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. 

This activity was developed by NASA's Global Precipitation Measurement (GPM) team as an introductory experience to a series of lessons about water resources on Earth.

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

Students are introduced to the Earthrise phenomenon by seeing the Earth as the Apollo 8 astronauts viewed our home planet for the first time from the Moon.  They will analyze a time series of mapped plots of Earth science variables that NASA monitors to better understand the Earth

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

Students learn how to estimate the "energy efficiency" of photosynthesis, or the amount of energy that plants absorb for any given location on Earth. This is the ratio of the amount of energy stored to the amount of light energy absorbed and is used to evaluate and model photosynthesis efficiency.

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.

Students will analyze a pie chart (circle graph) showing the distribution of different parts of the Earth system's absorption and reflection of energy. 

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.