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.
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Check out the Arctic and Earth SIGNs video to explore how climate models are used in climate change research.
Students will use coloring sheets to create a color coded model of El Niño, then make comparisons using the actual model by answering questions. If the Data Literacy Map Cube is used with this, students will color their models first.
Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.
Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.
This investigation is part of the NASA: Mission Geography Module "What are the causes and consequences of climate change?" that guides students through explorations in climatic variability and evidence for global climate change.
The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.
Students are introduced to the Earthrise phenomenon by seeing the Earth as the Apollo 8 astronauts viewed our home planet for the first time from the Moon. They will analyze a time series of mapped plots of Earth science variables that NASA monitors to better understand the Earth
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, 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.