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 observe seasonal images of Monthly Normalized Difference Vegetation, looking for any changes in vegetation that are occurring throughout the year. They put the images in order based on what they know about seasonal changes.

Students will analyze and interpret graphs to compare the flow of (shortwave) energy from the Sun toward China over the course of a year on cloudy versus clear days. Students will draw a conclusion and support it with evidence.

This mini lesson engages students by watching a NASA video related to seasonal chlorophyll concentration as it relates to net radiation using NASA's Aqua satellite. Students will examine the model and answer the questions.

This lesson is designed to help students analyze the interaction between different cloud heights and Earth's incoming and outgoing energy. 

Students watch a video and answer questions on Dr. Patrick Taylor (Atmospheric Scientist, NASA Langley Research Center) as he discusses the study of clouds and Earth's energy budget by analyzing data from Low Earth Orbit satellites. 

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 Lesson Plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because this is a differentiated resource, it is appropriate for multiple grade bands.

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. 

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.