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. 

Students analyze historic plant growth data (i.e., Peak Bloom dates) of Washington, D.C.’s famous cherry blossom trees, as well as atmospheric near surface temperatures as evidence for explaining the phenomena of earlier Peak Blooms in our nation’s capital.

After learning about the different characteristics of satellite data, students will describe the advantages and disadvantages of using two different satellites to study the Urban Heat Island Effect.  

Students will analyze how surface (skin) temperatures vary across a community and determine what factors contribute to this variation. Students will describe how human activity can affect the local environment. 

Students review a video that models the global impact of smoke from fires to develop an understanding of how models can be used to interpret and forecast phenomena in the Earth System. 

Examine the images to see the projected differences in land use between 1900 and 2100. 

This StoryMap allows students to explore the formation and impacts of ash and aerosols from volcanic eruptions around the world in a 5 E-learning cycle. They will investigate how ash and aerosols produced from volcanic eruptions are hazardous to the human ecosystem, and will analyze concentrations of aerosols from a volcanic eruption over time. 

This StoryMap 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. 

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.

Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.