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.

Students will identify and describe the relationship between land cover classification and surface temperature as they relate to the urban heat island effect. Students will also describe patterns between population density and the locations of urban heat islands. 

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. 

In this lesson, students will explore the effect of aerosols on sky color and visibility by using an interactive virtual model. 

Students interpret AQI maps and charts to compare today’s AQI with the past five days. Using the EPA’s air quality activity guides, students create a social media post for residents of their region providing key information related to today’s AQI.

Students analyze diagrams showing the effects of clouds on Earth’s Radiation and answer the questions that follow. This mini lesson is designed to help students analyze the interaction between clouds and Earth's incoming and outgoing energy. 

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

Students will observe monthly satellite data of the North Atlantic to identify relationships among key science variables that include sea surface salinity (SS), air temperature at the ocean surface (AT), sea surface temperature (ST), evaporation (EV), precipitation (PT), and evaporation minus pre

NASA Worldview is a free online visualization tool that is a great launchpad for learners who are new (or veteran) users of satellite data.

This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.