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 will engage in a collaborative learning routine as they explore slides that show how the development of public transportation infrastructure changed the land in Woodlawn, Maryland. They will make observations of a satellite image and a photo from the ground as well as read background information on the impact of urbanization. 

This mini lesson focuses on Landsat satellite data and how it is used to detect changes in land use. Students will answer questions based off of a NASA Video that features how Landsat data are interpreted in the forests of the Pacific Northwest, and gives examples of the effects insects and logging have with land management.

Students will synthesize information from maps that show population, concentrations of PM_2.5, and PM_2.5-attributable mortality across the globe in order to draw conclusions about the relationship between particulate pollution and human health. 

Students observe how air quality changes over time, for a selected location, using data from the United States Environmental Protection Agency (EPA).

Students will make a claim about whether changing albedo contributes to changes in Arctic habitats.

Students analyze Landsat images of Atlanta, Georgia to explore the relationship between surface temperature and vegetation.

In this mini lesson, students analyze a bar graph showing the relative forcings from natural and human factors that affect Earth's climate. They use information from this graph to assess the relative importance of these factors.

Carbon dioxide concentration in the atmosphere is affected by many processes including fires, deforestation, and plant respiration. Students will evaluate a Landsat image to determine the rate of carbon dioxide sequestration in a particular area.

Students will describe how the spread of COVID-19 is affected by population density and explain why patterns in the spread of COVID-19 are happening over time.