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. 

Students will describe the changes in a newly-formed volcanic island over the first three years of its life.  

Examine the images to see the projected differences in land use between 1900 and 2100. 

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.

Arctic sea ice is the cap of frozen seawater blanketing most of the Arctic Ocean and neighboring seas in wintertime. It follows seasonal patterns of thickening and melting. Students view how the quantity has changed from 1979 through 2018. 

The fires in Greece during the summer of 2007 devastated large tracks of forest and ground cover in this Mediterranean region. Students analyze these data to determine the scale, area, and percentage of the forest impacted by of these fires.

Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.

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.

This activity will help students better understand and practice estimating percent cloud cover.

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.