This activity is one of a series in the collection, The Potential Consequences of Climate Variability and Change activities.
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This activity is modified from the USDA/US Forest Services' lesson found in the Natural Inquirer newsletter. The purpose of this hands-on activity is to engage students in a similar process for monitoring forests as NASA scientists use to study the Biosphere, whereby they apply what they kn
This mini lesson focuses on Landsat satellite data and how it is used to detect changes in land use. Students will answer questions based off of a NASA Video that features how Landsat data are interpreted in the forests of the Pacific Northwest, and gives examples of the effects insects and logging have with land management.
Students analyze and compare satellite data of Ocean Chlorophyll Concentrations with Sea Surface Temperatures, beginning with the North Atlantic region, while answering questions about the global patterns of these phenomenon.
In this interactive, students will learn the basics of space weather by engaging in a short interactive which introduces key terms: space weather, sunspot, solar flare, coronal mass ejection, and solar wind. Students will be able to identify the causes and hazards of space weather.
In this interactive, students will explore safe methods for viewing the Sun at home or in the classroom, including using solar eclipse glasses and a pinhole projector. The interactive includes a video that explains how the projector works and how to build one.
Students will analyze and interpret maps of the average net atmospheric radiation to compare the flow of energy from the Sun toward Earth in different months and for cloudy versus clear days. Students will draw conclusions and support them with evidence.
Students observe monthly images of changing vegetation patterns, looking for seasonal changes occurring throughout 2017. These data can be used by students to develop their own models of change.
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.