This lesson is designed to help students analyze the interaction between different cloud heights and Earth's incoming and outgoing energy.
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Carbon dioxide concentration in the atmosphere is affected by many processes including fires, deforestation, and plant respiration. Students will evaluate a Landsat image to determine the rate of carbon dioxide sequestration in a particular area.
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.
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 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 describe how the spread of COVID-19 is affected by population density and explain why patterns in the spread of COVID-19 are happening over time.
Students watch a NOVA PBS video about the different effects of clouds on climate and Earth's energy budget. Then they answer questions and brainstorm to complete a flow chart of events that might occur if the percentage of absorbing clouds increases.
The Earth System Satellite Images, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships for a specific variable, identify patterns, and determine relationships among variables over one year.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner determine relationships among variables.