” and change the number in the window beneath the third window to “1.0.” After checking to make sure everything is set properly, click “Compute.” In short, you have just used the ICE math tool to compute the result of band 4 minus band 3 divided by band 4 plus band 3. The result is the greenness index value that scientists call NDVI.

Answers to “Questions to consider”:

1. Do you see any differences in the features of the tree in the red and near-infrared photos above? Explain any differences you see and what makes them look different.

These are two images of the same tropical forest tree, as seen looking down from above. This tropical tree is leafless in the dry season (like forests in North America that lose their leaves in the winter), so only the branches are left. Below this leafless tree is a shorter tree that is full of leaves. In the red band, the fully leaved tree below absorbs red light and the wood from the leafless tree above reflects red light. In the infrared band, the fully leaved tree below reflects a lot of light, much more than the bare branches above.

2. How is the way a satellite sees Earth’s vegetation similar to the way our eyes see it? How is it different?

Like our eyes, satellites "see" the green light reflected by chlorophyll in plants, but unlike our eyes, satellites can also "see" the infrared radiation reflected by plants.

3. What kind of “spectral signature” would you expect a rainforest to reflect back to the satellite? Would it have a high NDVI value or a low NDVI value? Explain why you think so.

A rainforest has a lot of green leafy vegetation, and vegetation absorbs almost all wavelengths of visible light while reflecting infrared radiation. Therefore a rainforest would reflect very little visible light back to the satellite and a lot of infrared. This combination of low visible light and high infrared would produce an NDVI value near the top of the NDVI scale.

4. Would the NDVI value of the Panama Rainforest be higher or lower than vegetation in a state park near where you live?

Answers will vary, of course, depending on where the students live. But as a general rule it will be less, unless students live in or near other tropical forests.

Exercise 3: Limits to Plant Growth

Review the on-line primer with your students and then ask them to review the global-scale movies of solar insolation (or exposure to sunlight at the surface), temperature, and rainfall. Each frame in these movies represents a 1-month average for the month indicated in 2001. Invite your students to notice how the pattern of each variable changes through the course of the year. The changes are usually most extreme at the higher latitudes in the Northern and Southern Hemisphere, while the measurements or more consistent year round near the equator.

Now focus upon the tiny isthmus of Panama. How do conditions change for that region over the course of the year? In January, February, and March, there is good exposure to sunlight and temperatures remain warm, but there is relatively little rainfall. This is the “dry” season and the lack of rain is a limit to plant growth during this time of year. As a result, many of the deciduous trees in Panama shed their leaves at this time. From April through December, the insolation value for the Panama region appears to go down noticeably because rain clouds are almost constantly forming there during this span. The temperatures remain fairly steady. So conditions are ideal for plant growth during this time.

Based upon these global-scale movies of rainfall, surface temperature, and insolation, make a chart of the values for each of these factors for each month of the year. When do you think is the best time of the year for plants to grow in Panama? When do you think is the worst time?

From January through March, conditions are probably too hot and dry for much plant growth. The lack of water during this span causes many deciduous trees to shed their leaves. By May of that year the seasonal rains had returned and remained fairly constant through December. At this spatial resolution (1 degree per pixel) it is hard to see much detail about Panama. Students may pick any month from May to December as the best time for plant growth. The main point here is for them to support their answer with the evidence that they gather.

Which of these limits to growth is the most important for the plants in Panama? Why do you think so?

Insolation is the most important limit to growth for plants in Panama. Because Panama is cloudy almost all year round, plants are limited in their exposure to sunlight and therefore in their ability to photosynthesize. This is particularly true during the rainy season, when thick rainclouds block much of the incoming sunlight.

Rainfall is probably the second most important limiting growth factor for plants in Panama. From January into March there is very little rainfall, whereas the insolation and temperature values remain fairly high during this time.

Temperature is fairly stable and plenty warm enough for plant growth all year round, and so it is the least important factor in Panama.

Do you think this Jason Expedition is taking place during the high or low growing season?

