In this activity, students use satellite images from the NASA Landsat team to quantify changes in glacier cover over time from 1986 to 2018.
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In this activity, you will use an inexpensive spectrophotometer* to test how light at different visible wavelengths (blue, green, red) is transmitted, or absorbed, through four different colored water samples.
Students analyze the relationship between sea surface height and ocean surface currents by graphing sea height using satellite data. Note: This lesson is modified from NASA's TOPEX/Poseidon lesson plan.
Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.
Students review Earth System phenomena that are affected by soil moisture. They analyze and evaluate maps of seasonal global surface air temperature and soil moisture data from NASA satellites. Building from their observations, students will select a location in the U.S.
Students identify and classify kinds of land cover (such as vegetation, urban areas, water, and bare soil) in Landsat satellite images of Phoenix, Arizona taken in 1984 and 2018.
Students will investigate the role of clouds and their contribution (if any) to global warming. Working in cooperative groups, students will make a claim about the future role clouds will play in Earth’s Energy Budget if temperatures continue to increase.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
The extreme temperatures during July 2022 prompt students to investigate a model that displays historical heat wave frequency data to discover the importance of defining terms when interpreting data.