This unit plan is published by the NASA Climate Change Research Initiative's (CCRI) Applied Research STEM Curriculum Portfolio. The CCRI Unit Plan, called “Urban Surface Temperatures and the Urban Heat Island Effects,“ has the purpose to educate students how climate is changi
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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.
The Earth System Satellite, help the learner visualize how different Earth system variables change over time. In this lesson, students will graph six points for a location over one year.
The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships, identify patterns, and determine relationships among variables.
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.
In this story map students will learn about the different components of the Earth's Energy Budget, where in the Earth System energy is being absorbed and reflected, and how features of the Earth such as clouds, aerosols, and greenhouse gases, can cause variations in the flow of energy into and out of Earth Systems. In the final section, students make a claim as to why the Earth's Energy Budget is currently out of balance and provide evidence to support their reasoning.
This lesson walks students through the use of Landsat false-color imagery and identification of different land cover features using these as models.
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.