Students will engage in a “Zoom In Inquiry” learning routine to understand a world map that shows changes in PM_2.5-attributable mortality per 100,000 population (Bondie, 2013).

Students explore albedo, sea ice, and the relationship between changing albedo and changing sea ice using data visualizations. 

Students will identify and describe the relationship between land cover classification and surface temperature as they relate to the urban heat island effect. Students will also describe patterns between population density and the locations of urban heat islands. 

Students visit a NASA Website called "Eyes on the Earth" to view satellite missions in 3D circling the Earth and learn to navigate to specific satellites to learn about their capability of analyzing our changing planet and air quality.

Students watch videos and/or review articles related to particulate matter and how this pollutant is monitored and measured, then provide their understanding individually or in groups.

Students categorize causes, effects, and responses to volcanic hazards through an Earth system perspective. They use remotely sensed images to examine the visible effects of the eruption of Mount St. Helens in 1980 and identify a buffer zone for safer locations for development.

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.

The ocean's surface is not level, and sea levels change in response to changes in chemistry and temperature. Sophisticated satellite measurements are required for scientists to document current sea level rise.

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.

Students compare climographs for two locations to determine the most likely months to expect the emergence of mosquitoes in each location.