This story map 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 story map lesson plan allows students to explore ocean circulation patterns as they relate to the world's ocean garbage patches using NASA ocean currents data. Students will investigate the forces that contribute to ocean circulation patterns, and how debris, especially plastics, travel from land to the garbage patches. 

This story map lesson plan allows students to explore global phytoplankton distribution using chlorophyll concentration data in a 5 E-learning cycle. Students will investigate the processes that allow phytoplankton populations to thrive, as well as how their role in the carbon cycle impacts the other spheres of the Earth System. 

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 Quick Start Guide lists examples of NASA datasets and imagery that could be used for student investigations related to content and practices in the Framework for K-12 Science Education.    This Guide is part of an educator toolkit that features resources for grades K-12 that can support and frame student investigations with NASA data and content. Check out the toolkit and samplers for elementary, middle, and high school at https://www.strategies.org/education/educators-toolkit/.

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

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.