Students identify and classify kinds of land cover (such as vegetation, urban areas, water, and bare soil) in Landsat satellite images of Phoenix, Arizona taken in 1984 and 2018.
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Students watch videos and/or review articles related to particulate matter and how this pollutant is monitored and measured, then provide their understanding individually or in groups.
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.
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 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.
Guided by the 5E model, this lesson allows students to work together to uncover how changes in sea ice extent in the Arctic and Antarctic regions are connected to Earth’s energy budget.
This interactive guides students through exploring how stars create the elements that make up the universe and life itself. Students will be able to identify the key elements in their bodies that were created from exploding stars.
The Urban Heat Island Implementation Sequence provides a series of lessons and activities for students to learn about the processes that create differences in surface temperatures, as well as how human activities have led to the creation of urban heat islands.
Students analyze the data and details of a complicated graph by identifying components and data patterns.
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.