The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships, identify patterns, and determine relationships among variables.  

Students can interact with NASA data to build a custom visualizations of local, regional, or global plant growth patterns over time, using the Earth System Data Explorer to generate plots of satellite data as they develop models of this phenomenon.

Learners follow adventurous camper, Awenasa, as she travels the United States and attends various camp locations throughout the year.  Learners analyze data to find her location among the various campsites using monthly averaged NASA satellite data (Cloud Coverage, Surface (S

Explore and connect to biosphere protocols in GLOBE. Each protocol has related Earth System Data Explorer datasets identified, as well.

Students will analyze a line graph that shows how the surface temperature and air temperature values change over the course of 24 hours.

This mini lesson engages students by watching a NASA video related to plant growth activity around the world using data from the NASA/NOAA Suomi NPP satellite and answering questions on these stability and change relationships.

The Earth's system is characterized by the interaction of processes that take place on molecular (very small) and planetary (very large) spatial scales, as well as on short and long time scales. Before scientists may begin their work with these data, it is important that they understand what the data are.

Explore and connect to protocols in GLOBE related to the cryosphere. Each protocol has related Earth System Data Explorer datasets identified as well.

The Earth System Satellite Images help students observe and analyze global Earth and environmental data, understand the relationship among different environmental variables, and explore how the data change seasonally and over longer timescales.