Students will identify and describe the relationship between watersheds and phytoplankton distribution.
Educational Resources - Search Tool
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)
Teachers, are you looking for resources to help you engage students in data analysis related to the Urban Heat Island in North America?
Check out the images featuring two science variables related to Urban Heat Islands: Monthly Surface Air Temperature (degrees Celsius) & Monthly Daytime Skin Temperature (degrees Celsius).
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.
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.
By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.