Jason XV is taking place in late January and early February, right smack in the middle of the dry season. So there will likely be relatively little plant growth during this time and students will observe many deciduous trees have shed their leaves.

Exercise 4: Vegetation Vital Signs

Review carefully the on-line primer, first by yourself and then with your students. Five different land surface measurements are introduced. There are textual descriptions of each measurement as well as thumbnail images showing what they look like. You can click each thumbnail to view larger versions with color palettes. Have your students read each description and examine the images, and then provide their own answers to the questions given for each.

Leaf Area Index Questions:
1. Which has a greater leaf area, a rainforest or a grassland?

In general, a rainforest has many more layers of leaves than a grassland, so its leaf area index value will be higher.

2. What can leaf area tell us about the vegetation in an ecosystem that NDVI cannot?

Leaf area can indicate the density of green foliage in an ecosystem, whereas NDVI cannot. The latter measure is an indication of the “greenness” of an ecosystem.

How is leaf area related to NDVI?

During the peak growing season, leaf area will affect the greenness of a scene. The greater the leaf area, the higher the NDVI value is likely to be.

Absorbed Sunlight Questions:
1. Rates of photosynthesis in vegetation can be slowed down by lack of water, cold temperatures, and lack of sunlight. Which of these factors do you think most influences vegetation in the rainforests of Panama? Why do you think so?

Rates of photosynthesis in the rainforests of Panama are slowed by limited exposure to sunlight due to the heavy cloud cover during much of the year, and lack of water in the dry season. In the “dry” season—January, February, and into March—there is less cloud cover and more exposure to sunlight. However, there is much less rain and so less water is available. Also, the dry season is the time of year when many deciduous trees in the region shed their leaves, which also lowers net photosynthetic activity. The temperature in Panama is warm and stable fairly year round, so temperature is the least limiting of these factors.

Questions for Taking the Tropics’ Temperature, Day and Night:
1. Do you see any relationship between either day or night time temperature and the net photosynthesis (absorbed carbon)?

Have your students refer to the rollover at the bottom of the page for visual correlation. Also, they can use the ICE tool to correlate these two measurements, by selecting them in the pop-down menus below the rollover. In the ICE window, instruct your students to click "Select Region" and then click and drag their cursor on the large window. Next, click on the thumbnails of any two of the measurements shown and then click "Scatter" to make a scatter plot. Refer to the section on Scatter Plots in the ICE User’s Guide to learn more about making and interpretting scatter plots.

There appears to be no correlation with nighttime temperatures and carbon absorption. There appears to be a positive correlation between daytime temperature and carbon absorption—the warmer the temperature the more carbon gets absorbed. But is this true only up to a point! If temperatures get too hot, the plants will stop photosynthesizing and start to wilt (which sometimes happens during the dry season).

2. Do you see any relationship between land surface temperature and land cover type?

Vegetation tends to keep daytime temperatures down in hot areas. As a general rule, across a region where the amount of incident sunlight is the same, vegetated areas will be cooler during the day than less vegetated areas. This is apparent when using the roll-over to compare land surface temperature and land cover type. However, there appears to much less of a relationship between night time temperature and land cover type.

3. Why would urban areas not cool off as much at night as an area with natural vegetation? (*Hint: Imagine walking barefoot across a blacktop asphalt parking lot on a hot summer day.)

Black asphalt and concrete absorb the sun’s light during the day and re-radiate its heat, especially at night. Compared to surrounding areas of natural vegetation, urban areas are usually warmer at night. Scientists have named this the “urban heat island effect.” Unfortunately, at the resolution of these images (1 kilometer per pixel) it is difficult to see this effect.

Questions for An Ecosystem’s Net Productivity:
1. Compare Panama’s plant productivity for different times of the year. Do you see any differences? When do you observe the greatest productivity? When do you observe the least productivity?

While the plants in Panama are productive year-round, their period of greatest productivity is during the rainy season. The plants are less productive during the dry season.

