NASA visualizers take data – numbers, codes – and turn them into animations people can see and quickly understand.

Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.

The Earth System Poster activity walks learners through global patterns and illuminates how each of the spheres is interconnected across the world. We will divide into small groups to look at maps of different parts of the earth system that have been observed by NASA satellites.

Students analyze the stability and change of sea level after watching a visualization of sea level height around the world. 

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.

In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008

Learners will analyze and interpret a box plot and evaluate the spread of the data. Learners will compare it with a different visualization of the data to see how the two compare, discuss the limitations of the two types of data displays and formulate questions.

Learn about volcanic ash and watch a visualization of the Calbuco volcano to see how ash travels around the world. 

Interpret a scatter plot to find patterns in the number of tropical cyclones from 1842 to 2018.

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.