Analysis & Application of Seasonal Vegetation Data: Student Activity
Directions: Students will observe seasonal maps of Monthly Normalized Difference Vegetation, known as NDVI - a measure of the "greenness" of Earth's landscapes and match to four different months of 2017. These maps will be offered in the Google Slide deck or in handouts provided by your teacher.
Teachers: The images can be downloaded, printed, and distributed in a Face-to-Face setting, along with the questions below. Alternatively, virtual learners will need to access the Google Slide to view the maps.
You will analyze these data for any changes in vegetation that are occurring throughout the year.
The colors on this maps show a measure of the "greenness" of Earth's landscapes. The values on these maps—ranging from -0.1 to 0.9—have no unit. Rather, they are index values in which higher values (0.4 to 0.9) show lands covered by green, leafy vegetation and lower values (0 to 0.4) show lands where there is little or no vegetation.
The vegetation maps (Images A-D) were created to represent the following time periods: February 2017, June 2017, October 2017, and December 2017 but are not in order. Match the maps with their corresponding months from 2017 based on your observations. For example, Map X = February 2017, etc.
Identify the seasonal cycles for vegetation throughout the year by answering the following questions.
What changes do you see through the year?
Choose a location or region. During which months do the extreme highs and lows occur? What explanations can you suggest for the timing of those extremes?
Which regions experience both the extreme highs and lows? Which regions don’t experience the extremes? Why do you think this happens?
As can be seen through a prism, many different wavelengths make up the spectrum of sunlight. When sunlight shines on objects, certain wavelengths are absorbed and other wavelengths are reflected. The pigment in plant leaves—chlorophyll—strongly absorbs visible light for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light. The more leaves a plant has, the more these wavelengths of light are affected. Scientists exploit this knowledge of plants' interactions with light to map the density of green vegetation across Earth's landscapes by designing satellite sensors to measure the wavelengths of red and near-infrared light that is absorbed and reflected by plants all over the world.
Subtracting plants' reflectance of red light from near-infrared light and then dividing that difference by the addition of the red and near-infrared light reflected produces a resulting value that scientists call Normalized Difference Vegetation Index (NDVI). The NDVI maps shown here were made using data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra satellite.
Plants are sensitive to their environment and so they serve as a good indicator whenever there is a change. Scientists routinely produce global NDVI maps to help them monitor and investigate shifts in plant growth patterns that occur in response to climate changes, environmental changes, and changes caused by humans. Farmers and resource managers also use NDVI maps to help them monitor the health of our forests and croplands. So these maps are used both for scientific research as well as societal benefit.
Teachers, these mini lessons/student activities are perfect "warm up" tasks that can be used as a hook, bellringer, exit slip, etc.
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Supported NGSS Performance Expectations
- 4-ESS2-2: Analyze and interpret data from maps to describe patterns of Earth’s features.
- MS-ESS2-1: Develop a model to describe the cycling of Earth's materials and the flow of energy that drives this process.
- HS-ESS2-4: Use a model to describe how variations in the flow of energy into and out of Earth’s systems result in changes in climate.
- HS-ESS2-2: Analyze geoscience data to make the claim that one change to Earth's surface can create feedbacks that cause changes to other Earth systems.