Use the Data Literacy Cube to guide students’ exploration of data to enrich their observations and inferences. This is a flexible resource that may be used with a variety of graphical representations of data. This activity requires a graph for students to evaluate. Fo
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In this activity, students use satellite images from the NASA Landsat team to quantify changes in glacier cover over time from 1986 to 2018.
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.
In this activity, we will introduce children to the colors of the sky. Children love to look at clouds. Here we will focus in on the sky in which clouds float. Children will learn why the sky has such a wide range of colors.
How much do you know about the frozen poles of our home planet?
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 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.
Compare pictures of different volcanoes. Then visit NASA's Space Place to learn about volcanoes and answer questions about volcanic eruptions.
In this NASA investigation, "What's Hot at the Mall," students examine how shopping malls change natural environments by examining thermal images gathered by NASA showing an area in Huntsville, Alabama.
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.