2. Which land cover type has the biggest change in productivity between the wet and dry season?

3. Why do you think plant productivity in Panama changes over the course of the year?

The three main factors that limit plant growth are access to sunlight, water, and temperature, in that order. Since Panama is located very near the equator, the temperature there is warm and suitable for plant growth year round. Access to both water and light are the mainly limits to plant productivity in Panama—water in the dry season and light in the rainy season. Using the ICE tool, when you compare plant productivity (absorbed carbon) in February 2003 to July 2003, you will find slightly higher values during the dry season due to the greater exposure to sunlight.

Questions for Mapping Land Cover Types:
1. What land cover types do you observe across Panama? Which is the most widespread? Which is the least widespread?

Evergreen broadleaf forest is the most widespread land cover type in Panama (bright green). Croplands are the second most widespread land cover type (tan). The least widespread land cover type appears to be urban areas (red).

2. Compare Panama’s leaf area index map to the land cover map. Which land cover types show the greatest leaf area? Which show the least leaf area?

The evergreen broadleaf forests show the greatest leaf area, according to these Terra maps. The urban areas, savannah regions, croplands show the least leaf area.

3. Compare Panama’s plant productivity map to the land cover map. Which land cover types show the greatest productivity? Which show the least productivity?

During the months chosen for this lesson (February and July 2003), the areas of greatest plant productivity occur in the evergreen forest regions. The areas of lowest productivity are in the urban areas and the croplands. However, during the peak of the crop growing season, productivity in croplands can be as high or even higher than the rainforest.

Comparing these land surface measurements using ICE

You might begin by instructing students to compare measurements taken during February 2001 (the dry season) to measurements taken during July 2001 (the wet season). Once any two of these measurements are displayed in the ICE tool, you can compare the two either by clicking the thumbnail to choose which to display in the large window and then clicking “Probe.” Now, passing your cursor over the large image reveals the unit value for each pixel, for both of the thumbnail images. This way, you can compare the two scenes on pixel-by-pixel basis.

Alternatively, try clicking “Plot Transect” and then clicking and dragging your cursor anywhere on the large image to make a line segment. A new window will open displaying a line graph of the values for every pixel along the line segment, for both scenes. This way, students can quickly compare the values across transects of the landscape for both times of the year.

Teachers might also invite students to use the “Scatter” plot tool in ICE to see if there is a relationship between any of these measurements. For instance, select “Absorbed Sunlight,” “Leaf Area Index,” and “Absorbed Carbon” for February 2001. Pick a region of interest within Panama by hitting “Select Region” and then clicking and dragging anywhere on the large image to draw a box. Then hit the “Scatter” button. NOTE: If no specific thumbnails are selected, then ICE will choose the first two thumbnails by default. To compare, say, the first and third thumbnails, click on each of them both before hitting the “Scatter” button.

If you do not know how to interpret scatter plots, please refer to the ICE User’s Guide.

Additional Slides as Needed (Microsoft PowerPoint files)

  • Introduction to Remote Sensing (5.83 MB)
    This presentation is an overview of remote sensing, what it is, why we use it, and how it works. Slides include the definitions of common remote-sensing terms, and examples of images captured by different remote sensing instruments. The presentation also highlights key steps in the history of remote sensing and ends with a spectacular global image of the Earth’s surface combined with ocean temperatures, both of which were captured by the MODIS sensor on the Terra satellite.
  • Leaf Reflectance (3.02 MB)
    This presentation addresses how and why vegetation interacts with sunlight the way it does, and how that interaction determines what a satellites “sees” when it looks at vegetation. The presentation includes examples of how vegetation looks different in different parts of the electromagnetic spectrum, and how using “invisible” parts of the spectrum can distinguish vegetated from non-vegetated surfaces as well as one type of vegetation from another. The presentation also includes brief discussion of photosynthesis, including schematic drawings of the process and structures involved, as well as graphs showing the range of sunlight that best drives the process.
  • The Human Eye (1.33 MB)
    This presentation briefly summarizes the main characteristics of the human eye and vision, and makes comparisons to the vision of other creatures. It includes electron micrograph images of the structures of the eye, as well as graphs that illustrate the link between our vision and the energy output of the Sun.