This series of videos highlights how NASA Climate Scientists use mathematics to solve everyday problems. These educational videos to illustrate how math is used in satellite data analysis.
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In this activity, students use satellite images from the NASA Landsat team to quantify changes in glacier cover over time from 1986 to 2018.
Because it recognizes the importance of U.S. coastal areas to the nation's economy, the U.S. National Ocean Service has formed a task force that is studying the trends and impacts of hurricanes on coastal regions. They have invited your students to participate.
Students use albedo values of common surfaces along with photographic images of Earth taken from the International Space Station to make an argument about specific anthropogenic activities that impact Earth’s albedo.
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 move through a series of short activities to explore and evaluate global solar radiation data from NASA satellites. In this process, students make qualitative and quantitative observations about seasonal variations in net energy input to the Earth System.
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.
Students are introduced to the Earthrise phenomenon by seeing the Earth as the Apollo 8 astronauts viewed our home planet for the first time from the Moon. They will analyze a time series of mapped plots of Earth science variables that NASA monitors to better understand the Earth
Students will examine a 2014-2015 El Niño Southern Oscillation (ENSO) event to identify relationships among sea surface height, sea surface temperature, precipitation, and wind vectors.
This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.