Use the Data Literacy Cube to guide students’ exploration of data to enrich their observations and inferences. This is a flexible resource that may be used with a variety of graphical representations of data. This activity requires a graph for students to evaluate. Fo
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This activity is one of a series in the collection, The Potential Consequences of Climate Variability and Change activities.
Students observe seasonal images of Monthly Leaf Area, looking for any changes that are occurring throughout the year.
The Earth System Poster activity walks learners through global patterns and illuminates how each of the spheres is interconnected across the world. We will divide into small groups to look at maps of different parts of the earth system that have been observed by NASA satellites.
The purpose of this activity is to have students use an Earth Systems perspective to identify the various causes associated with changes to Earth's forests as they review Landsat imagery of site locations from around the world.
In this NASA investigation, "What's Hot at the Mall," students examine how shopping malls change natural environments by examining thermal images gathered by NASA showing an area in Huntsville, Alabama.
This Lesson Plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because this is a differentiated resource, it is appropriate for multiple grade bands.
This lesson, "Awenasa Goes to Camp!," is a data analysis activity that presents maps of NASA Earth satellite data for a variety of locations across the United States for four unidentified months throughout the year. Each location represents a real science camp th
This lesson plan provides some generic maps, graphs, and data tables for use with the Data Literacy Cube. Because it is a differentiated resource, this lesson plan is appropriate for multiple grade bands.
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.