This investigation introduces students to the significant environmental changes occurring around the world. The investigation uses NASA satellite images of Brazil to illustrate deforestation as one type of environmental change.

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.

This content has been moved. You can find it under Creation of Urban Heat Islands Story Map link.

Students will analyze the mapped plot of the historic Ocean Chlorophyll Concentrations at key locations around the world for the period of 1998-2018.

Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.

This resource collection models for you (and your students) the process of analyzing solar radiation and phytoplankton data collected by satellites in the Arctic waters. 

The Great Smoky Mountains have a unique climate and weather pattern. Students will review a Landsat image and read about the history of the area and why Native Americans called the area “Shaconage.” Then they will answer the questions about what caused the unusual “blue smoke.”

Students visit a NASA Website called "Eyes on the Earth" to view satellite missions in 3D circling the Earth and learn to navigate to specific satellites to learn about their capability of analyzing our changing planet and air quality.

Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.

These resources are intended to be used with teachers and students to help model how to apply data literacy skills to analyzing patterns as they relate to stability and change in COVID-19 (and related human geographic) and nitrogen dioxide data.