Students watch a short video to gather information about sources of methane emissions and then extend their understanding of these sources to evaluate monthly trends in the Alaska region, ultimately making connections to Earth’s energy budget.

This StoryMap allows students to explore the urban heat island effect using land surface temperature and vegetation data in a 5 E-learning cycle. Students investigate the processes that create differences in surface temperatures, as well as how human activities have led to the creation of urban heat islands. 

My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.

This graphic organizer may be used to help students analyze the processes and components of Earth System phenomena.

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

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.  

The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.

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

Teachers, are you looking for resources to help you engage students in data analysis related to Global Phytoplankton Distribution?

Check out the monthly 2018 images featuring two science variables related to Phytoplankton Distribution: Chlorophyll Concentration (milligrams per cubic meter)  & Monthly Flow of Energy into Surface by Shortwave Radiation (watts per square meter)

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