The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.

The purpose of this activity is to have students use an Earth Systems perspective to identify the various causes associated with changes to Earth's forests as they review Landsat imagery of site locations from around the world.

This activity is modified from the USDA/US Forest Services' lesson found in the Natural Inquirer newsletter.  The purpose of this hands-on activity is to engage students in a similar process for monitoring forests as NASA scientists use to study the Biosphere, whereby they apply what they kn

This activity invites students to model and observe the effect of melting ice sheets (from land) on sea level and the difference between the effect of melting sea-ice to that of melting land ice on sea level.

This lesson is taken from NASA's Phytopia: Discovery of the Marine Ecosystem written in partnership with Bigelow Laboratory for Ocean Science with funding from the National Science Foundation.

To investigate the different rates of heating and cooling of certain materials on earth in order to understand the heating dynamics that take place in the Earth’s atmosphere.

Conduct this EO Kids mini-lesson with your students to explore the phenomenon of Urban Heat Island Effect.

Students develop and test a hypothesis about how albedo affects temperature.

The Great Smoky Mountains have a unique climate and weather pattern. Students will review a Landsat image and read about the history of the area and why Native Americans called the area “Shaconage.” Then they will answer the questions about what caused the unusual “blue smoke.”

Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.